The Importance of Spreadsheets in the Digital Age

When it comes to tools that are ubiquitous and essential in today's digital landscape, spreadsheets are often one of the first things that come to mind. Whether you're a seasoned business professional or an individual looking to improve your productivity skills, understanding the world of spreadsheets is crucial for success. In this article, we'll delve into the fascinating realm of spreadsheets, exploring their evolution, common functions, and future prospects.

The Evolution of Spreadsheets

As Richie mentioned earlier, "there's only like 30 commonly used functions" in spreadsheets, making them incredibly versatile tools that can be used to tackle a wide range of tasks. This limited number of functions belies the complexity and power of spreadsheets, which have become an indispensable part of modern computing. From simple calculations to sophisticated data analysis, spreadsheets offer a flexible framework for users to create, manipulate, and present data in a clear and concise manner.

One of the most significant reasons why spreadsheets will continue to thrive is their adaptability. As new needs arise, users turn to spreadsheets to solve them, creating a long tail of applications that have become indispensable in modern businesses. This phenomenon was observed by Richie, who mentioned that "every single day, new use cases and needs arise" that are addressed through the creation of proprietary or purpose-built software.

The Sticky Nature of Spreadsheets

Another factor contributing to the enduring popularity of spreadsheets is their ability to adapt to changing requirements while maintaining compatibility with existing workflows. This "stickiness" is a hallmark of successful technology, as users become accustomed to working in a particular way and are reluctant to change. Richie's experience with an 20-year-old spreadsheet that continued to receive updates weekly is a testament to this phenomenon.

The Power of Backwards Compatibility

Spreadsheets have also learned from the discipline of programming, which emphasizes backwards compatibility. In order to avoid disruptions to existing workflows, software developers must ensure that new features and functionality are compatible with older versions of the software. This has resulted in spreadsheets becoming more sophisticated while remaining accessible to users.

Spreadsheets as a Stealth Way to Teach Programming

Interestingly, Richie mentioned that spreadsheets can be seen as a stealth way to teach people programming skills. By mastering spreadsheet functions and techniques, individuals can develop essential problem-solving skills and logical thinking, which are also valuable in the world of computer science. This realization has significant implications for educators and professionals looking to enhance their students' or colleagues' skills.

The Future of Spreadsheets

Looking ahead, it's clear that spreadsheets will continue to play a vital role in modern computing. With advancements in technology and new applications emerging, users can expect to see further innovations in the world of spreadsheets. Richie offered some sage advice for spreadsheet users: "having a conversation with someone who works in creating software" can help individuals learn from each other's expertise.

Ultimately, the world of spreadsheets is a rich and fascinating realm that offers much to explore and learn. By understanding their evolution, common functions, and future prospects, we can unlock their full potential and harness their power to improve our productivity, communication, and collaboration skills.

"WEBVTTKind: captionsLanguage: enthe software industry has been very busy building Fantastic Tools for data scientists and all the data experts but the everyday knowledge worker that still has to do quite a lot of work with data and numbers and visualization calculations and so on has been left with the humble spreadsheet for about 40 years and what what spreadsheet users often don't realize is that they are writing software they are you know spreadsheet are code they're just encoding relationships between data that lives in cells instead of writing kind of lines of code that get executed one after another uh really glad to have you on the show uh I'm gonna dive straight into the tricky question which is you're trying to build a company around spreadsheets but for such a long time when people think of spreadsheets it's either Excel or maybe more recently Google Sheets so what made you try and decide to take on these big competitors yeah so the the uh the long and short of it is that in my previous job as a BPO product management on click one of the kind of bi companies uh I uh I kind of realized that while we were making this you know accessible software for business people to do analysis and kind of uh look at their operational data there were still kind of these were power users told there were only a handful of people in each organization that really you have to use them and then they had a much larger viewership obviously but then uh and kind of everybody would go to these you know click people or Tableau people within their organization to have anything done with with uh with new dashboards being built out or analysis or something like that but then you know at the same time it's not like the people that they were servicing and that were mainly viewing uh the bi tools weren't working with data and numbers but they were just doing it in spreadsheets and uh that kind of led me on a on uh now six six year Journey or so to kind of kind of dive into that market and try to really understand it but I I think to sum it up I came to the conclusion that the software industry has been very busy uh building Fantastic Tools for data scientists and all the data experts but the everyday knowledge worker that still has to do quite a lot of work with data and numbers and visualization calculations and so on has been left with the humble spreadsheet for about 40 years and while it has evolved there hasn't been like any big step chains in the tooling we give to Everyday knowledge workers so that's kind of how I came to how we came to this Market I should then also be careful that we are not kind of you know we're not taking Excel and Google Sheets heads on we think of ourselves as the numbers tool for a new generation and what we mean by that is you know broad Strokes what the market looks like is uh Enterprise companies larger companies older companies somewhat generally speaking older people use Excel then you have companies started in the last maybe 15 years they would have started on Gmail they will be using the Google Suite now Google workspace and kind of over the last maybe five years the you know Google Sheets has in those organizations almost entirely replaced Excel but then you have kind of the the newest generation of companies Maybe started in the last five years they would probably also have started on Gmail and they're by the Google Suite that will be their anchor but they are also buying best of great tools like notion like canva like airtable and the like and those are our people so we we have the best numbers tool for that target audience Excel people and Google Sheets people can use grid as well for their benefit but our sweet spot is that kind of upcoming generation that is using uh cloud-based productivity tools that aren't necessarily a part of either the Microsoft or the Google stack that's really interesting that you sort of said um you've got these bi tools of power bi and click and Tableau and all this sort of thing and that actually even though they're sort of purporting to make data easy to use for everyone there's still too technical for a lot of people and so actually this is the reason spreadsheets still exist um so uh you also said um I'm spreadsheet's been around since the 1980s um so what are the sort of Innovations left uh is everything not invented already uh not quite but uh it's definitely been an innovation that has stuck around uh so I was lucky enough when I was living in Boston to get to know Dan bricklin uh the creator of uh physical the very first spreadsheet uh so that was released back in 79 and uh you know so came to the market and it was really it was the first business software ever made like it was the first reason anybody would bring a PC into an office before that there was no reason to there was nothing you could do at work with with PC uh personal computer uh so Visa calc was made for Apple II so Apple II were the first computers that made their way onto desks at uh in people's offices and the reason for that was physical so it was very transformational and immediately what people started doing wasn't only working with was it I think we typically think of when uh people are when we think of spreadsheets are you know calculations and financial models and the like but uh you know we also probably all know that people use spreadsheets as small databases they stand up almost like small business applications and so on and this happened uh right away like people were making CRM systems in physical before CRM was probably decades before CIA I was even a term and then now that's kind of broken off and I think it's 150 billion dollar industry uh the kind of the customer relationship management and then you you or you've more or less seen this with kind of entire categories of business software that they start to offer something and even and kind of when people are starting their businesses they may you know even today I think many companies first CRM system is a spreadsheet and then they figure out maybe when they have 100 customers that there might be a better solution to that but they are I mean the reason they've stuck around is that they are so flexible uh it's one of the biggest strength and probably also one of their biggest weakness but it's a very kind of um you know essentially just this concept of being able to have a two-dimensional text editor uh you know if it was nothing else is you know that is very compelling because there aren't any uh any uh like you you are uh you only have certain level of guidance and actually very low levels of guidance in terms of having to kind of Define your columns or kind of however you can just type anywhere and that's that allows for a lot of freedom and it kind of lowers the barrier to entry a lot and then you kind of the the waves that we've seen so this cult on Apple II uh the PC kind of the the the uh the doors based PC came out in uh in uh the early 80s and then Lotus one two three uh went on the rise you could open vesicle uh documents or physical spreadsheets and load this one to three but Lotus one to three quickly replaced uh vesicles because they were on this more powerful platform that became more ubiquitous then you go into the 90s then you have kind of the rise of the the windowed uh of Windows and kind of the windowed way of of working and Excel was first there and kind of made use of that and then in the um in the 2000s you have kind of a lot of work moving to the browser moving to the cloud and then Google Sheets comes in and takes uh uh takes advantage of that so what you've essentially seen is you've seen these kind of four waves now you know Google Sheets still is a contender Excel is still kind of the the uh 500 or 800 pound gorilla in that market but you have these kind of four Generations that each of them taking kind of each of them happening with a major wave in Computing and making some use of that but not fundamentally changing the way we kind of approach this work and I think that's for for the good but uh the the way kind of we uh think of it as a grid is first of all we're focused exclusively on the numbers side of what people do in spreadsheet others like airtable for example have done a great job of being there for you when you need something more modern and maybe a little bit more sophisticated uh if you're using a spreadsheet as a database but if you're doing numbers work in in um and you kind of realize that the traditional spreadsheets meaning Excel and Google Sheets aren't uh quite pulling it off for you because you are in this new generation you're using you have your your data in a notion database and you want to visualize it like that's just not easy to do with uh with Google Sheets let alone with Excel and that's where we kind of come in hook up with your notion data allow you to easily visualize that embed it back everything is live connected you can do calculations on top of it and so on so it's partially kind of this um kind of just being more mindful of this new technological stack the other big innovation we bring to the table is that uh one of the things that if you think like a computer scientist you will often think about kind of the the data layers the logic layer and the presentation layer and the spreadsheet uh is interesting in the way that it combines all three you know type in two numbers of data uh up them up that's logic and then you bold the result that's presentation and kind of you know obviously spreadsheet users don't think of it that way but this again is kind of both the strength and a weakness but while the spreadsheet has moved into the browser as kind of a user interface it hasn't really taken made the use of the browser as kind of the the media Rich interactive UI that the the web allows you to do and that's kind of what we do we separate we give you a new presentation layer so that when you have done your thinking and pull together your data and you've done your logic in the spreadsheet you can then as a modeler for us whoever kind of pulled the data together you can now give it kind of a guided narrative allow your uh your audience to get the right context interact with the right things without them you know being able to ruin your model or kind of looking at the wrong things and so on so that's that's kind of where we come in that's really interesting there's a lot to unpack there I actually like to get into a bit more about this sort of uh the combining of the different layers between like data and logic and presentation because that's one thing where um certainly if you've done any programming you're like oh that's a it's a it's a very weird Paradigm to switch to with with spreadsheets but if you're a spreadsheet User it's very very natural so um what sort of uh work have you done to try and separate these things or or make them distinguished right so so very early on it actually kind of uh I think the moment when I realized uh that you know not only is there a big opportunity just in this General space but here is a pain point is when kind of two things came together first of all I came across a survey that said that uh 88 of spreadsheet users on a regular basis have to share what they have pulled together in a spreadsheet with someone else at the same time I was hearing as I was talking to people a lot of um uncertainty around exactly that moment you know people don't like to send their Excel files or kind of share full access to uh their Google Sheets models with with others because they know that you know they can ruin the model they can look at the wrong things and so on so what people do instead is they copy