The Importance of Data Literacy in Small Businesses

One key takeaway from our conversation with Kendra is that data usage is often underestimated in small businesses. While it's easy to think that only large corporations need data expertise, the reality is that even small businesses rely heavily on data to inform their decisions. In fact, many small business owners are beginning to recognize the importance of hiring experts to handle their data needs, effectively creating a "fractional Chief Data Officer" and "Chief Security Officer".

This concept may seem daunting for some small business owners, but it's actually becoming more accessible with the rise of subscription-based cloud platform providers. By paying a monthly fee, businesses can tap into expertise they might not otherwise have, without having to hire full-time employees. This model is particularly appealing to small business owners who are already stretched thin with multiple responsibilities.

Another area where data literacy is critical is in logistics and supply chain management. With the increasing use of e-commerce platforms, there's a growing need for businesses to be able to handle large amounts of data related to package tracking, inventory management, and customer behavior. However, not all small business owners have the technical expertise to handle this type of data, making it essential to invest in software solutions that can help streamline operations.

In our conversation with Kendra, we touched on her passion for data literacy and its growing importance in the modern workplace. As technology continues to advance at an incredible pace, being able to work effectively with data will become increasingly valuable. According to Kendra, she's excited about the prospect of helping people build their confidence in working with data, particularly as it relates to using tools like large language models.

One area where Kendra sees significant potential for growth is in reinvigorating people's thirst for learning and exploration. With the rise of AI and machine learning, there will be an increasing need for workers to stay up-to-date on the latest developments and best practices. By investing time and effort into developing data literacy skills, individuals can position themselves for long-term career success and economic productivity.

Kendra also highlights the importance of recognizing that data expertise is not solely the domain of large corporations or tech companies. Instead, it's an essential skillset that can be developed by anyone, regardless of their background or experience level. By providing access to online resources, training programs, and community support, individuals can build confidence in working with data and unlock new opportunities for growth.

For Kendra, this is a particularly exciting time because she sees the potential for data literacy to transform millions of people's lives. By harnessing the power of technology and developing essential skills, individuals can become more economically productive, confident, and prepared for an uncertain future. Ultimately, Kendra believes that data literacy has the potential to level the playing field and create a more inclusive and equitable society.

In conclusion, our conversation with Kendra underscores the importance of data literacy in small businesses and beyond. As technology continues to advance at breakneck speed, being able to work effectively with data will become increasingly valuable. By investing time and effort into developing data literacy skills, individuals can position themselves for long-term career success, economic productivity, and a more fulfilling life. With the rise of subscription-based cloud platform providers, online resources, and community support, there's never been a better time to start learning about data – and unlocking its potential.

"WEBVTTKind: captionsLanguage: enI think that it is true now and it will only become more true over the next 50 years that being comfortable and confident with data with what it means with how we treat it well being able to spot when someone is lying with Statistics being able to understand how to use statistics to understand more about it is only going to become a more important part of the working life of every person listening to this podcast hi Kendra thanks for joining us on the show today oh it is a real pleasure to be here we spend a lot of time on the show talking about Enterprise data and that's all quite excited to hear about the opposite to talk about what goes on in small businesses so I guess to begin with uh can you tell me what are the main use cases of data in small businesses oh my goodness it isn't a wide-ranging question to get started with um so zeros sort of original premise is is to be the backbone of the back office small business so we offer the general ledger in the cloud so effectively it doesn't matter what kind of small business you're running you in almost every jurisdiction you need to pay tax and hopefully you'll be profitable and so to do that you need to understand fairly intimately the finance that runs through your business so that the small business data that we are interested in Passionate in obsessed with I would say is effectively that the lifeblood of the school business the cash flow that runs through it the payroll the inventory the the financing all of the things that perhaps you didn't go into small business to do but if you don't do it well you won't stay in business for very long okay so it seems like the place to get started running business really is worrying about what's the the financial data what's happening with that making sure that you are sort of doing your payroll your taxes correctly it's sort of one of those things that you want to spend as little time on as possible but as much time as necessary because it's not why you went into business unless you happen to be an accountant or a bookkeeper but it is really really important to make sure your business runs well and probably a little different from country to country but where I am today recording in Australia 90 of businesses in Australia are small businesses so it is an enormous part of every economy I hadn't realized it was it was so important that I suppose yeah really think about it there are an awful lot of small businesses around um and I like the idea that um it's uh something you want to spend sort of just enough time on because uh sometimes you get over excited about data here we're like oh yeah everyone should do more more things a day to but often if you're a small business owner maybe um it's not where you intended to be spending your time but uh we'll get into that in maybe a more delays to tell in a moment but um first of all have you seen any success stories from small businesses making better use of data so I one reason I love working at xero is I love the fact that many people I run into industry are users of our software so I can continually say that people say how weird you work and I say I work at xero and your hairdresser your plumber your little coffee shop they genuinely say oh I love Sarah and the rest the reason is kind of what we were just touching on I love zero because it makes my life easy so I would say there's a general High tone of I like it because it reduces the time I need to spend on those things if you then dig deeper into success stories for me probably if I think about some of the conversations I've had some of the perhaps slightly larger small businesses if that makes sense who have been running for a little while so now the perhaps they have a couple of years worth of inventory or a few years worth of repeat orders they actually find even the ones who perhaps aren't data Savvy by Nature when you sit down with them and say well do you know the wealth of information that now sits and the records that you've been keeping with xero um they actually have gone through and discovered things like order time lags or customers who order in a seasonal pattern and then have been actually able to reshape their their ordering or their Staffing to meet that demand so yeah when people are perhaps given a little bit of a nudge for the folk whose businesses aren't data oriented but you give them a little bit of a nudge and you say think about what actually now sits in the records that you have usually what you hear people say is I can be more efficient I can serve my customers better or I can save money all of which are wonderful things if you're a small business owner absolutely I love the idea that just being able to surface things like seasonality or order quantities can make a huge difference to someone's livelihood and it's the thing right we think about it the big businesses particularly I'm sure many of the folk listen to this podcast who are data practitioners and they think about this all the time and many of them will work in large businesses optimize millions of customers now we have millions of customers ourselves at zero but our customers our small businesses they don't tend to but they can take those ideas of looking for patterns and enormous amounts of data and look for patterns in their smaller amounts of data and it's still really really valuable absolutely and some of the sort of strikes me um if you've got one or two business owners who are doing everything then you're not going to have the resource to have a data specialist to help you look at all this stuff so how can you make effective use of data when you have this limit to your resources it's a really good question and I think we would try to answer that in two ways one is to encourage people that when they use a product such as xero their data is actually quite tidy and quite neat and many people listen to this podcast and be very aware that the large amount of time spent for a data practitioner is needing up your data so for folk who are using a cloud software provider for doing their accounting actually a lot of that uniqueness has occurred so that you know they um if you're using multiple Banks you'll have pulled it into a single Bank etc etc the other side of it is we are always as a company striving to make the this simple for our customers so we build products that do that and deliver them through xero so for me for my machine learning team my AI products team we have two mantras that we build towards one remove toil use the data and the patterns from the data to make small businesses life easy and two Delight with Insight if we can pull patterns that say hey Richard you seem to come in every Thursday at eight o'clock in the evening and these are things you do so we're going to queue them up for you and suggest to you that this time we've already taken care of is when we have a suggestion for and this one oh this supplier plays late so we suggest that you go and lunch that supplier so you can make payroll next week that's going to make your life easier so that would be I'd say the two sides of it one the data is tidy for those human beings who would like to delve into it to find their seasonality patterns and their big customers and two all good software providers should be working on that data to pre-provide the value that you can get from it so uh that first idea around making sure your date is tidy it's one of those things that sort of easier said than done so do you have any tips for how you can go about making your data tidier or easier to analyze as a small business owner put your attention is Paramount if you would like to be able to derive value from anything including data you need to pay attention to it when you are generating it so if you are a small business owner saying I'm sure there'd be something in there you sort of need to begin with the end in mind if we go for a you know a well-known phrase what I mean by that is you need to label it correctly you need to categorize it consistently you need to as you go through your general ledger categorization be consistent in the saying this is office supplies all this and that sounds boring and it sounds mundane but it's actually as you know everyone listing here will know it's the Bedrock of being able to do anything useful because what are you trying to do when you look at data you're either probably trying to eyeball it yourself for patterns can't find patterns if you haven't added them or you're trying to feed the data to the machine and as we all know if you machines are really really good at picking up whatever is actually there and if what is there is noise they will pick up the noise so I would suggest that paying attention to making sure that you are generating the data and the labels around the data I.E the categories and the annotations that you put in a consistent fashion will pay dividends in allowing you to import information out of that data I like the idea that I'm just doing really simple things like categorizing your data consistently is going to pay is going to pay off in the future so something that might seem boring is really going to benefit your business now I think as you mentioned a lot of people when they go into business they don't necessarily care about data that might be a bit hesitant about using data so if I'm a plumber or a cook or something then I'm not necessarily going to think oh data is something I should be spending my time on so what data skills do small business owners need first one everyone needs is just a little bit more confidence um and you can get that by sitting down and working with your bookkeeper so I think accounting is a really interesting space because some of our primary users are actually folks who are really number seven accountants and bookkeepers are actually really numerically literate number Savvy people now they might have some concerns around the technology side of things but if they they are really good at dealing with data because they have done it all their lives so one thing I'd say to small business owners is that advisor you have that bookkeeper that you work with that accountant who looks after your taxes at the end of the year if you approach it with curiosity they're actually a fantastic resource to helping you become more comfortable with data and um they're probably be quite delighted if you ask them because you know when you do poor coding on the general ledger side of your input they're the ones who sort that out and make sure that actually a tax time everything flows through really smoothly so that would be one suggestion would be lean on the business partners that you have today and then the other one would would be to put down your preconceptions about the fact that it is difficult or the fact that you need specific skill to do it and there are lots of great online resources if you want to read about it but essentially yeah I'd approach it with a child's mind and say I believe I can learn about this information and and start from there with one one back there for me is I think our education systems universally across the world kind of turn people off doing quantitative things we don't unfortunately teach math particularly well we teach statistics if possible even worse and people tend to leave formal education with a misconception about the fact that it is a Part B complicated and c not for them and if you can put down a b and c and start again and say well hang on every time everything I read in the paper says the machines are taking over the world that data literacy is going to become more important how about I give it another crack and try again with my newly enhanced Googling or chat TPT skills um give it another go would actually be my biggest recommendation that's fantastic because it is so easy to say oh this isn't for me this is a hard thing and give up before you even uh before you even tried anything I don't like the idea that you just gotta give it a go and see um so trying to be uh maybe more more concrete about this I mean so we talk a lot about um the idea of data-driven decision making and as a small business owner you have to make a lot of decisions yourself so how can you bring data into that process of making decisions about your business so I kind of I can't let me give you two examples um which you certainly could do yourself or if you are a user of xero you can make use of um the products that we offer so one of them is forecasting your cash flow so a very very very common reason that small businesses go out of business is because of cash flow problems and I don't know what it's like in every jurisdiction that we operate in but certainly in Australia we have challenges with big businesses paying small businesses slowly so it's really common to sit on a float and be like oh you know what I'll just paid my invoices a little late I'll keep that money in the bank and I'll use that as a flight to run my own business and Beekman says engage in that practice unfortunately so cash flow I or the lack thereof people not paying invoices on time is a huge reason that small businesses go out of business or can't make payroll so what what is the first thing that you can do to assist a business with that apart from trying to influence government policy to make big businesses pay on time what you can do is give people information about payments so we have built and continue to extend and work out a cash flow forecasting app which looks at the sequence of payments into your accounts over the last 30 60 90 days and forecasts forward what your level of cash flow intend to be now I know that people can and do do this themselves I know that because I was at a cocktail party on a frigate true story and was talking about the fact that I worked with xero and one of the gentlemen there who was a port designer say to me ah short-term cash flow forecasting he said I used to do that myself in a spreadsheet and now I use your app which I was delighted but so you can do it yourself but what it effectively says is in 30 60 in 90 days given the pattern of transactions and the pattern of payment coming into your account this is the cash flow balance we expect to see in your account and that's transformative because it allows you to say I can't make payroll unless I dig in and understand that one supplier who has a habit of paying 14 days beyond the due date has on time okay that's an action that I can take I can ring that supplier and say mate I need you to pay me on time I don't set my payment terms you know for amusement value I set my payment terms so that I can make cash flow and payroll and pay my themes so cash flow forecasting is one great way to use data to inform how you run your business um another one that I know is just so valuable to the small business economy so again I'm going to you know sort of talk through it is at the other end when we are pulling information out of everyone's bank accounts and into the general ledger there is an incredibly tedious process that all bookkeepers and small business owners need to do which is called coding your transactions to the general ledger and that's where we're talking about before of providing high quality data it's saying ah that oh yeah that was when I took client X out for the coffee oh oh yeah that's when I had to make the emergency run because I'd actually run out of envelopes and I went into the officeworks and purchased some things and putting those against the correct um categories now again that's the place where you as a human if you are tidy and organized and consistent in your coding can speed yourself up but it's also where machines can do a great job because that's where you can Source the wisdom of crafts you as a small business owner intimately understand your own purchasing habits we as a SAS software provider don't but we do have the benefit of millions of customers transaction habits and hundreds of thousands of bookkeepers categorization habits so we can and have and it is now available in our software create machine learning driven predictions of that category that just that's right that transaction line that just flowed through from your bank account we believe it belongs here would you like to accept that yes in an amazing toil reduction for small business owners because it is a lot quicker to review what a machine has suggested to you you might want to accept accept it 90 of the time and go oh silly machine you got it wrong 10 of the time then to actually have to access your own memory every single transaction and click all the buttons that allow you to category eyes so those would be two places I think you can use data to speed up your day-to-day so you mentioned that at xero you have millions of small businesses and you can see patterns across the data that an individual small business couldn't see can you give me an example of some of these patterns that appear yeah this is actually another really really interesting one um folks were just in raptures so we have a product um in a number of a number of the company countries we work in called Hub Doc and hubdoc allows people to upload their financial documents and to have those financial documents automatically processed and added to their accounting software and we have for a number of years had a machine learning driven pathway so that when you upload your financial document be that a bill an invoice uh it's goes through OCR optical character recognition that comes out as an electronic version of itself and we then go go through and pick out the key Fields so we can pick out what currency is that in what date was it who was the merchant and what is the um the invoice total for instance let's say now one of the most annoying things and I'm not an accountant so people will have to forgive me if I get this slightly wrong but I'm fairly sure I'm correct is when what you think is an invoice comes through but it is actually a credit note so rather than somebody charging you money they're actually giving you money back because you've overpaid a previous inverse or something like that now as you can imagine if you have a document come through and you code it as an invoice when it is actually credit note in your back end you actually end up with a double up problem because it was money that was supposed to go on one study alleged and goes up on the other so say it was 25 Grand you'll actually get a fifty thousand dollar offset of incorrectness and where the money is supposed to be because you took negative 25 and put in a positive 25 effectively you've got a 50. so it is the bug bear of small bits and signers accountants and bookkeepers everywhere when somebody miscodes a credit note because you have to go picking through the reconcile General lecture understanding how on Earth you have a fifty thousand dollar incorrect level in your bank account versus your reconciled Ledger now what we are able to do by looking at millions and millions and millions of financial documents was build something called okay this is you know our great naming here credit note detection but it does exactly what it sounds like it does it's not a simple problem as your listeners will understand because it's anomaly detection and anomaly detection is hard because for every for every credit note there are I'm going to get the slightly wrong at hundreds if not thousands of invoices so the documents look very very similar some people will stamp credit notes across them and that people won't they look very very similar and one percent ish or a fraction of a percentage I actually create a note so it's a hard thing to do well it's also actually a hard thing for humans to pick up because we're really really good at getting into the mode and just going yep click click click click but that is an example of where we can use interactions or millions of people to pick up the subtle patterns that indicate this isn't an inverse its credit note and actually alert humans in the flow so that's something I really like too is actually the way we do it it's very easy for humans to fall into the mode of I'm just clicking a button and we need to be reminded or you probably need to pay a little more attention before you click this button and it's one of my sort of hobby horses is I get frustrated when I hear people think that an AI product is the algorithm it's the sexy part gets uh talked about so the part that gets published it's the part that gives people patents but it's only part of a really functional AI product and when I'm talking to folk about how to build really functional AI products I'm always reminding them that it's a systems problem and that's it's the end-to-end flow including the human and in this case a credit note detection the piece of the of the flow that actually we thought quite hard about which is this is an impactful thing because if we get it wrong it's really annoying and if the human doesn't notice it's really annoying it's in the wrong place so we actually subtly but in a nice in a way that who a human stands out because it is different redesign the interface at the point where we say hey human we're fairly sure that this is in fact not an invoice a credit note but we suggest that you now pause and take a little time to think and to genuinely verify our decision and so that just that subtlety in redesign the interface and making that pop up to the person in a way that is noticeable was a really important part of