paste things out of spreadsheets into Powerpoints and PDFs and emails and so on uh to kind of give it some narrative write some text around it but these are tedious to make they're tedious to update if you have to kind of change the numbers uh people will have different versions of things available to them and so on so this kind of combination of here's a here you have this fantastic tool for doing the the thinking and the uh let's say kind of the the the exploration and the thinking on the data and the the logic but it doesn't really have a proper presentation layer people are always moving somewhere else when they need to present their findings isn't that some something that we can kind of combine more because even though people are kind of putting trust into their their spreadsheets and they may be Bolding some lines to kind of you know help guide the eye to the the right things and so on those are mainly you know for well for themselves and also for the visuals that they end up copying out of their spreadsheets and pasting into something else I see I think like everyone's experienced the horror of like copying pasting bits of spreadsheets into a report so yeah I'm certainly glad if that's going away absolutely and you probably also kind of people probably also kind of recognize this their this moment in the meeting where somebody else but what if like you know something was different and then the answer is oh let's rerun the numbers and I'll get back to you wouldn't it be great if you were able to because the model is there just gonna you know change that around uh in the meeting and answer the question on the spot and kind of move on with it so that's kind of the the other thing that we we give we allow people to interact with the model without them having kind of the full uh ability to you know change things or ruin it or change things that you don't want people to be playing around with that's actually very cool because it it does seem like um that's one of the big problems with with doing data analysis is that quite often by the time you've answered the question the person who asked it doesn't care anymore because there's that sort of lag and being able to do sort of real-time updates to your analyzes is is pretty important to a lot of the time um okay so um I'd like to get into uh generative AI since it's such a huge topic and this is something you've been building into grid so um first of all can you just tell me in what ways do you think AI can improve spreadsheets so so uh maybe first kind of for uh the audience audience's perspective so grid offers a spreadsheet solution where you can edit spreadsheets in in a natural way and then you can uh kind of build this these great documents on top of them to present the data so you can do that either on top of spreadsheets that are built inside of Grid or you can pull in spreadsheets from Excel or Google Sheets or even data from notion and app table and other sources so in that context we have been thinking a lot about like everybody in the world we've been thinking a lot about kind of what does generative AI mean for for this uh market and for our space and and one of the things that are fairly obvious we are always looking for opportunities to make working with numbers less intimidating uh and you know uh do that by by making you know visualization super easy making kind of uh you know data work uh very approachable and so on and one of the things that you know especially uh people that aren't already advanced spreadsheet users struggle with is writing formulas so you know that there are formulas that can do a lot of different uh things but you don't know the names of the functions you don't know exactly you know what the syntax of it and so on so there's a quite a lot of discovery that tends to happen either in the documentation or just Googling the the web for Solutions and how do I write the formula that does X uh we decided kind of the first step we decided to take was to help this user uh by integrating uh formula assistance into into grid so instead of writing we actually say kind of slash slash is the new equals uh and uh so you can start the formula by typing in slash or hitting kind of the the uh the formula assistant button and then you just type in natural language what you want your formula to do and it will come back with a suggested formula in the right syntax and so on and this works really really well and I'll say kind of I'll be candid when I say first when we try uh kind of started playing with this I thought this would be a great demo gimmick uh when we had kind of integrated and I saw how powerful it was I realized that this is great for novice users this is not just a demo gimmick this is actually useful for uh early spreadsheet doctors and then I find myself using it all the time myself even though I consider myself fairly Advanced spreadsheet user I find myself using it all the time because it's just faster than remembering what that function was called or what exactly the syntax looks like when you're doing kind of the the lookups or the Sorting or some of the more kind of intermediate uh complexity things that that you tend to do in in spreadsheets so uh it's it's really a fantastic uh addition to the spreadsheet and something that I think will become table stakes in spreadsheet software uh within too long um uh at the same time I think there are there are a few other areas where generative AI will play uh you know it will probably play uh you know in the analytics industry more generally speaking I think it will play in several different places but if we think about a spreadsheet in particular you already see people doing data enrichment using generative AI so essentially you draw you can draw a skeleton of some data you want to fill in most of the demos I've seen are kind of you have countries uh on the uh on kind of uh in the rows and then you may have kind of capital population those types of things and uh as uh the headers to the columns and then you have generative AI filling them in um this is this is uh fairly good at the same time you know most often people are working with their own proprietary data and kind of things that you would be looking up from from internal systems so at least kind of open AIS models that are trained on the open web will not be able to answer those types of of questions but it kind of hints at what could be done if you feed such models with your own business data and you how kind of much work that could save the third area that I would like to touch upon and and this is kind of I think uh true of a lot of things that people are are applying generative AI to these days they have great assistance they can save you a lot of work they can you know they can be very creative meaning they can help you kind of explore uh uh a space that you may not wear you know and go into parts of kind of an exploration space where you might have had a blind spot before but I think we should look at them as assistance and not as experts so meaning that you know the difference between if you if you have an assistant they may do a lot of your work they may save you a lot of time but in the end you are responsible for their work if you turn to an expert you actually expect them to know more than yourself about the domain and kind of come back with answers that you will trust almost without kind of uh you know with without a second thought and that is kind of you know with generative AI uh I think that is dangerous like we want people to be looking at them as assistants and kind of applying them their own domain knowledge and and so on to what they're worth before submitting it or accepting it but I think we are kind of one of the hardest things will be the right expectation management to kind of explain to people that you can't just throw in a question and get a perfect answer back and don't have to have to think about it and this is where in in the spreadsheet world but I think this applies is I think there is some expectation that soon we will be able to you know a financial modeler's job will be able to be solved by a generative model you you'll be able to kind of prompt it and say make me a you know maybe a five-year budget for you know a company that is so and so and you know explain kind of the characteristics of your business and that is not within the realm of the possible uh you know of the the current Uh current generation of AI and I'll just be bold and say state that out loud that's really interesting and I think one of the big fears with using um AI is that it sometimes gets the wrong answer and if you make mistake particularly um if it comes up with a formula in a financial spreadsheet and the number's wrong then that could have huge implications for your business so do you have any recommendations for how you deal with um like potential wrongness I mean you mentioned the idea of it being an assistant but uh do you have any other sort of advice well it's not like we haven't had these problems in the past that have huge errors have been made by humans making the the wrong formulas and I think in many ways the same things apply here you know uh apply a second set of eyes on anything that that matters try to build in uh checks you know where wherever possible uh and and so on and there is kind of a whole actually when it comes to these kind of business critical type of strategies there's a whole school of kind of best practices uh in those types of modeling uh and you know often you know as as we know there are there is a whole category of just financial planning software that kind of goes uh you know what movie that moves that out of the spreadsheet into something a little bit more rigid which may often be the right solution uh but you know in in general I think that it comes down to uh I think this is probably the biggest thing we have to kind of solve with generative AI generally is just how do we make sure people double check how do we make sure that people don't trust these things uh blindly and that applies inside of the spreadsheet as it does anywhere else what we've been trying to do is kind of build in little hints you know we don't submit the formula we show you the formula formula and the potential result so you can kind of check it before you accept it but there's probably kind of more Discovery needed there to just understand you know what's the right level of what I want you to say what what's the right level of of competence we should tell people to to have in this and you know that's that's actually one of the things that generative AI doesn't do terribly well it it doesn't know it it doesn't know uh itself how confident it is and the answers it it returns that's really interesting um okay so one um other area where it seems like AI could be useful is in the explanation of results so have you put any thought into how you uh go from results to some kind of interpretation if you want to do reporting absolutely there's been uh you know there have been um experiments in the more and promote more broadly in the analytics industry for I want to say almost a decade now with just you know generated uh narratives around data uh you know before the before we had the the current generation of of generative AI these were often very kind of dry like they were often templated where you had kind of pre-written text and then maybe kind of you changed some adjectives based on if the number was positive or negative or or things like that uh but you know there were certainly things that were slightly more sophisticated than that uh I found this area fascinating and I think there's definitely you know there are definitely things there Microsoft is is making some inroads and at least the way they talk about and demo uh the co-pilot that they are introducing for the entire Suite they kind of they they uh say it can be applied to kind of write a narrative around your your data I'm curious to see kind of how good it is and I think that once again we will have to look at it as an assistant that we will have to be very critical of the work it returns and then kind of make sure that we uh we read it through nicely but it's also interesting and I've always been fascinated by how much value we perceive in the text that explains what we see in the data so I remember I was talking to uh an analyst at one of the big research companies and he was his area of expertise was uh Financial solution or kind of fintech essentially and he said like they they offered two or two products you could buy one or the other or you could buy a bundle of the two and one product was a Tracker it tracked kind of uh products in the market and showed you month by month kind of the market share and how much it sold and things like that and then uh there was uh two pages that came out monthly but essentially made charts of the data that you could subscribe to and then explained in text what uh the data what the the chart was showing you and uh the much more popular product was the one that had less data in it in fact it had less uh information like there were fewer data points in that uh but uh but it had the the text explanation and maybe obviously kind of in some cases he was putting some perspective like a historical perspective or like it's typical of this company to do so and so on and so on so there's a value in that as well but then kind of that was that was actually more popular than even the bundle of the two so uh I think the you know there's a good reason people are exploring this because we want like numbers aren't something we're born to work with it's a very abstract way of thinking but words and language is something that we have an innate skill to to work with and therefore kind of translating insights into text is a huge area and this is something that we we've been uh exploring the interesting thing is kind of how to inject because spreadsheets themselves have very little semantic context you know they have like their individual cells they do have some relations between them there are some labels the labels can be uh can be put pretty much anywhere how do you teach uh generative AI to read the right level of semantics into that and be able to understand kind of you know that this is actually the Total Line and uh you know this is how the revenue was uh kind of the the components of the of the revenue number and things like that this is going to be an interesting area to to keep exploring that's really fascinating I like your example about the sort of the trading sort of newsletter where it's like actually having just a really short text summary was more useful than just vast amounts of data to a lot of people I suppose if you think about it well you know if you're trading stuff you already got a choice of like buy stuff hold stuff sell stuff then so getting closer to that is like is is actually pretty useful um so uh you mentioned that you're you're sort of quite an advanced spreadsheet usually yourself and I'm wondering um are the uses for AI different if you are an advanced user compared to if it's a very casual spreadsheet user or a beginner so in in what we have implemented uh I think that the highest the biggest value comes to the novice users the user that kind of