building a really useful AI product and we roll with credit note detection out gosh time flies so it's probably longer ago than I think it is now several months ago and I kid you not people love it to Pieces it was one of the most requested feat product features and when we rolled it out people were in raptures that we have now an anomaly detection system that allows them to avoid accidentally coding a credit note as an invoice thus fascinating and I love the point that the AI is just a tool and actually the thing you're trying to improve is the customer experience so you really have to think about the user interface and things like that so in like um do you have any advice on how things like the design and product teams can work with AI and sort of understand the nuances here because sometimes um you have you sort of AI and data teams separately you're from the the product teams and maybe um the communication between them can be quite tricky do you have any it seems like you did a lot of wraggling of the these different teams so I'm as curious as to your advice here yeah it's a really good question and I have really strong advice don't don't have separate algorithm and product teams it is insane it adds way too much overhead and you'll end up building things that each side of that equation thinks are good and your customers think I'm not so good if we are polite for their language um an AI product which to my mind 100 is the end-to-end complete customer experience including the human computer interface is no different from any other product you wouldn't arbitrarily split up another product and say you know what you do the button and use this bit and you do that in my lived experience AI products are harder to build they're harder to build because we're not as used to them because they are complex and subtle and because you are hard coding in a way that is almost impossible to really pull apart you are deeply wiring together a flow and the the large amount of data that your algorithm was trained on and it's you know that long time ago Google wrote a paper called the high interest credit card of technical debt machine learning the high interest credit card of technical debt and it's because of that absolutely insoluble tight coupling between the data that your algorithm was trained on and the end-to-end flow that your AI product has they're harder to build they're more expensive to maintain you want to start off with a team setup that is as optimized for that as possible so just don't separate them in my opinion if you want to build something successful the other thing I would say is this is tricky because in my experience AI product Builders are a lot more iterative than other types of product build I've yet to find a team who can sit down at the beginning of a challenge and say yep I can absolutely guarantee for you that with the data available to us today we will be able to build a product that is acceptable to the human users within three months maybe there are teams out there who can do it who are iterating on a product that they have already built but I think it's incredibly unusual so you need to allow for more iteration time what I would say though is perhaps there is not full-time work for a designer throughout that entire process but robot tied the team that thinks they don't need a designer involved right at the beginning of the conversation so get your cross-functional skilled team together at the beginning of the conversation get them to know each other get them to appreciate the other person's skills but don't skip that step don't skip the step it says at the end we need to have an end-to-end usable product that humans don't have an uncanny valley reaction to that doesn't trip them up from their workflow that doesn't provide something that is so subtle that nobody ever noticed had happened they're expensive they're slow to build we sure as heck don't want to get 95 of the way there and then discover that we have an unworkable human human computer interaction so take my advice get those work involved right at the very beginning that seems like great advice to get all the people you need together at the start and I think you mentioned that almost no one will tell you that they can do this sort of thing in one go probably the people who do tell you that they could do and won't go there they're people that you don't working on this sort of uh project I think they're almost certainly focused simply haven't done that before or what I see disconcertingly too much of now and it'll ebb and flow because we're humans and we'll come and you know we get over things um but there has been at least in my head at least twice two waves of this and I think we're in another wave right now is very enthusiastic software engineers who believe that as long as they can call an API they understand how to do machine learning and we've all gotten very excited in the last few months about the amazing accessibility of really competent large language models and oh my goodness the number of people I have heard tell me say to me oh and you know we can just call the API can you now good elections there or the beautiful uh the beautiful Board of Forbes type article that was circulating with all the boards in Australia and I'm sure all the boards in the US as well the cost of software engineering is going to go to zero in the next 10 years is it now sneering is only writing code is it is that right so I would say yeah absolutely folk who who tell you that this is going to be very quick now because all I'm going to need to do is stitch together multiple calls to check GPT using Lane chain have never actually tried to build a functional AI product so avoid them bite the plague or if you really need their skill set Embrace their enthusiasm but make sure that they work in lockstep with folk scientific training who understand how to build experiments and test the outcomes of those experiments and use the interface experts and product managers who really understand what the customer is after because it's very easy to think you are building for the problem that you're trying to solve but actually build to solve a subtly but importantly different one and I'm sure we've got a few Chief Finance officers listening thinking oh yeah cost of software engineering go down to zero that sounds brilliant but it might be uh might be wishful thinking um On a related note so um you said that uh these sort of new generative AI tools the large language models uh that may be not um uh well they're sort of difficult to build products for but are they useful to small businesses I think at the moment what we see is that they are difficult to replace humans with and you have to think really carefully about doing that they certainly seem to be very very attractive for augmenting humans with so I'll just give you a couple of the for instances that I've I've heard from small business owners um one of them is writing boilerplate or what I call breaking the white piece of paper problem who hasn't sat down in front of a proposal they need to write or a letter they need to send and go on ah I'll know it when I see it but how does that go again particularly you know you haven't had coffee on a Monday morning I I know a large number of small business owners who are this their go-to they have it open next to Google I'm sorry I'm talking chat TPT the interface open AIS interface they have it's open next to Google and they use it to generate the first draft of communications and I do stress the first draft if I've got extremely excited about it back in you know back in the before times January and February um and thought that it was going to be uh drag and drop replacement for a lot of the things they did the impression I get talking to folk now is it's like having an intern that you know they'll get it to 90 but you're always going to need to take that extra 10 yourself so where I see small business owners as owners using it is largely in doing desk research if they you know if some folk just really prefer the back and forth that you get from a chat bot than that you get from the search engine and creating first drafts boilerplates break the white sheet of paper for written customer communication now I would say that they are also pretty careful to note now perhaps they weren't four months ago but they are now yeah but you do want to read it before you use it because it will it will get at 90 percent of the weight there perhaps even 95 of the way there but as we're seeing player in the courts now as the human who uses it you're the one that's responsible for it so that would be my just my note of caution to some small business owners is it's still you it's still your business and I would always read very carefully anything that came out of a generative large language model because it's not sentient it does not know what it is doing it cannot give you a confidence level for how confident it is that what it has said is the right answer to your question it is a sequence generating machine and it is generating you as statistically likely sequence to the sequence that you put into it so yeah so since you were mentioning Plumbing businesses earlier than Rob boilerplate no I think yeah it's great for writing boilerplate not good for fixing boilers at the moment certainly true that would be a good Adventure though AI that comes in there Fix You boiler all right so um moving on to uh getting back to sort of uh using data in small businesses are there any important business metrics that you think um are important as a small business oh I am not an so I should put every of amateur opinion it really depends on your business Richie um and this is something that I would simply say having had conversations with many many small business owners um the ones that they all come back to is cash flow incredibly important um cost of goods sold incredibly important um there's a lot of subtleties around payroll and understanding particularly Awards rates so extremely important to understand your your obligations as an employer and that's something that again a lot of small business owners don't go into business to be employers but then as their business thrives and they become really successful they suddenly discover that there are lots of people um so having a really careful understanding of of making sure that you are doing everything that you need to as an employer is probably another place where I'd say paying really close and careful attention to that data is really important okay so it does seem like um a lot of this really is around like uh the finances of things and also around maybe some of the the comply and stuff like uh like tax and regulations and making sure you're doing the right thing there so I think it's I should get the best the best right right so so we I as an extremely difficult area to crack if you think about companies like xero like financial institutions um I've worked in financial institutions for many many years not recently but for many many years and small businesses really really hard anyone who works in a large bank will tell you yes just really hard what is the reason for that the reason is because small businesses are incredibly varied like as much as we will as humans would like to think we're unique we're kind of not like consumer patterns consumer patterns are reasonably easy to tap into and reasonably easy to um fingerprint we spend fairly similarly it is not difficult for a bank that has a significant amount of your banking to figure out quite a lot about your spending habits and to figure out quite a lot about your household composition from the spending habits there are just two things one although there are an enormous number of small businesses there are a lot less small businesses than there are spending households so we have a small data problem and within that somewhat smaller pool of small businesses there is a far greater Dynamic versatility of the types of small businesses that you have so that's why I think that it's it's much it's difficult to say this is the killer app for a specific vertical because there are there are killer applications for data for all the different specific verticals of small business but they are myriad so what's the common thing that all small businesses have in common so that it's easy for you know in a general podcast or a general conversation to zero in on it is the thing that everybody has to do everybody has to make payroll everybody has to pay their taxes everybody has to understand that they have paid their bills that their suppliers are paying their bills so there's a reason I think