has maybe always been afraid to even get started because they you know they don't even know where to where to begin uh so that's on the on the kind of formula assistant uh assistant side I however think that uh more broadly speaking you know generative AI will be an amplifier to pretty much every knowledge workers uh job so the more time you spend doing something the more time you spend in spreadsheets today uh the more value you will get out of generative AI once we learn how to properly uh apply it because there's just a larger number to to multiply so I think that you know that's where we will see the the most impactful uh Solutions in this space Comet to help people that you know it is to help the people that live and breathe spreadsheets uh day in day out already uh to you know maybe five or ten times more uh in you know in in every productive hour that they they get and what they can do today uh but at the same time our like we don't see ourselves as the the AIS brexit company we are just looking at AI as one of the tools that we can bring to make working with numbers less intimidating to the everyday knowledge worker especially kind of the the the young professional that is getting started in uh in their career and isn't already kind of an advanced spreadsheet user so uh you know it's not AI isn't Central to what we do it's uh you know one of the tools and you know now a very interesting new tool but we can take a look at and say how can we use this to help our user base and that's actually how I think most of the software industry should be thinking about AI like you are already you already have valuable software in a given space where you are a domain expert how can you apply AI in that space and you know to the the software the great software that's all uh already delivering value to your target audience rather than rethinking entirely how can AI make this radically different that will be the the role of uh startups that will be big in 10 years uh and you know uh yes you you may want to kind of keep an eye on it but your immediate opportunity as to how can I bring this into what we already have and make that better that seems a really good advice I'm assuming that's something we've been thinking about a lot at data Camp um is like we're not going to Pivot to becoming an AI company but sort of where can we build AI uh into datacab just to help people learn faster all right so um you mentioned there is not the only thing you've been working on and one thing I'd like to talk about is Integrations so you mentioned airtable before in the air table sort of big thing was it's a spreadsheet but it also helps you work alongside data into in a database uh and of course spreadsheets are only going to be like one tool of many if you're working with data so how does grid think about um integrating with other software so we are we are very uh we try to understand the tool stack of our uh target audience really well head table is one of the tools we see there are you know in this category of companies started in the last five maybe after 10 years there are and maybe especially kind of you know the tech companies and and companies that kind of on the Innovative side of the spectrum uh there are there are companies that have built almost their entire I.T infrastructure on Earth table you know we talked about CRM before they had their CRM and and airtable they may have some of their building and air table they may have some of the financials inevitable and so on so it's a really kind of for the companies that really embrace it it's this really big and important thing and yes uh airtable has used you know the positioning they took was they used you know get rid of the spreadsheet and things like that but they were really just talking about the database side of using spreadsheets meaning when people are using the the fact that you have this two-dimensional uh grid uh to type things into uh to us kind of a way to store contacts or other kind of tabular popular data uh like I said before our kind of our whole Spiel is to kind of be there for people when they are on the number side of things so the way we think about Integrations in that case is you know for people that are inevitable they will probably also want to do uh projections they will also want to do calculations they will also want to visualize the data and Report out on it in a uh in a kind of in a like I said before a guided narrative in kind of an approachable way so uh great is a fantastic tool to lay it on top of Earth table having your data in there creating charts and uh and narratives and grid and the reporting out on what you have inevitable and similarly uh you know notion uh which has been pushing their databases quite a lot and been super successful on the wiki long form document side of of things for for this uh for this demographic uh you know there like they don't have anything in terms of data visualizations let alone interactivity and calculations so that's kind of where where we come in and we try to plug that uh as well as we can so that data can flee flow freely between you know well if you're you know what we often see is kind of the tool stuck maybe you have your most advanced spreadsheets maybe in Google Sheets that can flow in through through grid and straight into your into your notion wiki page some of the data is in uh in an ocean database that can be combined on the same dashboard and then maybe some data and airtable flows nicely in that but it can also flow into mirror or into kind of one of the more visual uh Thinking Tools that you're working with and all of this is is really a breeze using grid but really cumbersome if you're using Google Sheets let alone Excel certainly I'd agree that with Excel and Google Sheets trying to get them to interact with other bits of software it just take a little bit of effort to get set up so it's nice something you're thinking about um one of the uh integration I'd like to talk about is with things like python uh um even SQL I mean you mentioned databases but um as a sort of data scientist my sort of tool of choice is going to be like python or R so uh how do those integrate with grid I have a lot of opinions but but our main target audience is kind of somebody that is not quite that technical so there was probably a runaway screaming if they see something that looks like code so that's not kind of our our sweet spot however obviously being able to kind of take uh you know a python uh function and making that available inside of a spreadsheet so that you can do calculations on the data that you have in a spreadsheet using an advanced function uh coming from from something else is uh is interesting and is kind of uh really valuable there are uh there are others that are kind of taking that on much more directly where we will probably kind of end up in in this hierarchy is we uh despite by making uh API apis available so that you can do these calls both ways and you can both write the grid and you can also call out to external systems from grid is probably kind of how we will enable this because again the the technical sophistication of the people that are writing the python code is probably they're going to be you know fine and kind of probably even prefer having kind of a restful API that they can interact with whether that is actually using uh great to call out to a function they've written in python or having python reach out to uh you know logic that has been written in a spreadsheet and I'll kind of drive that example home with an example uh you know we've seen we've seen quite a lot of people create pricing calculators using uh using grid so you know you have you know there's no doubt that the marketing department or kind of the product organization in inside of uh inside of a company will have a spreadsheet with the pricing plan somewhere and then they realize you know it may be a little bit complicated so we want to get it out on our web page and up until you know great the way to do that is you hire the web agency the web agency came in they rewrote the uh entire logic from your spreadsheet and then they would uh you know they would put up a calculator that customers could use on the uh on the website and that was that and then there was a change to the pricing and you would have to go back to the web Agency for them to kind of re- do the logic that was already redone in the in the spreadsheet uh with grid you know as soon as you have made the change in the spreadsheet and you have saved path to the right place then that is reflected in uh in the calculator that you've already built and if you want to do something more advanced so for example if you are a web department wants to plug into that or build kind of a custom UI on top of it or something like that you would be able to use an API to still use the logic that you know the the product of the marketing organization was well suited to put kind of into that spreadsheet but they would never be kind of consider themselves coders or be able to write that uh piece of code that would kind of come to the same results so that's kind of I hope that helps to kind of understand how we Bridge the you know here we have kind of this business site that is very well versed in their spreadsheet and that's how they work and then you have the more technical side that wants to work in code but you can bridge between the two worlds uh using something like grid okay that seems pretty useful uh so in that case what's the sort of middle case where you have business analysts who are working with power bi Tableau click all these sort of um bi tools uh how do they uh work with grid and as as well so there's definitely an overlap between what you can do in Grid and what you can do in these other tools uh the main thing and we are not here to kind of replace you know Pablo or power bi or click uh however we are here to enable an audience that up until now has not been able to kind of take the time it takes to learn these tools to do some of the same things not necessarily quite as sophisticated but kind of do things that are more akin to something that only people that knew these tools would have been doing before the other big distinction I'll make is that bi tools are about analyzing records and databases essentially records of things that have happened in the past so a bi you know if you if you want to be you want to be quick about it bi as a way to filter Source Aggregate and and limit kind of uh results that give you views on the records of things that have happened in the past but if a business is dreaming about the future it would be doing so in a model in a spreadsheet model so businesses analyzed it passed in bi with a dream about the future in spreadsheets one maybe uh criticism of spreadsheets is that uh sometimes it has problems uh particularly there was like a case of periods back where um the genetics the genetics Community had to renamed some genes because Excel just kept like changing the name to a date I think it was like the March one gene or something uh and so I think a lot of people might well AI is cool but I just want to have a spreadsheet that doesn't corrupt my data so how do you think about data quality and data Integrity yeah no so I I agree with I mean all of these credit systems are they're all correct and they come as a side effect of you know these tools trying to be uh trying to be very uh open and flexible to kind of different types of data entry and things like that maybe kind of in some cases like in the case of like a uh yeah I think it was like March one or and step nine were kind of the two that were often getting confused with with the gene names uh you know maybe it was being too lenient so maybe you can kind of you can you maybe you can have like targeted criticism about exactly what it did in those cases but more broadly speaking I think we often forget to uh to kind of uh talk about the flip side of it which is uh how much spreadsheets enable and Empower business users to do that they would otherwise not be able to do and the way to think about that in in my uh in kind of the way I'd encourage people to think about that is the reason people turn to spreadsheets so much uh is that uh you know you have you're faced with a new thing you're faced with like we're talking about the database uh thing before like maybe you have there are a hundred customers you have to call like for some reason so some service broke and you have to call 100 customers up or or reach out to them so you need that the names maybe a little bit of details about the incident that happened times you know phone numbers contact information those types of things and you have two choices you can either uh ask it to have a meeting where they can filter this view out of your CRM and maybe add some fields in the database where you can check if you've gotten a hold of them or not and and so on and it may be willing kind of if you have a priority project we may be willing to meet with you next week and then you know they will start the project and then four weeks later they will be able to kind of give you what you want so your alternative is I can do that I can go kind of the the official route and five weeks later be able to kind of start my job or I can fire up a blank uh spreadsheet maybe pull down the contact information from the CRM and just you know do it in a spreadsheet and I can do that you know before noon I can start calling them in the afternoon so it's obvious where the choice comes so when it comes to you know we should be careful of spreadsheet and we should know about the limitations but we should also not underestimate the empowerment that they are to perform kind of everyday business workers to take care of a lot of their everyday everyday I.T needs where they themselves are able to solve for something that otherwise they would need much more technical help to do okay yeah so um there is a gonna be a trade-off between um a spreadsheet being helpful for you and trying to like you know fix your data and giving you that extra productivity but occasionally it's going to do something wrong so you've got to be careful about like checking the results yeah so okay I I guess we would say the same of like our our uh our kind of um I.T systems I mean they sometimes have errors and those errors can uh can have uh big problems we are just more much more like in software development we tend to be or at least we we want to be much more disciplined when it comes to testing and uh uh and you know automated tests then and quality assurance but um you know uh things things still happen as We Know absolutely um all right so uh plotting is maybe the second area where traditionally um spreadsheets have been a little bit poor like just trying to do a histogram or a heat map which may be like not the most popular kind of plots but they're they're still fairly mainstream very difficult to do in Excel or Google Sheets so what's grid doing around improving visualization so we we have we have a bunch of visualization options and we are trying to the our approach is we want to you know make sure that the the basics are super easy so that you you know just put a lot of work into tuning Our you know uh column