beyond the fact that I work for an accounting company there's a reason for the fact that we all come back to the lifeblood of small business data being around finances because it is the common thread that all small businesses have to do well then of course depending whether you are a an inventory-based small business a services-based small business or any other of those Maria different ones there will be Pockets within each of those verticals where the data is incredibly rich and you can do a lot of other things with it I find it fascinating the idea that small businesses are incredibly buried in maybe more so than than large businesses perhaps so given that you've got billions of customers like what happens if you do patent breaking finish on this how do you what if you do a cluster analysis on small businesses one of the sort of one of the groups there yeah it's not so much that small businesses are more diverse than big businesses it's that you like if you're thinking about a bank a bank can afford to employ a human to look after the accounts of small business that's worthwhile you can't afford to employ a human to look after the accounts of one small business if you're a bank so that's why you need data to do more for you but it's extremely diverse what you're talking about I think leads leads inevitably to the Holy Grail of accounting which is small business benchmarking um lots of people work on small business benchmarking we're certainly very interested in it let me let me talk about one piece of it perhaps uh one thing that when you have to start thinking about quite hard when you start getting into this is what's a similarity metric how do you come up with a robust similarity metric to describe whether richly small business is similar to Kendra's small business and therefore if we understand that they are similar what how can we sort of say oh well Richie small business appears to be more profitable even though it is similar to Kendra is therefore how can we tap into what he is doing better than she is um there's an enormous amount of data cleanup to be done if we go back to the conversation we're having at the very beginning of the hour um when you are trying to get into something as esoteric as similarity measures in something as non-standard and multi-dimensional as small businesses there is an enormous amount of work to be done to Define what dimensions of similarity are we interested in so there's perhaps is there a simple answer to your question no there is no simple answer to your question is it an area of great interest to almost everybody in the small business economy absolutely there is and it's actually where perhaps some of the most fascinating data challenges in machine learning challenges go on because you do get into some fairly fundamental concepts about we we probably want to adopt something fairly similar to the concept of um vector embeddings but now instead of vector embeddings into a phase space of the English language you're talking about Vector embeddings into the phase space of a business similarity dimensional universe what does that even look like it is a really complicated and honestly really live question that a lot of people are pursuing um even when we get there I think the answer will still be just as the multi-dimensional face-space of the English language is incredibly sparse in patches you'll find the same thing I think in small businesses that will clusters emerge yes clusters will emerge they will be associated with with business verticals but there'll be an enormous amount of subtlety between those things because there's enormous amount of subtlety between you know a lawn mowing business perhaps running out of Queensland Australia and a lawn mowing business writing out of you know sorry so yeah I think enormous amounts to be learned there people very very busy doing so probably one of the most challenging questions to answer in a practical way could an AI products team amuse itself in that space for a very long time yes I'm sure they could can we give a definite guarantee that in six months time we can build a really tangible product much trickier because small business owners and their accountants can't agree on what dimensions is important to Benchmark small businesses and when humans don't agree you know you're going to have a really interesting and challenging time building an AI system that can provide an answer because two sets of humans will say I don't like your AI system because it doesn't it doesn't align with what I believe the most important similarity Matrix are from that's a really great answer I assumed to have stumbled into a very deep research problem perhaps this is something our listeners can spend some time thinking about it sounds like there's a space for some incredible research wins there maybe even some business wins if you haven't figured this sort of stuff out um all right I want to go back to a point you made earlier about well sometimes small businesses Thrive and with um a growing roster of staff what's the point um in a small business life cycle where you say okay now we can start employing some data professionals ourselves only a very small debt useful right you can run an incredibly productive small business um you know doing graphic design you probably never find a place in which um it's useful to generate uh to employ small businesses that's correct to employ data professions um so let me just touch on a couple of spaces where I know that people have done so and it is useful um I think one would be the sort of the high volume Drop Shipping type applications so people who run thriving businesses which are fairly low staff where they are um fulfilling online orders so I think that those spaces you can get to quite High Revenue generation perhaps not profit because you know it's it goods and goods out but quite High Revenue generation with fairly large volumes of sales rolling through and those are spaces where I think that I know some some small but successful business in that space have found it useful to bring info who can look for the patterns in that because those a lot of those businesses are volume games and so they lend themselves to what data can do really well at scale which is shave percentage points off of cost and therefore you know just streamline that so that's one where I'd say is I think that there's certainly those sorts of high volume sales businesses um can make use of can can find it valuable to have people maybe maybe not on permanent stuff maybe on contract um to do pattern analysis for them of this house um I mean that's the one that Springs to mind there there are certainly there are certainly um lots of verticals in the small business industry where this is important and I know that because there are now more than a South in the zero App Store so why do I mention that well from the very beginning of Sarah's business our founder knew that the small business economy is incredibly varied and one company trying to build to the needs of all of those people is inevitably going to fail badly because we can't possibly spread ourselves that then and so we have the zero Marketplace and within that space there are apps aimed at particular sub segments of the small business community and I think that that is where you will see the really data rich areas is where you see the clusters of apps coming up with particular problems so one that's just quite close to my mind to my heart personally is um the needs of the Agri tech industry so I have a hobby farm and there's a Hobby Farms where I hope to retire to one day um in beautiful Regional Victoria and so I'm really really interested in how you do broad acre farming in small scale and how you run cows and how you we have anything other than a grass farmer and I really love talking to the agronomists who work with the farming communities in Australia they mine the data within xero to do things like help inform their you know their massive broad acre farming so they're big farming clients um fertilizer yields so you know they they mine the information of how much you're spending on nitrogen-based fertilizer how much you're spending on extra stock feed how much you're spending on herbicide they add that data to the information of where you are when you are applying it where you are applying it at what levels you are applying it and they do an enormous amount of add-on work in understanding crop yields and um stock yields and all the rest of it and then advising multi-million dollar family businesses on how to make their farming operations more effective so there's another place where data professionals certainly have a place to play now those are reproducible enough that there are actually businesses with inside Sarah's App Store that specifically concentrate on providing some businesses with those answers so that's a place where maybe it's such a useful such a replicable need that people have actually said well there's a whole business model around doing that and so I'll hire some of those data scientists and I'll get them to focus just on the particular problem of how do I better inform farming operations so there's just there's heaps and heaps and heaps of places within the small business economy where either it makes sense for an individual small business owner to employ one or two people who are Savvy and comfortable with data or there's actually an entire business idea around bringing that data together enriching it with data from different parts of an organization's operations and and building a software solution when there's certainly employability for data scientists and and our analysts and data Professionals of all kinds in those spaces I have to say I'm always amazed at how much data there is involved in farming when it seems like such a a low-tech feel but actually that there's so much there um and your other example about logistics and if you're putting packages everywhere then there's going to be a vast amounts of of data involved in that but it just seemed like um in the small business space your point is that a lot of um the data usage is going to come through software rather than someone just messing about with python or whatever it is going to be encapsulated uh in a platform uh rather than being just numbers crunched by an individual and I think this just a scale scale one thing I we get a lot when chatting with small business owners and accountants is one reason we use SAS platforms is because then we can have Kendra as our chief data officer and Susie my colleague as our chief security officer you know which is effectively true right now as a small business owner I can't afford Kendra and Susie as my chief data officer and my chief security officer and nor would I want to because it's not my core business but why one reason I'm comfortable with paying a subscription model for a cloud platform provider is because of the expertise I effectively hire through that and small business owners actually think like that quite a lot more I think than really large people who work in really large businesses do they're like yeah I'm effectively buying a tiny fractional CDO and Tiny fractional ciso um so I think that small businesses huge generality there's an amazing number of different kinds of small businesses but they are quite plugged into the app ecosystem and that concept so I think yeah if you're interested in the space and your interest in your data professional who wants to work in that space one way is of course finding a thriving School business that is trying to become a not small business and therefore might have the space to bring you in as a dedicated professional but another way is just to look at all the places in the ecosystem of small business where a lot of data flows and either if you're entrepreneurial start your own small business around the small business data flow or find someone who also finds that a really fascinating problem and is trying to solve it and get on board fantastic I like the idea of starting a small business to help small businesses it's just small businesses all the way down all right um before we wrap up um is there anything you're working on at the moment that you're excited about I think one thing I I have perennially been excited about and it's um it's only growing at the moment with the the uh hype cycle shall we say of chat gbt is data literacy so I'm the mother of three children who've finished through the education system or often tertiary education now and I want them to have long and productive careers and I want that for everyone who's listening to this podcast I think that it is