charts line charts and tables like these are these are if you take these three visualizations together you can portray pretty much anything sometimes you want to reach outside of of that range to to kind of you know to bring a particular Point home uh for example to heat much or or dock plots or something like that so you know we've we've been implementing those as well at the same time like here is uh here like the the way I see this moving forward is there are we we can probably never fulfill everybody's visualization needs with something that we build into the product so here is where kind of at some point like those more technically technically capable uh should have access to apis where if you want to go outside of what the tool offers out of the box you would be able to enable that and maybe you would be able to build that in a way that not only you can use it but you can make that available to other users of the tool as well so essentially an expansion type model there but uh but this is this is something we we think nearly about and kind of given our target audience also uh you know it is important there's sometimes a tendency especially when people are getting started with visualizations and so on that they they want to move on to something that is you know non-traditional when maybe a column chart is the best way to for them to actually portray the point they want to get across so we also want to kind of don't want to limit them and what they can do but we want to guide them to you know knowing when to use something other than just some of the basics because they are often the the right choice it does amaze me how far you can get with business analysis just by doing wine charts and bar plots um but occasionally yeah you do these other other plot types so it's uh it's like this long tail of different uh visualizations you need to use so that sort of um extension model does seem quite reasonable um now the third um area where I think spreadsheet struggle is with debugging so I think everyone's coming across the case where there's like there's a weird error somewhere and they end up clicking through cells to try and find out exactly which formula went wrong somewhere um so how do you think about improving the debugging experience for spreadsheets so this is a this is a fascinating area so um I'll I'll take a dive so you know the behind me behind every spreadsheet is a uh dependency graph and you will be surprised how complex that dependency graph can become very quickly meaning you know you make a cell I I made an example before where kind of you type a number and cell A1 and B1 and then C1 you add them up like that dependency tree is only one level deep but then you know as soon as you have like maybe you have a financial model with 10 assumptions and you're calculating that for you know monthly for five years or something like that you will you know by now you will have a couple of thousand nodes and the number of links between those nodes will be in the tens of thousands and the depth of the three will probably be you know or the depth of the of the graph will probably be I don't know 25 30 levels deep easily so it's uh it's kind of obvious that it's easy to get lost in that somewhere and it's also kind of obvious that it may be hard to trace exactly where in all those kind of dependencies going up 25 levels to to hundreds of cells uh to come to a conclusion in a single cell can be can be hard so we have one of the Privileges of uh the job I have is that we had to build our own spreadsheet engine from scratch so we are by far the most powerful spreadsheet engine that can run entirely in JavaScript uh and in there by kind of in your browser that was needed to be able to kind of make fast interactions uh happen with uh with large spreadsheet models uh in in a browser so therefore we had to kind of take a deep dive here and there are we have only kind of just begun to scratch the surface of making this available to our users but the tools we have internally to kind of debug just as we are developing the spreadsheet engine are fascinating so when you kind of you're able to see the intermed immediate results and kind of how they flow and exactly where so for example if you have an address to be able to trace from the cell where the error manifests itself to where it actually first started propagating which is something that you know Excel or Google Sheets do nothing to help you help you do you will have to just realize which one of all these cells that are now throwing an error are at the root of the dependencies for for what you're looking for and I think there are a lot of opportunities to do more there and uh again we have to kind of be mindful of what's useful to our target audience that aren't necessarily the most sophisticated ones but I've seen kind of a I've seen a major opportunity also in just applying that to a much more advanced audience where you can we can kind of throw at them analysis of their of their spreadsheet and kind of maybe also point out non-obvious errors like omissions in uh in cell ranges and things like that that happen all the time uh where you know you've added up all but the you know last two months of something and therefore you had the wrong sum somewhere Excel tries to help you in Google Sheets as well but if you aren't like visually looking at the right place in the model uh there will be no uh there will be no cue for you to look at so so yeah so it's it's an absolutely fascinating area and the the dependency graph is uh especially when you think of a kind of dependency dependency graphs come obviously come up in all sorts of uh computer science Solutions but the kind of a calculation dependency graph like uh spreadsheets is is a super fascinating area both two kind of try to optimize you know there are so many places where you can optimize for Speed and uh and memory and and all sorts of things but also just in the way that it manifests essentially a large algorithm that you what you have in a dependency graph is an algorithm you could write traditional code that would come to the same conclusion now good luck debugging that so so that's kind of uh but you know you have these business users that are creating these complex algorithms just by uh essentially offloading their thinking cell by cell or line by line row by row into a spreadsheet model I find it fascinating because we normally talk about dependency graphs in the context of data engineering and scheduling like when your different analyzes are going to run and the fact that actually um the spreadsheet uh like the engine is sort of using the same graphs uh to run the calculations and this can be helpful for debugging that that's a really interesting sort of coincidence for for those for those that are kind of interested in those types of things in the audience I think they'll be fascinating to know that dependency graphs were not there in the very first spreadsheets so the way they would calculate is they would just first calculate cell A1 and then B1 and C1 and then it would go row by row so you could only do calculations that would refer up and to the right up and to the left and if the calculation was referring uh either down or to the right you'd have to re-run the model a few times before you got a persistent result wow that's pretty inefficient uh yeah so I guess I'm glad we we have graph uh based engines now right all right so um we talk a lot about data literacy on this podcast and so um how do you think spreadsheets can be used to help uh novices get started with data I would go as far as saying spreadsheets are probably where novices start with data uh so I mean it's probably the First Data tool most of us are at least first freeform data to alert like free uh pre-expiration data exploration tool is maybe kind of the way to put it that we come across uh I actually I have been surprised as I've taken a dive into this how but the first time user experience is with spreadsheets they have been able to rely on a lot of uh ingrained knowledge inside of businesses and universities and and everywhere else but when people are starting to use spreadsheets they can turn to something somebody that already knows how to use them that's how most people you know that's how most people get a big chunk of their initial learning there so I think that uh you know just first time user experience in general and maybe as I alluded to before being better about kind of best practices teaching people best practices while they are doing things for the first time like okay you want the pie chart you know that can be good but you know here is when a pie chart is a good solution for you and here are some of the reasons you know you might not uh want to use them and then oh you know I I learned something I should be using a different type of visualization to get my point across whereas kind of today we just throw people in and they we have there's no guidance neither on properly how to use the functions of the tools nor of you know what good data analysis and and presentation of data results looks like yeah I I do agree that uh spreadsheets had like a really good sort of starting point for um working Daytona and so it just seem like some level of spreadsheet competency is pretty important in almost every data role but do you have a sense of like what the most important spreadsheet skills are like Jesus needs to be really good at formulas or figuring out macros or what's the deal it obviously it depends depends a bit on your role one of the interesting things about uh Myspace and maybe kind of in some ways in talking to you know your audience is that the people who are the least likely to rely on spreadsheets in their work are techies because they have we have other tools at our disposal to do the things that normal people have to have to do in spreadsheets so we we are a little bit blind to uh often how much they just drive they run the world like you know the whole business side of our organizations are driven by spreadsheets the decision making many of the processes like a lot of things are just driven off of a spreadsheets that we've never seen and we are largely unaware that they even exist so I think that um I I'm very much kind of the numbers side of things so I think that kind of the yes getting the the basic uh the basic kind of formula skills right uh is a great way to uh it is a very important uh way to start and the funny thing there is kind of you can master uh I'll I'll give you a a a statistic so the top 30 spreadsheet functions meaning the most the 30 most used functions in spreadsheet they actually cover more than 98 all spreadsheet in the world so only two percent of spreadsheets use functions that are not one of these kind of 30 most used ones so kind of Master the master the the the most uh commonly used ones and you are going to be you know well well ahead of a lot of your your colleagues I think also um you know after that after kind of having gotten enough skill to get the job done meaning to get your thinking out and doing the analysis or uh or um you're getting to kind of uh the the results that you were looking for then I think the the skill after that is how do I communicate this like how do I properly tell the story what is the data telling me and how can how should I uh present that to someone so it makes an impact uh and that is definitely something that spreadsheets don't help you with that is something that you know some somebody like us uh that's our kind of bread and butter helping you with the narrative and the presentation and that is kind of I think the skill that comes after like first you have to first you need to learn how to work with data and think and maybe kind of maybe the part that I overlooked is you know the amount of data cleansing and uh and uh manipulation you often have to do before you can start your your actual work so kind of you know learning some tips and tricks there is definitely useful but then on the other side of that if you're not showing this to someone it's like it's worthless it's just in your head and usually like I said 88 of the time people find themselves presenting what they have pulled together in respected to someone else and that is an important skill to have that's uh kind of interesting the idea that actually I think he said there's only like 30 commonly used functions or something so and now think about it yeah you probably can get a long way with just being able to do like summon average and then maybe the occasional if statement so yeah actually the hardest bit is being able to communicate what your results are to other people um yeah yeah I I can certainly agree with that um all right so um I know talking about the future is a bit of a mugs game but I would like your opinions on what you think the long-term future is uh for their spreadsheets I think spreadsheets in like the spreadsheet the way we think about them when I say the word right now are probably going to be around for a long time you know I'm I'm willing to I'm willing to wager at bet for 20 years and I wouldn't be surprised if if it's a lot longer uh the reason for that uh is you know there are several reasons for that first of all they are a pretty well proven way of doing uh a lot of things like they're very generic open-ended tools and while ever since kind of the physical case people have been kind of chipping off you know major use cases and making proprietary or purpose-built software to uh to better do something that people have been doing in spreadsheets new um needs arise every single day as well and people who turn to spreadsheets to to solve them so uh and that is that is going to be like spreadsheet user usage hasn't gone down uh uh you know with more and more proprietary and software being built for some of these uses it's actually gone up and the reason is for everything you chop off there's just more added to the long tail uh that kind of needs to be solved as well the other is that just so many processes uh so much knowledge so many assets that already rely on things within businesses and I think we especially us on the kind of I I imagine a lot of people listening here on are very much on the early adopters end of the curve I think we tend to underestimate how sticky things can that work can be you know I've seen spreadsheets that have been updated weekly for 20 years and I'm not joking like there are there's a role added to a spreadsheet every week and that spreadsheet started 20 years ago so these types of things happen and they happen because it works and it's what the business user has or the disposal and you know there's no reason to change it if it works well the the 20th spreadsheet I mean I guess having long-term compatibility is amazing it also seems like slightly terrifying that that thing exists you know and and the interesting thing here is that nothing interesting has happened in this space without being backwards compatible with what came before it some of the decisions made by Dan Brecklin who I'm referred to before before the maker of physical and his dorm room in Harvard in uh you know 1978 are still the way we write formulas and spreadsheet today because uh Lotus one two three had to be backwards compatible with vertical Excel had to be backwards compatible with lotus one two three Google Sheets was backwards compatible with Excel from day one and even though each and every one of us uh you know are acting on some new functionality whatever Paradigm comes next will have to be backwards compatible with what we have today do you have any final advice for spreadsheet users yeah I mean obviously I'd tell them to go and try out grid it will add to your to your life uh it will help you uh better kind of present the the uh the things that you have uh pulled together but more generally speaking I think that you know maybe um maybe kind of having a conversation with you know somebody that works in creating software because what what spreadsheet users often don't realize is that they are writing software they are you know spreadsheets are code they're just encoding relationships between data that lives in cells instead of writing kind of lines of code that get executed one after another uh but we haven't like the spreadsheet world hasn't learned has a lot to learn from some of the discipline and even just very simple things like having a check some somewhere like somewhere where you know you know that if everything works the result in this cell should be you know a certain number having those kind of checks in place even though it kind of isn't anything more than that will often kind of save you a lot of pain somewhere so yeah learning from you know have a have a peer conversation with uh with a computer scientist and see what you can learn from each other that's brilliant I love the idea of spreadsheets as being like a stealth way to teach people programming uh fantastic okay all right uh with that uh thank you for being on the show uh I hope you enjoyed the experience this was uh great fun thank you Richie foreignthe software industry has been very busy building Fantastic Tools for data scientists and all the data experts but the everyday knowledge worker that still has to do quite a lot of work with data and numbers and visualization calculations and so on has been left with the humble spreadsheet for about 40 years and what what spreadsheet users often don't realize is that they are writing software they are you know spreadsheet are code they're just encoding relationships between data that lives in cells instead of writing kind of lines of code that get executed one after another uh really glad to have you on the show uh I'm gonna dive straight into the tricky question which is you're trying to build a company around spreadsheets but for such a long time when people think of spreadsheets it's either Excel or maybe more recently Google Sheets so what made you try and decide to take on these big competitors yeah so the the uh the long and short of it is that in my previous job as a BPO product management on click one of the kind of bi companies uh I uh I kind of realized that while we were making this you know accessible software for business people to do analysis and kind of uh look at their operational data there were still kind of these were power users told there were only a handful of people in each organization that really you have to use them and then they had a much larger viewership obviously but then uh and kind of everybody would go to these you know click people or Tableau people within their organization to have anything done with with uh with new dashboards being built out or analysis or something like that but then you know at the same time it's not like the people that they were servicing and that were mainly viewing uh the bi tools weren't working with data and numbers but they were just doing it in spreadsheets and uh that kind of led me on a on uh now six six year Journey or so to kind of kind of dive into that market and try to really understand it but I I think to sum it up I came to the conclusion that the software industry has been very busy uh building Fantastic Tools for data scientists and all the data experts but the everyday knowledge worker that still has to do quite a lot of work with data and numbers and visualization calculations and so on has been left with the humble spreadsheet for about 40 years and while it has evolved there hasn't been like any big step chains in the tooling we give to Everyday knowledge workers so that's kind of how I came to how we came to this Market I should then also be careful that we are not kind of you know we're not taking Excel and Google Sheets heads on we think of ourselves as the numbers tool for a new generation and what we mean by that is you know broad Strokes what the market looks like is uh Enterprise companies larger companies older companies somewhat generally speaking older people use Excel then you have companies started in the last maybe 15 years they would have started on Gmail they will be using the Google Suite now Google workspace and kind of over the last maybe five years the you know Google Sheets has in those organizations almost entirely replaced Excel but then you have kind of the the newest generation of companies Maybe started in the last five years they would probably also have started on Gmail and they're by the Google Suite that will be their anchor but they are also buying best of great tools like notion like canva like airtable and the like and those are our people so we we have the best numbers tool for that target audience Excel people and Google Sheets people can use grid as well for their benefit but our sweet spot is that kind of upcoming generation that is using uh cloud-based productivity tools that aren't necessarily a part of either the Microsoft or the Google stack that's really interesting that you sort of said um you've got these bi tools of power bi and click and Tableau and all this sort of thing and that actually even though they're sort of purporting to make data easy to use for everyone there's still too technical for a lot of people and so actually this is the reason spreadsheets still exist um so uh you also said um I'm spreadsheet's been around since the 1980s um so what are the sort of Innovations left uh is everything not invented already uh not quite but uh it's definitely been an innovation that has stuck around uh so I was lucky enough when I was living in Boston to get to know Dan bricklin uh the creator of uh physical the very first spreadsheet uh so that was released back in 79 and uh you know so came to the market and it was really it was the first business software ever made like it was the first reason anybody would bring a PC into an office before that there was no reason to there was nothing you could do at work with with PC uh personal computer uh so Visa calc was made for Apple II so Apple II were the first computers that made their way onto desks at uh in people's offices and the reason for that was physical so it was very transformational and immediately what people started doing wasn't only working with was it I think we typically think of when uh people are when we think of spreadsheets are you know calculations and financial models and the like but uh you know we also probably all know that people use spreadsheets as small databases they stand up almost like small business applications and so on and this happened uh right away like people were making CRM systems in physical before CRM was probably decades before CIA I was even a term and then now that's kind of broken off and I think it's 150 billion dollar industry uh the kind of the customer relationship management and then you you or you've more or less seen this with kind of entire categories of business software that they start to offer something and even and kind of when people are starting their businesses they may you know even today I think many companies first CRM system is a spreadsheet and then they figure out maybe when they have 100 customers that there might be a better solution to that but they are I mean the reason they've stuck around is that they are so flexible uh it's one of the biggest strength and probably also one of their biggest weakness but it's a very kind of um you know essentially just this concept of being able to have a two-dimensional text editor uh you know if it was nothing else is you know that is very compelling because there aren't any uh any uh like you you are uh you only have certain level of guidance and actually very low levels of guidance in terms of having to kind of Define your columns or kind of however you can just type anywhere and that's that allows for a lot of freedom and it kind of lowers the barrier to entry a lot and then you kind of the the waves that we've seen so this cult on Apple II uh the PC kind of the the the uh the doors based PC came out in uh in uh the early 80s and then Lotus one two three uh went on the rise you could open vesicle uh documents or physical spreadsheets and load this one to three but Lotus one to three quickly replaced uh vesicles because they were on this more powerful platform that became more ubiquitous then you go into the 90s then you have kind of the rise of the the windowed uh of Windows and kind of the windowed way of of working and Excel was first there and kind of made use of that and then in the um in the 2000s you have kind of a lot of work moving to the browser moving to the cloud and then Google Sheets comes in and takes uh uh takes advantage of that so what you've essentially seen is you've seen these kind of four waves now you know Google Sheets still is a contender Excel is still kind of the the uh 500 or 800 pound gorilla in that market but you have these kind of four Generations that each of them taking kind of each of them happening with a major wave in Computing and making some use of that but not fundamentally changing the way we kind of approach this work and I think that's for for the good but uh the the way kind of we uh think of it as a grid is first of all we're focused exclusively on the numbers side of what people do in spreadsheet others like airtable for example have done a great job of being there for you when you need something more modern and maybe a little bit more sophisticated uh if you're using a spreadsheet as a database but if you're doing numbers work in in um and you kind of realize that the traditional spreadsheets meaning Excel and Google Sheets aren't uh quite pulling it off for you because you are in this new generation you're using you have your your data in a notion database and you want to visualize it like that's just not easy to do with uh with Google Sheets let alone with Excel and that's where we kind of come in hook up with your notion data allow you to easily visualize that embed it back everything is live connected you can do calculations on top of it and so on so it's partially kind of this um kind of just being more mindful of this new technological stack the other big innovation we bring to the table is that uh one of the things that if you think like a computer scientist you will often think about kind of the the data layers the logic layer and the presentation layer and the spreadsheet uh is interesting in the way that it combines all three you know type in two numbers of data uh up them up that's logic and then you bold the result that's presentation and kind of you know obviously spreadsheet users don't think of it that way but this again is kind of both the strength and a weakness but while the spreadsheet has moved into the browser as kind of a user interface it hasn't really taken made the use of the browser as kind of the the media Rich interactive UI that the the web allows you to do and that's kind of what we do we separate we give you a new presentation layer so that when you have done your thinking and pull together your data and you've done your logic in the spreadsheet you can then as a modeler for us whoever kind of pulled the data together you can now give it kind of a guided narrative allow your uh your audience to get the right context interact with the right things without them you know being able to ruin your model or kind of looking at the wrong things and so on so that's that's kind of where we come in that's really interesting there's a lot to unpack there I actually like to get into a bit more about this sort of uh the combining of the different layers between like data and logic and presentation because that's one thing where um certainly if you've done any programming you're like oh that's a it's a it's a very weird Paradigm to switch to with with spreadsheets but if you're a spreadsheet User it's very very natural so um what sort of uh work have you done to try and separate these things or or make them distinguished right so so very early on it actually kind of uh I think the moment when I realized uh that you know not only is there a big opportunity just in this General space but here is a pain point is when kind of two things came together first of all I came across a survey that said that uh 88 of spreadsheet users on a regular basis have to share what they have pulled together in a spreadsheet with someone else at the same time I was hearing as I was talking to people a lot of um uncertainty around exactly that moment you know people don't like to send their Excel files or kind of share full access to uh their Google Sheets models with with others because they know that you know they can ruin the model they can look at the wrong things and so on so what people do instead is they copy paste things out of spreadsheets into Powerpoints and PDFs and emails and so on uh to kind of give it some narrative write some text around it but these are tedious to make they're tedious to update if you have to kind of change the numbers uh people will have different versions of things available to them and so on so this kind of combination of here's a here you have this fantastic tool for doing the the thinking and the uh let's say kind of the the the exploration and the thinking on the data and the the logic but it doesn't really have a proper presentation layer people are always moving somewhere else when they need to present their findings isn't that some something that we can kind of combine more because even though people are kind of putting trust into their their spreadsheets and they may be Bolding some lines to kind of you know help guide the eye to the the right things and so on those are mainly you know for well for themselves and also for the visuals that they end up copying out of their spreadsheets and pasting into something else I see I think like everyone's experienced the horror of like copying pasting bits of spreadsheets into a report so yeah I'm certainly glad if that's going away absolutely and you probably also kind of people probably also kind of recognize this their this moment in the meeting where somebody else but what if like you know something was different and then the answer is oh let's rerun the numbers and I'll get back to you wouldn't it be great if you were able to because the model is there just gonna you know change that around uh in the meeting and answer the question on the spot and kind of move on with it so that's kind of the the other thing that we we give we allow people to interact with the model without them having kind of the full uh ability to you know change things or