true now and it will only become more true over the next 50 years that being comfortable and confident with data with what it means with how we treat it well being able to spot when someone is lying with Statistics being able to understand how to use statistics to understand more about it is only going to become a more important part of the working life of every person listening to this podcast so that's a big big thing for me I'm really excited about uh helping people have the confidence to do things you making use of all of the tools that are emerging and and maybe using this Tipping Point with um with tech TPT and large language models becoming part of the vernacular to reinvigorate your confidence reinvigorate your your thirst for Learning and say I've got 40 years working ahead of me 50 years 60 years we're all going to be working for a real long time right because if we're all going to live to 100 we're all going to be working into our 80s how do I how do I um build into my sort of my patterns my habits I thirst for learning a thirst for re-educating myself and reinvigorating my um my career prospects and how do I reach out and use those incredible online resources to become a more confident user of data I'm passionate about that because I think it really will assess millions of people to become confident literature um and economically productive and I'm also excited about it because it feels like now is a time when people are being exposed to a much greater extent than they have been and so it's a good time to make that mind shift and to say okay I'm gonna jump on this bandwagon and I'm really going to learn so that would be an area that I'm really passionate and excited about fantastic I like the idea of just having this thirst for learning uh because you're gonna have a long career that's brilliant I think it's a great note to end on uh so thank you very much Kendra I think you Richie it's been a real pleasureI think that it is true now and it will only become more true over the next 50 years that being comfortable and confident with data with what it means with how we treat it well being able to spot when someone is lying with Statistics being able to understand how to use statistics to understand more about it is only going to become a more important part of the working life of every person listening to this podcast hi Kendra thanks for joining us on the show today oh it is a real pleasure to be here we spend a lot of time on the show talking about Enterprise data and that's all quite excited to hear about the opposite to talk about what goes on in small businesses so I guess to begin with uh can you tell me what are the main use cases of data in small businesses oh my goodness it isn't a wide-ranging question to get started with um so zeros sort of original premise is is to be the backbone of the back office small business so we offer the general ledger in the cloud so effectively it doesn't matter what kind of small business you're running you in almost every jurisdiction you need to pay tax and hopefully you'll be profitable and so to do that you need to understand fairly intimately the finance that runs through your business so that the small business data that we are interested in Passionate in obsessed with I would say is effectively that the lifeblood of the school business the cash flow that runs through it the payroll the inventory the the financing all of the things that perhaps you didn't go into small business to do but if you don't do it well you won't stay in business for very long okay so it seems like the place to get started running business really is worrying about what's the the financial data what's happening with that making sure that you are sort of doing your payroll your taxes correctly it's sort of one of those things that you want to spend as little time on as possible but as much time as necessary because it's not why you went into business unless you happen to be an accountant or a bookkeeper but it is really really important to make sure your business runs well and probably a little different from country to country but where I am today recording in Australia 90 of businesses in Australia are small businesses so it is an enormous part of every economy I hadn't realized it was it was so important that I suppose yeah really think about it there are an awful lot of small businesses around um and I like the idea that um it's uh something you want to spend sort of just enough time on because uh sometimes you get over excited about data here we're like oh yeah everyone should do more more things a day to but often if you're a small business owner maybe um it's not where you intended to be spending your time but uh we'll get into that in maybe a more delays to tell in a moment but um first of all have you seen any success stories from small businesses making better use of data so I one reason I love working at xero is I love the fact that many people I run into industry are users of our software so I can continually say that people say how weird you work and I say I work at xero and your hairdresser your plumber your little coffee shop they genuinely say oh I love Sarah and the rest the reason is kind of what we were just touching on I love zero because it makes my life easy so I would say there's a general High tone of I like it because it reduces the time I need to spend on those things if you then dig deeper into success stories for me probably if I think about some of the conversations I've had some of the perhaps slightly larger small businesses if that makes sense who have been running for a little while so now the perhaps they have a couple of years worth of inventory or a few years worth of repeat orders they actually find even the ones who perhaps aren't data Savvy by Nature when you sit down with them and say well do you know the wealth of information that now sits and the records that you've been keeping with xero um they actually have gone through and discovered things like order time lags or customers who order in a seasonal pattern and then have been actually able to reshape their their ordering or their Staffing to meet that demand so yeah when people are perhaps given a little bit of a nudge for the folk whose businesses aren't data oriented but you give them a little bit of a nudge and you say think about what actually now sits in the records that you have usually what you hear people say is I can be more efficient I can serve my customers better or I can save money all of which are wonderful things if you're a small business owner absolutely I love the idea that just being able to surface things like seasonality or order quantities can make a huge difference to someone's livelihood and it's the thing right we think about it the big businesses particularly I'm sure many of the folk listen to this podcast who are data practitioners and they think about this all the time and many of them will work in large businesses optimize millions of customers now we have millions of customers ourselves at zero but our customers our small businesses they don't tend to but they can take those ideas of looking for patterns and enormous amounts of data and look for patterns in their smaller amounts of data and it's still really really valuable absolutely and some of the sort of strikes me um if you've got one or two business owners who are doing everything then you're not going to have the resource to have a data specialist to help you look at all this stuff so how can you make effective use of data when you have this limit to your resources it's a really good question and I think we would try to answer that in two ways one is to encourage people that when they use a product such as xero their data is actually quite tidy and quite neat and many people listen to this podcast and be very aware that the large amount of time spent for a data practitioner is needing up your data so for folk who are using a cloud software provider for doing their accounting actually a lot of that uniqueness has occurred so that you know they um if you're using multiple Banks you'll have pulled it into a single Bank etc etc the other side of it is we are always as a company striving to make the this simple for our customers so we build products that do that and deliver them through xero so for me for my machine learning team my AI products team we have two mantras that we build towards one remove toil use the data and the patterns from the data to make small businesses life easy and two Delight with Insight if we can pull patterns that say hey Richard you seem to come in every Thursday at eight o'clock in the evening and these are things you do so we're going to queue them up for you and suggest to you that this time we've already taken care of is when we have a suggestion for and this one oh this supplier plays late so we suggest that you go and lunch that supplier so you can make payroll next week that's going to make your life easier so that would be I'd say the two sides of it one the data is tidy for those human beings who would like to delve into it to find their seasonality patterns and their big customers and two all good software providers should be working on that data to pre-provide the value that you can get from it so uh that first idea around making sure your date is tidy it's one of those things that sort of easier said than done so do you have any tips for how you can go about making your data tidier or easier to analyze as a small business owner put your attention is Paramount if you would like to be able to derive value from anything including data you need to pay attention to it when you are generating it so if you are a small business owner saying I'm sure there'd be something in there you sort of need to begin with the end in mind if we go for a you know a well-known phrase what I mean by that is you need to label it correctly you need to categorize it consistently you need to as you go through your general ledger categorization be consistent in the saying this is office supplies all this and that sounds boring and it sounds mundane but it's actually as you know everyone listing here will know it's the Bedrock of being able to do anything useful because what are you trying to do when you look at data you're either probably trying to eyeball it yourself for patterns can't find patterns if you haven't added them or you're trying to feed the data to the machine and as we all know if you machines are really really good at picking up whatever is actually there and if what is there is noise they will pick up the noise so I would suggest that paying attention to making sure that you are generating the data and the labels around the data I.E the categories and the annotations that you put in a consistent fashion will pay dividends in allowing you to import information out of that data I like the idea that I'm just doing really simple things like categorizing your data consistently is going to pay is going to pay off in the future so something that might seem boring is really going to benefit your business now I think as you mentioned a lot of people when they go into business they don't necessarily care about data that might be a bit hesitant about using data so if I'm a plumber or a cook or something then I'm not necessarily going to think oh data is something I should be spending my time on so what data skills do small business owners need first one everyone needs is just a little bit more confidence um and you can get that by sitting down and working with your bookkeeper so I think accounting is a really interesting space because some of our primary users are actually folks who are really number seven accountants and bookkeepers are actually really numerically literate number Savvy people now they might have some concerns around the technology side of things but if they they are really good at dealing with data because they have done it all their lives so one thing I'd say to small business owners is that advisor you have that bookkeeper that you work with that accountant who looks after your taxes at the end of the year if you approach it with curiosity they're actually a fantastic resource to helping you become more comfortable with data and um they're probably be quite delighted if you ask them because you know when you do poor coding on the general ledger side of your input they're the ones who sort that out and make sure that actually a tax time everything flows through really smoothly so that would be one suggestion would be lean on the business partners that you have today and then the other one would would be to put down your preconceptions about the fact that it is difficult or the fact that you need specific skill to do it and there are lots of great online resources if you want to read about it but essentially yeah I'd approach it with a child's mind and say I believe I can learn about this information and and start from there with one one back there for me is I think our education systems universally across the world kind of turn people off doing quantitative things we don't unfortunately teach math particularly well we teach statistics if possible even worse and people tend to leave formal education with a misconception about the fact that it is a Part B complicated and c not for them and if you can put down a b and c and start again and say well hang on every time everything I read in the paper says the machines are taking over the world that data literacy is going to become more important how about I give it another crack and try again with my newly enhanced Googling or chat TPT skills um give it another go would actually be my biggest recommendation that's fantastic because it is so easy to say oh this isn't for me this is a hard thing and give up before you even uh before you even tried anything I don't like the idea that you just gotta give it a go and see um so trying to be uh maybe more more concrete about this I mean so we talk a lot about um the idea of data-driven decision making and as a small business owner you have to make a lot of decisions yourself so how can you bring data into that process of making decisions about your business so I kind of I can't let me give you two examples um which you certainly could do yourself or if you are a user of xero you can make use of um the products that we offer so one of them is forecasting your cash flow so a very very very common reason that small businesses go out of business is because of cash flow problems and I don't know what it's like in every jurisdiction that we operate in but certainly in Australia we have challenges with big businesses paying small businesses slowly so it's really common to sit on a float and be like oh you know what I'll just paid my invoices a little late I'll keep that money in the bank and I'll use that as a flight to run my own business and Beekman says engage in that practice unfortunately so cash flow I or the lack thereof people not paying invoices on time is a huge reason that small businesses go out of business or can't make payroll so what what is the first thing that you can do to assist a business with that apart from trying to influence government policy to make big businesses pay on time what you can do is give people information about payments so we have built and continue to extend and work out a cash flow forecasting app which looks at the sequence of payments into your accounts over the last 30 60 90 days and forecasts forward what your level of cash flow intend to be now I know that people can and do do this themselves I know that because I was at a cocktail party on a frigate true story and was talking about the fact that I worked with xero and one of the gentlemen there who was a port designer say to me ah short-term cash flow forecasting he said I used to do that myself in a spreadsheet and now I use your app which I was delighted but so you can do it yourself but what it effectively says is in 30 60 in 90 days given the pattern of transactions and the pattern of payment coming into your account this is the cash flow balance we expect to see in your account and that's transformative because it allows you to say I can't make payroll unless I dig in and understand that one supplier who has a habit of paying 14 days beyond the due date has on time okay that's an action that I can take I can ring that supplier and say mate I need you to pay me on time I don't set my payment terms you know for amusement value I set my payment terms so that I can make cash flow and payroll and pay my themes so cash flow forecasting is one great way to use data to inform how you run your business um another one that I know is just so valuable to the small business economy so again I'm going to you know sort of talk through it is at the other end when we are pulling information out of everyone's bank accounts and into the general ledger there is an incredibly tedious process that all bookkeepers and small business owners need to do which is called coding your transactions to the general ledger and that's where we're talking about before of providing high quality data it's saying ah that oh yeah that was when I took client X out for the coffee oh oh yeah that's when I had to make the emergency run because I'd actually run out of envelopes and I went into the officeworks and purchased some things and putting those against the correct um categories now again that's the place where you as a human if you are tidy and organized and consistent in your coding can speed yourself up but it's also where machines can do a great job because that's where you can Source the wisdom of crafts you as a small business owner intimately understand your own purchasing habits we as a SAS software provider don't but we do have the benefit of millions of customers transaction habits and hundreds of thousands of bookkeepers categorization habits so we can and have and it is now available in our software create machine learning driven predictions of that category that just that's right that transaction line that just flowed through from your bank account we believe it belongs here would you like to accept that yes in an amazing toil reduction for small business owners because it is a lot quicker to review what a machine has suggested to you you might want to accept accept it 90 of the time and go oh silly machine you got it wrong 10 of the time then to actually have to access your own memory every single transaction and click all the buttons that allow you to category eyes so those would be two places I think you can use data to speed up your day-to-day so you mentioned that at xero you have millions of small businesses and you can see patterns across the data that an individual small business couldn't see can you give me an example of some of these patterns that appear yeah this is actually another really really interesting one um folks were just in raptures so we have a product um in a number of a number of the company countries we work in called Hub Doc and hubdoc allows people to upload their financial documents and to have those financial documents automatically processed and added to their accounting software and we have for a number of years had a machine learning driven pathway so that when you upload your financial document be that a bill an invoice uh it's goes through OCR optical character recognition that comes out as an electronic version of itself and we then go go through and pick out the key Fields so we can pick out what currency is that in what date was it who was the merchant and what is the um the invoice total for instance let's say now one of the most annoying things and I'm not an accountant so people will have to forgive me if I get this slightly wrong but I'm fairly sure I'm correct is when what you think is an invoice comes through but it is actually a credit note so rather than somebody charging you money they're actually giving you money back because you've overpaid a previous inverse or something like that now as you can imagine if you have a document come through and you code it as an invoice when it is actually credit note in your back end you actually end up with a double up problem because it was money that was supposed to go on one study alleged and goes up on the other so say it was 25 Grand you'll actually get a fifty thousand dollar offset of incorrectness and where the money is supposed to be because you took negative 25 and put in a positive 25 effectively you've got a 50. so it is the bug bear of small bits and signers accountants and bookkeepers everywhere when somebody miscodes a credit note because you have to go picking through the reconcile General lecture understanding how on Earth you have a fifty thousand dollar incorrect level in your bank account versus your reconciled Ledger now what we are able to do by looking at millions and millions and millions of financial documents was build something called okay this is you know our great naming here credit note detection but it does exactly what it sounds like it does it's not a simple problem as your listeners will understand because it's anomaly detection and anomaly detection is hard because for every for every credit note there are I'm going to get the slightly wrong at hundreds if not thousands of invoices so the documents look very very similar some people will stamp credit notes across them and that people won't they look very very similar and one percent ish or a fraction of a percentage I actually create a note so it's a hard thing to do well it's also actually a hard thing for humans to pick up because we're really really good at getting into the mode and just going yep click click click click but that is an example of where we can use interactions or millions of people to pick up the subtle patterns that indicate this isn't an inverse its credit note and actually alert humans in the flow so that's something I really like too is actually the way we do it it's very easy for humans to fall into the mode of I'm just clicking a button and we need to be reminded or you probably need to pay a little more attention before you click this button and it's one of my sort of hobby horses is I get frustrated when I hear people think that an AI product is the algorithm it's the sexy part gets uh talked about so the part that gets published it's the part that gives people patents but it's only part of a really functional AI product and when I'm talking to folk about how to build really functional AI products I'm always reminding them that it's a systems problem and that's it's the end-to-end flow including the human and in this case a credit note detection the piece of the of the flow that actually we thought quite hard about which is this is an impactful thing because if we get it wrong it's really annoying and if the human doesn't notice it's really annoying it's in the wrong place so we actually subtly but in a nice in a way that who a human stands out because it is different redesign the interface at the point where we say hey human we're fairly sure that this is in fact not an invoice a credit note but we suggest that you now pause and take a little time to think and to genuinely verify our decision and so that just that subtlety in redesign the interface and making that pop up to the person in a way that is noticeable was a really important part of building a really useful AI product and we roll with credit note detection out gosh time flies so it's probably longer ago than I think it is now several months ago and I kid you not people love it to Pieces it was one of the most requested feat product features and when we rolled it out people were in raptures that we have now an anomaly detection system that allows them to avoid accidentally coding a credit note as an invoice thus fascinating and I love the point that the AI is just a tool and actually the thing you're trying to improve is the customer experience so you really have to think about the user interface and things like that so in like um do you have any advice on how things like the design and product teams can work with AI and sort of understand the nuances here because sometimes um you have you sort of AI and data teams separately you're from the the product teams and maybe um the communication between them can be quite tricky do you have any it seems like you did a lot of wraggling of the these different teams so I'm as curious as to your advice here yeah it's a really good question and I have really strong advice don't don't have separate algorithm and product teams it is insane it adds way too much overhead and you'll end up building things that each side of that equation thinks are good and your customers think I'm not so good if we are polite for their language um an AI product which to my mind 100 is the end-to-end complete customer experience including the human computer interface is no different from any other product you wouldn't arbitrarily split up another product and say you know what you do the button and use this bit and you do that in my lived experience AI products are harder to build they're harder to build because we're not as used to them because they are complex and subtle and because you are hard coding in a way that is almost impossible to really pull apart you are deeply wiring together