ruin it or change things that you don't want people to be playing around with that's actually very cool because it it does seem like um that's one of the big problems with with doing data analysis is that quite often by the time you've answered the question the person who asked it doesn't care anymore because there's that sort of lag and being able to do sort of real-time updates to your analyzes is is pretty important to a lot of the time um okay so um I'd like to get into uh generative AI since it's such a huge topic and this is something you've been building into grid so um first of all can you just tell me in what ways do you think AI can improve spreadsheets so so uh maybe first kind of for uh the audience audience's perspective so grid offers a spreadsheet solution where you can edit spreadsheets in in a natural way and then you can uh kind of build this these great documents on top of them to present the data so you can do that either on top of spreadsheets that are built inside of Grid or you can pull in spreadsheets from Excel or Google Sheets or even data from notion and app table and other sources so in that context we have been thinking a lot about like everybody in the world we've been thinking a lot about kind of what does generative AI mean for for this uh market and for our space and and one of the things that are fairly obvious we are always looking for opportunities to make working with numbers less intimidating uh and you know uh do that by by making you know visualization super easy making kind of uh you know data work uh very approachable and so on and one of the things that you know especially uh people that aren't already advanced spreadsheet users struggle with is writing formulas so you know that there are formulas that can do a lot of different uh things but you don't know the names of the functions you don't know exactly you know what the syntax of it and so on so there's a quite a lot of discovery that tends to happen either in the documentation or just Googling the the web for Solutions and how do I write the formula that does X uh we decided kind of the first step we decided to take was to help this user uh by integrating uh formula assistance into into grid so instead of writing we actually say kind of slash slash is the new equals uh and uh so you can start the formula by typing in slash or hitting kind of the the uh the formula assistant button and then you just type in natural language what you want your formula to do and it will come back with a suggested formula in the right syntax and so on and this works really really well and I'll say kind of I'll be candid when I say first when we try uh kind of started playing with this I thought this would be a great demo gimmick uh when we had kind of integrated and I saw how powerful it was I realized that this is great for novice users this is not just a demo gimmick this is actually useful for uh early spreadsheet doctors and then I find myself using it all the time myself even though I consider myself fairly Advanced spreadsheet user I find myself using it all the time because it's just faster than remembering what that function was called or what exactly the syntax looks like when you're doing kind of the the lookups or the Sorting or some of the more kind of intermediate uh complexity things that that you tend to do in in spreadsheets so uh it's it's really a fantastic uh addition to the spreadsheet and something that I think will become table stakes in spreadsheet software uh within too long um uh at the same time I think there are there are a few other areas where generative AI will play uh you know it will probably play uh you know in the analytics industry more generally speaking I think it will play in several different places but if we think about a spreadsheet in particular you already see people doing data enrichment using generative AI so essentially you draw you can draw a skeleton of some data you want to fill in most of the demos I've seen are kind of you have countries uh on the uh on kind of uh in the rows and then you may have kind of capital population those types of things and uh as uh the headers to the columns and then you have generative AI filling them in um this is this is uh fairly good at the same time you know most often people are working with their own proprietary data and kind of things that you would be looking up from from internal systems so at least kind of open AIS models that are trained on the open web will not be able to answer those types of of questions but it kind of hints at what could be done if you feed such models with your own business data and you how kind of much work that could save the third area that I would like to touch upon and and this is kind of I think uh true of a lot of things that people are are applying generative AI to these days they have great assistance they can save you a lot of work they can you know they can be very creative meaning they can help you kind of explore uh uh a space that you may not wear you know and go into parts of kind of an exploration space where you might have had a blind spot before but I think we should look at them as assistance and not as experts so meaning that you know the difference between if you if you have an assistant they may do a lot of your work they may save you a lot of time but in the end you are responsible for their work if you turn to an expert you actually expect them to know more than yourself about the domain and kind of come back with answers that you will trust almost without kind of uh you know with without a second thought and that is kind of you know with generative AI uh I think that is dangerous like we want people to be looking at them as assistants and kind of applying them their own domain knowledge and and so on to what they're worth before submitting it or accepting it but I think we are kind of one of the hardest things will be the right expectation management to kind of explain to people that you can't just throw in a question and get a perfect answer back and don't have to have to think about it and this is where in in the spreadsheet world but I think this applies is I think there is some expectation that soon we will be able to you know a financial modeler's job will be able to be solved by a generative model you you'll be able to kind of prompt it and say make me a you know maybe a five-year budget for you know a company that is so and so and you know explain kind of the characteristics of your business and that is not within the realm of the possible uh you know of the the current Uh current generation of AI and I'll just be bold and say state that out loud that's really interesting and I think one of the big fears with using um AI is that it sometimes gets the wrong answer and if you make mistake particularly um if it comes up with a formula in a financial spreadsheet and the number's wrong then that could have huge implications for your business so do you have any recommendations for how you deal with um like potential wrongness I mean you mentioned the idea of it being an assistant but uh do you have any other sort of advice well it's not like we haven't had these problems in the past that have huge errors have been made by humans making the the wrong formulas and I think in many ways the same things apply here you know uh apply a second set of eyes on anything that that matters try to build in uh checks you know where wherever possible uh and and so on and there is kind of a whole actually when it comes to these kind of business critical type of strategies there's a whole school of kind of best practices uh in those types of modeling uh and you know often you know as as we know there are there is a whole category of just financial planning software that kind of goes uh you know what movie that moves that out of the spreadsheet into something a little bit more rigid which may often be the right solution uh but you know in in general I think that it comes down to uh I think this is probably the biggest thing we have to kind of solve with generative AI generally is just how do we make sure people double check how do we make sure that people don't trust these things uh blindly and that applies inside of the spreadsheet as it does anywhere else what we've been trying to do is kind of build in little hints you know we don't submit the formula we show you the formula formula and the potential result so you can kind of check it before you accept it but there's probably kind of more Discovery needed there to just understand you know what's the right level of what I want you to say what what's the right level of of competence we should tell people to to have in this and you know that's that's actually one of the things that generative AI doesn't do terribly well it it doesn't know it it doesn't know uh itself how confident it is and the answers it it returns that's really interesting um okay so one um other area where it seems like AI could be useful is in the explanation of results so have you put any thought into how you uh go from results to some kind of interpretation if you want to do reporting absolutely there's been uh you know there have been um experiments in the more and promote more broadly in the analytics industry for I want to say almost a decade now with just you know generated uh narratives around data uh you know before the before we had the the current generation of of generative AI these were often very kind of dry like they were often templated where you had kind of pre-written text and then maybe kind of you changed some adjectives based on if the number was positive or negative or or things like that uh but you know there were certainly things that were slightly more sophisticated than that uh I found this area fascinating and I think there's definitely you know there are definitely things there Microsoft is is making some inroads and at least the way they talk about and demo uh the co-pilot that they are introducing for the entire Suite they kind of they they uh say it can be applied to kind of write a narrative around your your data I'm curious to see kind of how good it is and I think that once again we will have to look at it as an assistant that we will have to be very critical of the work it returns and then kind of make sure that we uh we read it through nicely but it's also interesting and I've always been fascinated by how much value we perceive in the text that explains what we see in the data so I remember I was talking to uh an analyst at one of the big research companies and he was his area of expertise was uh Financial solution or kind of fintech essentially and he said like they they offered two or two products you could buy one or the other or you could buy a bundle of the two and one product was a Tracker it tracked kind of uh products in the market and showed you month by month kind of the market share and how much it sold and things like that and then uh there was uh two pages that came out monthly but essentially made charts of the data that you could subscribe to and then explained in text what uh the data what the the chart was showing you and uh the much more popular product was the one that had less data in it in fact it had less uh information like there were fewer data points in that uh but uh but it had the the text explanation and maybe obviously kind of in some cases he was putting some perspective like a historical perspective or like it's typical of this company to do so and so on and so on so there's a value in that as well but then kind of that was that was actually more popular than even the bundle of the two so uh I think the you know there's a good reason people are exploring this because we want like numbers aren't something we're born to work with it's a very abstract way of thinking but words and language is something that we have an innate skill to to work with and therefore kind of translating insights into text is a huge area and this is something that we we've been uh exploring the interesting thing is kind of how to inject because spreadsheets themselves have very little semantic context you know they have like their individual cells they do have some relations between them there are some labels the labels can be uh can be put pretty much anywhere how do you teach uh generative AI to read the right level of semantics into that and be able to understand kind of you know that this is actually the Total Line and uh you know this is how the revenue was uh kind of the the components of the of the revenue number and things like that this is going to be an interesting area to to keep exploring that's really fascinating I like your example about the sort of the trading sort of newsletter where it's like actually having just a really short text summary was more useful than just vast amounts of data to a lot of people I suppose if you think about it well you know if you're trading stuff you already got a choice of like buy stuff hold stuff sell stuff then so getting closer to that is like is is actually pretty useful um so uh you mentioned that you're you're sort of quite an advanced spreadsheet usually yourself and I'm wondering um are the uses for AI different if you are an advanced user compared to if it's a very casual spreadsheet user or a beginner so in in what we have implemented uh I think that the highest the biggest value comes to the novice users the user that kind of has maybe always been afraid to even get started because they you know they don't even know where to where to begin uh so that's on the on the kind of formula assistant uh assistant side I however think that uh more broadly speaking you know generative AI will be an amplifier to pretty much every knowledge workers uh job so the more time you spend doing something the more time you spend in spreadsheets today uh the more value you will get out of generative AI once we learn how to properly uh apply it because there's just a larger number to to multiply so I think that you know that's where we will see the the most impactful uh Solutions in this space Comet to help people that you know it is to help the people that live and breathe spreadsheets uh day in day out already uh to you know maybe five or ten times more uh in you know in in every productive hour that they they get and what they can do today uh but at the same time our like we don't see ourselves as the the AIS brexit company we are just looking at AI as one of the tools that we can bring to make working with numbers less intimidating to the everyday knowledge worker especially kind of the the the young professional that is getting started in uh in their career and isn't already kind of an advanced spreadsheet user so uh you know it's not AI isn't Central to what we do it's uh you know one of the tools and you know now a very interesting new tool but we can take a look at and say how can we use this to help our user base and that's actually how I think most of the software industry should be thinking about AI like you are already you already have valuable software in a given space where you are a domain expert how can you apply AI in that space and you know to the the software the great software that's all uh already delivering value to your target audience rather than rethinking entirely how can AI make this radically different that will be the the role of uh startups that will be big in 10 years uh and you know uh yes you you may want to kind of keep an eye on it but your immediate opportunity as to how can I bring this into what we already have and make that better that seems a really good advice I'm assuming that's something we've been thinking about a lot at data Camp um is like we're not going to Pivot to becoming an AI company but sort of where can we build AI uh into datacab just to help people learn faster all right so um you mentioned there is not the only thing you've been working on and one thing I'd like to talk about is Integrations so you mentioned airtable before in the air table sort of big thing was it's a spreadsheet but it also helps you work alongside data into in a database uh and of course spreadsheets are only going to be like one tool of many if you're working with data so how does grid think about um integrating with other software so we are we are very uh we try to understand the tool stack of our uh target audience really well head table is one of the tools we see there are you know in this category of companies started in the last five maybe after 10 years there are and maybe especially kind of you know the tech companies and and companies that kind of on the Innovative side of the spectrum uh there are there are companies that have built almost their entire I.T infrastructure on Earth table you know we talked about CRM before they had their CRM and and airtable they may have some of their building and air table they may have some of the financials inevitable and so on so it's a really kind of for the companies that really embrace it it's this really big and important thing and yes uh airtable has used you know the positioning they took was they used you know get rid of the spreadsheet and things like that but they were really just talking about the database side of using spreadsheets meaning when people are using the the fact that you have this two-dimensional uh grid uh to type things into uh to us kind of a way to store contacts or other kind of tabular popular data uh like I said before our kind of our whole Spiel is to kind of be there for people when they are on the number side of things so the way we think about Integrations in that case is you know for people that are inevitable they will probably also want to do uh projections they will also want to do calculations they will also want to visualize the data and Report out on it in a uh in a kind of in a like I said before a guided narrative in kind of an approachable way so uh great is a fantastic tool to lay it on top of Earth table having your data in there creating charts and uh and narratives and grid and the reporting out on what you have inevitable and similarly uh you know notion uh which has been pushing their databases quite a lot and been super successful on the wiki long form document side of of things for for this uh for this demographic uh you know there like they don't have anything in terms of data visualizations let alone interactivity and calculations so that's kind of where where we come in and we try to plug that uh as well as we can so that data can flee flow freely between you know well if you're you know what we often see is kind of the tool stuck maybe you have your most advanced spreadsheets maybe in Google Sheets that can flow in through through grid and straight into your into your notion wiki page some of the data is in uh in an ocean database that can be combined on the same dashboard and then maybe some data and airtable flows nicely in that but it can also flow into mirror or into kind of one of the more visual uh Thinking Tools that you're working with and all of this is is really a breeze using grid but really cumbersome if you're using Google Sheets let alone Excel certainly I'd agree that with Excel and Google Sheets trying to get them to interact with other bits of software it just take a little bit of effort to get set up so it's nice something you're thinking about um one of the uh integration I'd like to talk about is with things like python uh um even SQL I mean you mentioned databases but um as a sort of data scientist my sort of tool of choice is going to be like python or R so uh how do those integrate with grid I have a lot of opinions but but our main target audience is kind of somebody that is not quite that technical so there was probably a runaway screaming if they see something that looks like code so that's not kind of our our sweet spot however obviously being able to kind of take uh you know a python uh function and making that available inside of a spreadsheet so that you can do calculations on the data that you have in a spreadsheet using an advanced function uh coming from from something else is uh is interesting and is kind of uh really valuable there are uh there are others that are kind of taking that on much more directly where we will probably kind of end up in in this hierarchy is we uh despite by making uh API apis available so that you can do these calls both ways and you can both write the grid and you can also call out to external systems from grid is probably kind of how we will enable this because again the the technical sophistication of the people that are writing the python code is probably they're going to be you know fine and kind of probably even prefer having kind of a restful API that they can interact with whether that is actually using uh great to call out to a function they've written in python or having python reach out to uh you know logic that has been written in a spreadsheet and I'll kind of drive that example home with an example uh you know we've seen we've seen quite a lot of people create pricing calculators using uh using grid so you know you have you know there's no doubt that the marketing department or kind of the product organization in inside of uh inside of a company will have a spreadsheet with the pricing plan somewhere and then they realize you know it may be a little bit complicated so we want to get it out on our web page and up until you know great the way to do that is you hire the web agency the web agency came in they rewrote the uh entire logic from your spreadsheet and then they would uh you know they would put up a calculator that customers could use on the uh on the website and that was that and then there was a change to the pricing and you would have to go back to the web Agency for them to kind of re- do the logic that was already redone in the in the spreadsheet uh with grid you know as soon as you have made the change in the spreadsheet and you have saved path to the right place then that is reflected in uh in the calculator that you've already built and if you want to do something more advanced so for example if you are a web department wants to plug into that or build kind of a custom UI on top of it or something like that you would be able to use an API to still use the logic that you know the the product of the marketing organization was well suited to put kind of into that spreadsheet but they would never be kind of consider themselves coders or be able to write that uh piece of code that would kind of come to the same results so that's kind of I hope that helps to kind of understand how we Bridge the you know here we have kind of this business site that is very well versed in their spreadsheet and that's how they work and then you have the more technical side that wants to work in code but you can bridge between the two worlds uh using something like grid okay that seems pretty useful uh so in that case what's the sort of middle case where you have business analysts who are working with power bi Tableau click all these sort of um bi tools uh how do they uh work with grid and as as well so there's definitely an overlap between what you can do in Grid and what you can do in these other tools uh the main thing and we are not here to kind of replace you know Pablo or power bi or click uh however we are here to enable an audience that up until now has not been able to kind of take the time it takes to learn these tools to do some of the same things not necessarily quite as sophisticated but kind of do things that are more akin to something that only people that knew these tools would have been doing before the other big distinction I'll make is that bi tools are about analyzing records and databases essentially records of things that have happened in the past so a bi you know if you if you want to be you want to be quick about it bi as a way to filter Source Aggregate and and limit kind of uh results that give you views on the records of things that have happened in the past but if a business is dreaming about the future it would be doing so in a model in a spreadsheet model so businesses analyzed it passed in bi with a dream about the future in spreadsheets one maybe uh criticism of spreadsheets is that uh sometimes it has problems uh particularly there was like a case of periods back where um the genetics the genetics Community had to renamed some genes because Excel just kept like changing the name to a date I think it was like the March one gene or something uh and so I think a lot of people might well AI is cool but I just want to have a spreadsheet that doesn't corrupt my data so how do you think about data quality and data Integrity yeah no so I I agree with I mean all of these credit systems are they're all correct and they come as a side effect of you know these tools trying to be uh trying to be very uh open and flexible to kind of different types of data entry and things like that maybe kind of in some cases like in the case of like a uh yeah I think it was like March one or and step nine were kind of the two that were often getting confused with with the gene names uh you know maybe it was being too lenient so maybe you can kind of you can you maybe you can have like targeted criticism about exactly what it did in those cases but more broadly speaking I think we often forget to uh to kind of uh talk about the flip side of it which is uh how much spreadsheets enable and Empower business users to do that they would otherwise not be able to do and the way to think about that in in my uh in kind of the way I'd encourage people to think about that is the reason people turn to spreadsheets so much uh is that uh you know you have you're faced with a new thing you're faced with like we're talking about the database uh thing before like maybe you have there are a hundred customers you have to call like for some reason so some service broke and you have to call 100 customers up or or reach out to them so you need that the names maybe a little bit of details about the incident that happened times you know phone numbers contact information those types of things and you have two choices you can either uh ask it to have a meeting where they can filter this view out of your CRM and maybe add some fields in the database where you can check if you've gotten a hold of them or not and and so on and it may be willing kind of if you have a priority project we may be willing to meet with you next week and then you know they will start the project and then four weeks later they will be able to kind of give you what you want so your alternative is I can do that I can go kind of the the official route and five weeks later be able to kind of start my job or I can fire up a blank uh spreadsheet maybe pull down the contact information from the CRM and just you know do it in a spreadsheet and I can do that you know before noon I can start calling them in the afternoon so it's obvious where the choice comes so when it comes to you know we should be careful of spreadsheet and we should know about the limitations but we should also not underestimate the empowerment that they are to perform kind of everyday business workers to take care of a lot of their everyday everyday I.T needs where they themselves are able to solve for something that otherwise they would need much more technical help to do okay yeah so um there is a gonna be a trade-off between um a spreadsheet being helpful for you and trying to like you know fix your data and giving you that extra productivity but occasionally it's going to do something wrong so you've got to be careful about like checking the results yeah so okay I I guess we would say the same of like our our uh our kind of um I.T systems I mean they sometimes have errors and those errors can uh can have uh big problems we are just more much more like in software development we tend to be or at least we we want to be much more disciplined when it comes to testing and uh uh and you know automated tests then and quality assurance but um you know uh things things still happen as We Know absolutely um all right so uh plotting is maybe the second area where traditionally um spreadsheets have been a little bit poor like just trying to do a histogram or a heat map which may be like not the most popular kind of plots but they're they're still fairly mainstream very difficult to do in Excel or Google Sheets so what's grid doing around improving visualization so we we have we have a bunch of visualization options and we are trying to the our approach is we want to you know make sure that the the basics are super easy so that you you know just put a lot of work into tuning Our you know uh column charts line charts and tables like these are these are if you take these three visualizations together you can portray pretty much anything sometimes you want to reach outside of of that range to to kind of you know to bring a particular Point home uh for example to heat much or or dock plots or something like that so you know we've we've been implementing those as well at the same time like here is uh here like the the way I see this moving forward is there are we we can probably never fulfill everybody's visualization needs with something that we build into the product so here is where kind of at some point like those more technically technically capable uh should have access to apis where if you want to go outside of what the tool offers out of the box you would be able to enable that and maybe you would be able to build that in a way that not only you can use it but you can make that available to other users of the tool as well so essentially an expansion type model there but uh but this is this is something we we think nearly about and kind of given our target audience also uh you know it is important there's sometimes a tendency especially when people are getting started with visualizations and so on that they they want to move on to something that is you know non-traditional when maybe a column chart is the best way to for them to actually portray the point they want to get across so we also want to kind of don't want to limit them and what they can do but we want to guide them to you know knowing when to use something other than just some of the basics because they are often the the right choice it does amaze me how far you can get with business analysis just by doing wine charts and bar plots um but occasionally yeah you do these other other plot types so it's uh it's like this long tail of different uh