a flow and the the large amount of data that your algorithm was trained on and it's you know that long time ago Google wrote a paper called the high interest credit card of technical debt machine learning the high interest credit card of technical debt and it's because of that absolutely insoluble tight coupling between the data that your algorithm was trained on and the end-to-end flow that your AI product has they're harder to build they're more expensive to maintain you want to start off with a team setup that is as optimized for that as possible so just don't separate them in my opinion if you want to build something successful the other thing I would say is this is tricky because in my experience AI product Builders are a lot more iterative than other types of product build I've yet to find a team who can sit down at the beginning of a challenge and say yep I can absolutely guarantee for you that with the data available to us today we will be able to build a product that is acceptable to the human users within three months maybe there are teams out there who can do it who are iterating on a product that they have already built but I think it's incredibly unusual so you need to allow for more iteration time what I would say though is perhaps there is not full-time work for a designer throughout that entire process but robot tied the team that thinks they don't need a designer involved right at the beginning of the conversation so get your cross-functional skilled team together at the beginning of the conversation get them to know each other get them to appreciate the other person's skills but don't skip that step don't skip the step it says at the end we need to have an end-to-end usable product that humans don't have an uncanny valley reaction to that doesn't trip them up from their workflow that doesn't provide something that is so subtle that nobody ever noticed had happened they're expensive they're slow to build we sure as heck don't want to get 95 of the way there and then discover that we have an unworkable human human computer interaction so take my advice get those work involved right at the very beginning that seems like great advice to get all the people you need together at the start and I think you mentioned that almost no one will tell you that they can do this sort of thing in one go probably the people who do tell you that they could do and won't go there they're people that you don't working on this sort of uh project I think they're almost certainly focused simply haven't done that before or what I see disconcertingly too much of now and it'll ebb and flow because we're humans and we'll come and you know we get over things um but there has been at least in my head at least twice two waves of this and I think we're in another wave right now is very enthusiastic software engineers who believe that as long as they can call an API they understand how to do machine learning and we've all gotten very excited in the last few months about the amazing accessibility of really competent large language models and oh my goodness the number of people I have heard tell me say to me oh and you know we can just call the API can you now good elections there or the beautiful uh the beautiful Board of Forbes type article that was circulating with all the boards in Australia and I'm sure all the boards in the US as well the cost of software engineering is going to go to zero in the next 10 years is it now sneering is only writing code is it is that right so I would say yeah absolutely folk who who tell you that this is going to be very quick now because all I'm going to need to do is stitch together multiple calls to check GPT using Lane chain have never actually tried to build a functional AI product so avoid them bite the plague or if you really need their skill set Embrace their enthusiasm but make sure that they work in lockstep with folk scientific training who understand how to build experiments and test the outcomes of those experiments and use the interface experts and product managers who really understand what the customer is after because it's very easy to think you are building for the problem that you're trying to solve but actually build to solve a subtly but importantly different one and I'm sure we've got a few Chief Finance officers listening thinking oh yeah cost of software engineering go down to zero that sounds brilliant but it might be uh might be wishful thinking um On a related note so um you said that uh these sort of new generative AI tools the large language models uh that may be not um uh well they're sort of difficult to build products for but are they useful to small businesses I think at the moment what we see is that they are difficult to replace humans with and you have to think really carefully about doing that they certainly seem to be very very attractive for augmenting humans with so I'll just give you a couple of the for instances that I've I've heard from small business owners um one of them is writing boilerplate or what I call breaking the white piece of paper problem who hasn't sat down in front of a proposal they need to write or a letter they need to send and go on ah I'll know it when I see it but how does that go again particularly you know you haven't had coffee on a Monday morning I I know a large number of small business owners who are this their go-to they have it open next to Google I'm sorry I'm talking chat TPT the interface open AIS interface they have it's open next to Google and they use it to generate the first draft of communications and I do stress the first draft if I've got extremely excited about it back in you know back in the before times January and February um and thought that it was going to be uh drag and drop replacement for a lot of the things they did the impression I get talking to folk now is it's like having an intern that you know they'll get it to 90 but you're always going to need to take that extra 10 yourself so where I see small business owners as owners using it is largely in doing desk research if they you know if some folk just really prefer the back and forth that you get from a chat bot than that you get from the search engine and creating first drafts boilerplates break the white sheet of paper for written customer communication now I would say that they are also pretty careful to note now perhaps they weren't four months ago but they are now yeah but you do want to read it before you use it because it will it will get at 90 percent of the weight there perhaps even 95 of the way there but as we're seeing player in the courts now as the human who uses it you're the one that's responsible for it so that would be my just my note of caution to some small business owners is it's still you it's still your business and I would always read very carefully anything that came out of a generative large language model because it's not sentient it does not know what it is doing it cannot give you a confidence level for how confident it is that what it has said is the right answer to your question it is a sequence generating machine and it is generating you as statistically likely sequence to the sequence that you put into it so yeah so since you were mentioning Plumbing businesses earlier than Rob boilerplate no I think yeah it's great for writing boilerplate not good for fixing boilers at the moment certainly true that would be a good Adventure though AI that comes in there Fix You boiler all right so um moving on to uh getting back to sort of uh using data in small businesses are there any important business metrics that you think um are important as a small business oh I am not an so I should put every of amateur opinion it really depends on your business Richie um and this is something that I would simply say having had conversations with many many small business owners um the ones that they all come back to is cash flow incredibly important um cost of goods sold incredibly important um there's a lot of subtleties around payroll and understanding particularly Awards rates so extremely important to understand your your obligations as an employer and that's something that again a lot of small business owners don't go into business to be employers but then as their business thrives and they become really successful they suddenly discover that there are lots of people um so having a really careful understanding of of making sure that you are doing everything that you need to as an employer is probably another place where I'd say paying really close and careful attention to that data is really important okay so it does seem like um a lot of this really is around like uh the finances of things and also around maybe some of the the comply and stuff like uh like tax and regulations and making sure you're doing the right thing there so I think it's I should get the best the best right right so so we I as an extremely difficult area to crack if you think about companies like xero like financial institutions um I've worked in financial institutions for many many years not recently but for many many years and small businesses really really hard anyone who works in a large bank will tell you yes just really hard what is the reason for that the reason is because small businesses are incredibly varied like as much as we will as humans would like to think we're unique we're kind of not like consumer patterns consumer patterns are reasonably easy to tap into and reasonably easy to um fingerprint we spend fairly similarly it is not difficult for a bank that has a significant amount of your banking to figure out quite a lot about your spending habits and to figure out quite a lot about your household composition from the spending habits there are just two things one although there are an enormous number of small businesses there are a lot less small businesses than there are spending households so we have a small data problem and within that somewhat smaller pool of small businesses there is a far greater Dynamic versatility of the types of small businesses that you have so that's why I think that it's it's much it's difficult to say this is the killer app for a specific vertical because there are there are killer applications for data for all the different specific verticals of small business but they are myriad so what's the common thing that all small businesses have in common so that it's easy for you know in a general podcast or a general conversation to zero in on it is the thing that everybody has to do everybody has to make payroll everybody has to pay their taxes everybody has to understand that they have paid their bills that their suppliers are paying their bills so there's a reason I think beyond the fact that I work for an accounting company there's a reason for the fact that we all come back to the lifeblood of small business data being around finances because it is the common thread that all small businesses have to do well then of course depending whether you are a an inventory-based small business a services-based small business or any other of those Maria different ones there will be Pockets within each of those verticals where the data is incredibly rich and you can do a lot of other things with it I find it fascinating the idea that small businesses are incredibly buried in maybe more so than than large businesses perhaps so given that you've got billions of customers like what happens if you do patent breaking finish on this how do you what if you do a cluster analysis on small businesses one of the sort of one of the groups there yeah it's not so much that small businesses are more diverse than big businesses it's that you like if you're thinking about a bank a bank can afford to employ a human to look after the accounts of small business that's worthwhile you can't afford to employ a human to look after the accounts of one small business if you're a bank so that's why you need data to do more for you but it's extremely diverse what you're talking about I think leads leads inevitably to the Holy Grail of accounting which is small business benchmarking um lots of people work on small business benchmarking we're certainly very interested in it let me let me talk about one piece of it perhaps uh one thing that when you have to start thinking about quite hard when you start getting into this is what's a similarity metric how do you come up with a robust similarity metric to describe whether richly small business is similar to Kendra's small business and therefore if we understand that they are similar what how can we sort of say oh well Richie small business appears to be more profitable even though it is similar to Kendra is therefore how can we tap into what he is doing better than she is um there's an enormous amount of data cleanup to be done if we go back to the conversation we're having at the very beginning of the hour um when you are trying to get into something as esoteric as similarity measures in something as non-standard and multi-dimensional as small businesses there is an enormous amount of work to be done to Define what dimensions of similarity are we interested in so there's perhaps is there a simple answer to your question no there is no simple answer to your question is it an area of great interest to almost everybody in the small business economy absolutely there is and it's actually where perhaps some of the most fascinating data challenges in machine learning challenges go on because you do get into some fairly fundamental concepts about we we probably want to adopt something fairly similar to the concept of um vector embeddings but now instead of vector embeddings into a phase space of the English language you're talking about Vector embeddings into the phase space of a business similarity dimensional universe what does that even look like it is a really complicated and honestly really live question that a lot of people are pursuing um even when we get there I think the answer will still be just as the multi-dimensional face-space of the English language is incredibly sparse in patches you'll find the same thing I think in small businesses that will clusters emerge yes clusters will emerge they will be associated with with business verticals but there'll be an enormous amount of subtlety between those things because there's enormous amount of subtlety between you know a lawn mowing business perhaps running out of Queensland Australia and a lawn mowing business writing out of you know sorry so yeah I think enormous amounts to be learned there people very very busy doing so probably one of the most challenging questions to answer in a practical way could an AI products team amuse itself in that space for a very long time yes I'm sure they could can we give a definite guarantee that in six months time we can build a really tangible product much trickier because small business owners and their accountants can't agree on what dimensions is important to Benchmark small businesses and when humans don't agree you know you're going to have a really interesting and challenging time building an AI system that can provide an answer because two sets of humans will say I don't like your AI system because it doesn't it doesn't align with what I believe the most important similarity Matrix are from that's a really great answer I assumed to have stumbled into a very deep research problem perhaps this is something our listeners can spend some time thinking about it sounds like there's a space for some incredible research wins there maybe even some business wins if you haven't figured this sort of stuff out um all right I want to go back to a point you made earlier about well sometimes small businesses Thrive and with um a growing roster of staff what's the point um in a small business life cycle where you say okay now we can start employing some data professionals ourselves only a very small debt useful right you can run an incredibly productive small business um you know doing graphic design you probably never find a place in which um it's useful to generate uh to employ small businesses that's correct to employ data professions um so let me just touch on a couple of spaces where I know that people have done so and it is useful um I think one would be the sort of the high volume Drop Shipping type applications so people who run thriving businesses which are fairly low staff where they are um fulfilling online orders so I think that those spaces you can get to quite High Revenue generation perhaps not profit because you know it's it goods and goods out but quite High Revenue generation with fairly large volumes of sales rolling through and those are spaces where I think that I know some some small but successful business in that space have found it useful to bring info who can look for the patterns in that because those a lot of those businesses are volume games and so they lend themselves to what data can do really well at scale which is shave percentage points off of cost and therefore you know just streamline that so that's one where I'd say is I think that there's certainly those sorts of high volume sales businesses um can make use of can can find it valuable to have people maybe maybe not on permanent stuff maybe on contract um to do pattern analysis for them of this house um I mean that's the one that Springs to mind there there are certainly there are certainly um lots of verticals in the small business industry where this is important and I know that because there are now more than a South in the zero App Store so why do I mention that well from the very beginning of Sarah's business our founder knew that the small business economy is incredibly varied and one company trying to build to the needs of all of those people is inevitably going to fail badly because we can't possibly spread ourselves that then and so we have the zero Marketplace and within that space there are apps aimed at particular sub segments of the small business community and I think that that is where you will see the really data rich areas is where you see the clusters of apps coming up with particular problems so one that's just quite close to my mind to my heart personally is um the needs of the Agri tech industry so I have a hobby farm and there's a Hobby Farms where I hope to retire to one day um in beautiful Regional Victoria and so I'm really really interested in how you do broad acre farming in small scale and how you run cows and how you we have anything other than a grass farmer and I really love talking to the agronomists who work with the farming communities in Australia they mine the data within xero to do things like help inform their you know their massive broad acre farming so they're big farming clients um fertilizer yields so you know they they mine the information of how much you're spending on nitrogen-based fertilizer how much you're spending on extra stock feed how much you're spending on herbicide they add that data to the information of where you are when you are applying it where you are applying it at what levels you are applying it and they do an enormous amount of add-on work in understanding crop yields and um stock yields and all the rest of it and then advising multi-million dollar family businesses on how to make their farming operations more effective so there's another place where data professionals certainly have a place to play now those are reproducible enough that there are actually businesses with inside Sarah's App Store that specifically concentrate on providing some businesses with those answers so that's a place where maybe it's such a useful such a replicable need that people have actually said well there's a whole business model around doing that and so I'll hire some of those data scientists and I'll get them to focus just on the particular problem of how do I better inform farming operations so there's just there's heaps and heaps and heaps of places within the small business economy where either it makes sense for an individual small business owner to employ one or two people who are Savvy and comfortable with data or there's actually an entire business idea around bringing that data together enriching it with data from different parts of an organization's operations and and building a software solution when there's certainly employability for data scientists and and our analysts and data Professionals of all kinds in those spaces I have to say I'm always amazed at how much data there is involved in farming when it seems like such a a low-tech feel but actually that there's so much there um and your other example about logistics and if you're putting packages everywhere then there's going to be a vast amounts of of data involved in that but it just seemed like um in the small business space your point is that a lot of um the data usage is going to come through software rather than someone just messing about with python or whatever it is going to be encapsulated uh in a platform uh rather than being just numbers crunched by an individual and I think this just a scale scale one thing I we get a lot when chatting with small business owners and accountants is one reason we use SAS platforms is because then we can have Kendra as our chief data officer and Susie my colleague as our chief security officer you know which is effectively true right now as a small business owner I can't afford Kendra and Susie as my chief data officer and my chief security officer and nor would I want to because it's not my core business but why one reason I'm comfortable with paying a subscription model for a cloud platform provider is because of the expertise I effectively hire through that and small business owners actually think like that quite a lot more I think than really large people who work in really large businesses do they're like yeah I'm effectively buying a tiny fractional CDO and Tiny fractional ciso um so I think that small businesses huge generality there's an amazing number of different kinds of small businesses but they are quite plugged into the app ecosystem and that concept so I think yeah if you're interested in the space and your interest in your data professional who wants to work in that space one way is of course finding a thriving School business that is trying to become a not small business and therefore might have the space to bring you in as a dedicated professional but another way is just to look at all the places in the ecosystem of small business where a lot of data flows and either if you're entrepreneurial start your own small business around the small business data flow or find someone who also finds that a really fascinating problem and is trying to solve it and get on board fantastic I like the idea of starting a small business to help small businesses it's just small businesses all the way down all right um before we wrap up um is there anything you're working on at the moment that you're excited about I think one thing I I have perennially been excited about and it's um it's only growing at the moment with the the uh hype cycle shall we say of chat gbt is data literacy so I'm the mother of three children who've finished through the education system or often tertiary education now and I want them to have long and productive careers and I want that for everyone who's listening to this podcast I think that it is true now and it will only become more true over the next 50 years that being comfortable and confident with data with what it means with how we treat it well being able to spot when someone is lying with Statistics being able to understand how to use statistics to understand more about it is only going to become a more important part of the working life of every person listening to this podcast so that's a big big thing for me I'm really excited about uh helping people have the confidence to do things you making use of all of the tools that are emerging and and maybe using this Tipping Point with um with tech TPT and large language models becoming part of the vernacular to reinvigorate your confidence reinvigorate your your thirst for Learning and say I've got 40 years working ahead of me 50 years 60 years we're all going to be working for a real long time right because if we're all going to live to 100 we're all going to be working into our 80s how do I how do I um build into my sort of my patterns my habits I thirst for learning a thirst for re-educating myself and reinvigorating my um my career prospects and how do I reach out and use those incredible online resources to become a more confident user of data I'm passionate about that because I think it really will assess millions of people to become confident literature um and economically productive and I'm also excited about it because it feels like now is a time when people are being exposed to a much greater extent than they have been and so it's a good time to make that mind shift and to say okay I'm gonna jump on this bandwagon and I'm really going to learn so that would be an area that I'm really passionate and excited about fantastic I like the idea of just having this thirst for learning uh because you're gonna have a long career that's brilliant I think it's a great note to end on uh so thank you very much Kendra I think you Richie it's been a real pleasure\n"