visualizations you need to use so that sort of um extension model does seem quite reasonable um now the third um area where I think spreadsheet struggle is with debugging so I think everyone's coming across the case where there's like there's a weird error somewhere and they end up clicking through cells to try and find out exactly which formula went wrong somewhere um so how do you think about improving the debugging experience for spreadsheets so this is a this is a fascinating area so um I'll I'll take a dive so you know the behind me behind every spreadsheet is a uh dependency graph and you will be surprised how complex that dependency graph can become very quickly meaning you know you make a cell I I made an example before where kind of you type a number and cell A1 and B1 and then C1 you add them up like that dependency tree is only one level deep but then you know as soon as you have like maybe you have a financial model with 10 assumptions and you're calculating that for you know monthly for five years or something like that you will you know by now you will have a couple of thousand nodes and the number of links between those nodes will be in the tens of thousands and the depth of the three will probably be you know or the depth of the of the graph will probably be I don't know 25 30 levels deep easily so it's uh it's kind of obvious that it's easy to get lost in that somewhere and it's also kind of obvious that it may be hard to trace exactly where in all those kind of dependencies going up 25 levels to to hundreds of cells uh to come to a conclusion in a single cell can be can be hard so we have one of the Privileges of uh the job I have is that we had to build our own spreadsheet engine from scratch so we are by far the most powerful spreadsheet engine that can run entirely in JavaScript uh and in there by kind of in your browser that was needed to be able to kind of make fast interactions uh happen with uh with large spreadsheet models uh in in a browser so therefore we had to kind of take a deep dive here and there are we have only kind of just begun to scratch the surface of making this available to our users but the tools we have internally to kind of debug just as we are developing the spreadsheet engine are fascinating so when you kind of you're able to see the intermed immediate results and kind of how they flow and exactly where so for example if you have an address to be able to trace from the cell where the error manifests itself to where it actually first started propagating which is something that you know Excel or Google Sheets do nothing to help you help you do you will have to just realize which one of all these cells that are now throwing an error are at the root of the dependencies for for what you're looking for and I think there are a lot of opportunities to do more there and uh again we have to kind of be mindful of what's useful to our target audience that aren't necessarily the most sophisticated ones but I've seen kind of a I've seen a major opportunity also in just applying that to a much more advanced audience where you can we can kind of throw at them analysis of their of their spreadsheet and kind of maybe also point out non-obvious errors like omissions in uh in cell ranges and things like that that happen all the time uh where you know you've added up all but the you know last two months of something and therefore you had the wrong sum somewhere Excel tries to help you in Google Sheets as well but if you aren't like visually looking at the right place in the model uh there will be no uh there will be no cue for you to look at so so yeah so it's it's an absolutely fascinating area and the the dependency graph is uh especially when you think of a kind of dependency dependency graphs come obviously come up in all sorts of uh computer science Solutions but the kind of a calculation dependency graph like uh spreadsheets is is a super fascinating area both two kind of try to optimize you know there are so many places where you can optimize for Speed and uh and memory and and all sorts of things but also just in the way that it manifests essentially a large algorithm that you what you have in a dependency graph is an algorithm you could write traditional code that would come to the same conclusion now good luck debugging that so so that's kind of uh but you know you have these business users that are creating these complex algorithms just by uh essentially offloading their thinking cell by cell or line by line row by row into a spreadsheet model I find it fascinating because we normally talk about dependency graphs in the context of data engineering and scheduling like when your different analyzes are going to run and the fact that actually um the spreadsheet uh like the engine is sort of using the same graphs uh to run the calculations and this can be helpful for debugging that that's a really interesting sort of coincidence for for those for those that are kind of interested in those types of things in the audience I think they'll be fascinating to know that dependency graphs were not there in the very first spreadsheets so the way they would calculate is they would just first calculate cell A1 and then B1 and C1 and then it would go row by row so you could only do calculations that would refer up and to the right up and to the left and if the calculation was referring uh either down or to the right you'd have to re-run the model a few times before you got a persistent result wow that's pretty inefficient uh yeah so I guess I'm glad we we have graph uh based engines now right all right so um we talk a lot about data literacy on this podcast and so um how do you think spreadsheets can be used to help uh novices get started with data I would go as far as saying spreadsheets are probably where novices start with data uh so I mean it's probably the First Data tool most of us are at least first freeform data to alert like free uh pre-expiration data exploration tool is maybe kind of the way to put it that we come across uh I actually I have been surprised as I've taken a dive into this how but the first time user experience is with spreadsheets they have been able to rely on a lot of uh ingrained knowledge inside of businesses and universities and and everywhere else but when people are starting to use spreadsheets they can turn to something somebody that already knows how to use them that's how most people you know that's how most people get a big chunk of their initial learning there so I think that uh you know just first time user experience in general and maybe as I alluded to before being better about kind of best practices teaching people best practices while they are doing things for the first time like okay you want the pie chart you know that can be good but you know here is when a pie chart is a good solution for you and here are some of the reasons you know you might not uh want to use them and then oh you know I I learned something I should be using a different type of visualization to get my point across whereas kind of today we just throw people in and they we have there's no guidance neither on properly how to use the functions of the tools nor of you know what good data analysis and and presentation of data results looks like yeah I I do agree that uh spreadsheets had like a really good sort of starting point for um working Daytona and so it just seem like some level of spreadsheet competency is pretty important in almost every data role but do you have a sense of like what the most important spreadsheet skills are like Jesus needs to be really good at formulas or figuring out macros or what's the deal it obviously it depends depends a bit on your role one of the interesting things about uh Myspace and maybe kind of in some ways in talking to you know your audience is that the people who are the least likely to rely on spreadsheets in their work are techies because they have we have other tools at our disposal to do the things that normal people have to have to do in spreadsheets so we we are a little bit blind to uh often how much they just drive they run the world like you know the whole business side of our organizations are driven by spreadsheets the decision making many of the processes like a lot of things are just driven off of a spreadsheets that we've never seen and we are largely unaware that they even exist so I think that um I I'm very much kind of the numbers side of things so I think that kind of the yes getting the the basic uh the basic kind of formula skills right uh is a great way to uh it is a very important uh way to start and the funny thing there is kind of you can master uh I'll I'll give you a a a statistic so the top 30 spreadsheet functions meaning the most the 30 most used functions in spreadsheet they actually cover more than 98 all spreadsheet in the world so only two percent of spreadsheets use functions that are not one of these kind of 30 most used ones so kind of Master the master the the the most uh commonly used ones and you are going to be you know well well ahead of a lot of your your colleagues I think also um you know after that after kind of having gotten enough skill to get the job done meaning to get your thinking out and doing the analysis or uh or um you're getting to kind of uh the the results that you were looking for then I think the the skill after that is how do I communicate this like how do I properly tell the story what is the data telling me and how can how should I uh present that to someone so it makes an impact uh and that is definitely something that spreadsheets don't help you with that is something that you know some somebody like us uh that's our kind of bread and butter helping you with the narrative and the presentation and that is kind of I think the skill that comes after like first you have to first you need to learn how to work with data and think and maybe kind of maybe the part that I overlooked is you know the amount of data cleansing and uh and uh manipulation you often have to do before you can start your your actual work so kind of you know learning some tips and tricks there is definitely useful but then on the other side of that if you're not showing this to someone it's like it's worthless it's just in your head and usually like I said 88 of the time people find themselves presenting what they have pulled together in respected to someone else and that is an important skill to have that's uh kind of interesting the idea that actually I think he said there's only like 30 commonly used functions or something so and now think about it yeah you probably can get a long way with just being able to do like summon average and then maybe the occasional if statement so yeah actually the hardest bit is being able to communicate what your results are to other people um yeah yeah I I can certainly agree with that um all right so um I know talking about the future is a bit of a mugs game but I would like your opinions on what you think the long-term future is uh for their spreadsheets I think spreadsheets in like the spreadsheet the way we think about them when I say the word right now are probably going to be around for a long time you know I'm I'm willing to I'm willing to wager at bet for 20 years and I wouldn't be surprised if if it's a lot longer uh the reason for that uh is you know there are several reasons for that first of all they are a pretty well proven way of doing uh a lot of things like they're very generic open-ended tools and while ever since kind of the physical case people have been kind of chipping off you know major use cases and making proprietary or purpose-built software to uh to better do something that people have been doing in spreadsheets new um needs arise every single day as well and people who turn to spreadsheets to to solve them so uh and that is that is going to be like spreadsheet user usage hasn't gone down uh uh you know with more and more proprietary and software being built for some of these uses it's actually gone up and the reason is for everything you chop off there's just more added to the long tail uh that kind of needs to be solved as well the other is that just so many processes uh so much knowledge so many assets that already rely on things within businesses and I think we especially us on the kind of I I imagine a lot of people listening here on are very much on the early adopters end of the curve I think we tend to underestimate how sticky things can that work can be you know I've seen spreadsheets that have been updated weekly for 20 years and I'm not joking like there are there's a role added to a spreadsheet every week and that spreadsheet started 20 years ago so these types of things happen and they happen because it works and it's what the business user has or the disposal and you know there's no reason to change it if it works well the the 20th spreadsheet I mean I guess having long-term compatibility is amazing it also seems like slightly terrifying that that thing exists you know and and the interesting thing here is that nothing interesting has happened in this space without being backwards compatible with what came before it some of the decisions made by Dan Brecklin who I'm referred to before before the maker of physical and his dorm room in Harvard in uh you know 1978 are still the way we write formulas and spreadsheet today because uh Lotus one two three had to be backwards compatible with vertical Excel had to be backwards compatible with lotus one two three Google Sheets was backwards compatible with Excel from day one and even though each and every one of us uh you know are acting on some new functionality whatever Paradigm comes next will have to be backwards compatible with what we have today do you have any final advice for spreadsheet users yeah I mean obviously I'd tell them to go and try out grid it will add to your to your life uh it will help you uh better kind of present the the uh the things that you have uh pulled together but more generally speaking I think that you know maybe um maybe kind of having a conversation with you know somebody that works in creating software because what what spreadsheet users often don't realize is that they are writing software they are you know spreadsheets are code they're just encoding relationships between data that lives in cells instead of writing kind of lines of code that get executed one after another uh but we haven't like the spreadsheet world hasn't learned has a lot to learn from some of the discipline and even just very simple things like having a check some somewhere like somewhere where you know you know that if everything works the result in this cell should be you know a certain number having those kind of checks in place even though it kind of isn't anything more than that will often kind of save you a lot of pain somewhere so yeah learning from you know have a have a peer conversation with uh with a computer scientist and see what you can learn from each other that's brilliant I love the idea of spreadsheets as being like a stealth way to teach people programming uh fantastic okay all right uh with that uh thank you for being on the show uh I hope you enjoyed the experience this was uh great fun thank you Richie foreign\n"