The 3 Phases of Making a Business Case for AI - with Scott Nowson, AI Lead at PwC Middle East
This is Daniel Fidel and you're listening to a and business podcast. This is our Thursday episodes. You know what that means will be focusing on making the business case for a in the enterprise, which is making the business case, really mean well. It means a lot of things it means anything that will essentially get the C. Suite to say yes to a project. We need to be able to match the right. A application to the right business problem need to build a potentially understand the state of our data and our company to know if we can actually leverage a certain application and we need to make the. Case we need to be able to convey what is the short and the long term value of this particular project or initiative sometime? That's short term. Financial are alive. That's never the whole picture. We've also got a paint the picture for strategy so this a lot of moving parts to make a I make its way into the enterprise if you sell AI products or services, that's topic obviously to your heart, but if you're looking to buy or deploy AI. Ai In your company. You still have to understand the same skills and we want to shed more light on that process. We believe that the people who are the catalyst who genuinely understand how to make the business argument for a and had to pick the right. Projects are going to be the people who make a big dent in their enterprise in in their industry in general in terms of overhauling it with artificial intelligence. We interviewed this week Scott. Is the artificial intelligence lead for the Middle East for PW C. Scott as a PhD in P and Scott is an excellent interviewee I've got a great relationship with Scott. He was on one of our previous episodes. If you go to our soundcloud or I tuned to search for Scott Nelson, he was in a previous episode about AI adoption. He speaks this week about the three phases of making the business case. So, what does it look like actually? Break up this business case presentation to three different parts what? What do you need to put together to be able to give yourself the best chance of getting the C. Suite to say yes of getting a sign off getting that pilots started getting that deployment, actually rolling and Scott does a great job of breaking down I think that these three phases obviously be thought of in many different ways as probably a lot of ways to conceptualize it, but I think this is a useful lens to looks from so without further ado. This is Scott Nelson here on the. Business podcast. So Scott the next question here is around building digital maturity when it comes to adopting I. It's not just about plumbing in having work. It's also about getting our digital infrastructure right building our teams in a new way potentially organizing our our it structure and some different fashion that often feels like a hurdle feels like a barrier feels like a reason not to do I. How she enterprise leaders think about that. It's not clearly just a negative, but clearly it is a bit of a cost is a bit of a hurdle. You like to frame it. I frame it pretty much like that that it can be a hurdle. That understanding of Ai, and where sits on your journey, and that it is part of a journey is critical. I've actually heard. It discussed on on the podcast before by the likes of Ian Wilson. World the world invests all the time in digital transformation. That's been one of the key things that consultancies in. The Powell world right now, but that's about aligning systems. Generation data. And then that comes ai transformation in our this is this off? You've gotten all your data ducks in a row then we can look at. Because having a long term, AI strategy is key to make a success, but key to that is having your data strategy in place. It's really hard to avoid that. It's just going to be more successful. Bought I- Tampa? That saying this should not be limiting factor for getting started with. Is this is you need to be thinking long term and short term? It's perfectly appropriate to start with small in house proofs of concept. To use off the shelf, cognitive sevices from from a Microsoft or an IBM say so. They are definitely barriers on hurdles and. In are in this region in the middle. East we find a lot of clients who may be onto mature in the data strategy yet. PASSIONATE ABOUT GETTING A I. Like to guide them from both directions his. How you get started quickly his how you can get some immediate value bought here the steps you need to take to get their longtime. And vendor companies I'm just thinking about maybe the even the software side, not even a consultancy sort of like you folks you. They often have to be the ones to introduce the C. Suite to the fact that yes, we can help you prevent payment fraud. Yes, we can help you to whatever count the number of people at India retail store whatever the case may be but. You know this this. This are also going to have to be required to start working with a in. That often feels like this this extra. This extra stuff some of them I. I think tried to make an argument and I think there should be an argument made in. You probably have a better one here that some of that maturity is an upside when we start working with the fraud data, we're GONNA figure out a new way to train to groom to store this information, so it can be of greater value in the long term for our application, and also you guys have a better understanding and more harmonized data set to do other applications within kind of sell, the necessary maturity part as a benefit as opposed to just a hurdle. Is there an approach? There is their way to think about that. The, that is actually an approach that works, it's honest it's true there are things that you can do in the shaping that will essentially form a discovery phase for something else like I'll go in and get your data out full you and it might be painful, but although a lot more about what your data looks like, and can advise you on how you need to fix it to make this easier next time. I will lend things within your data. The perhaps okay, here's some will use cases. If you did X. Thin. Actually you can enable why and. I've built you, but it also foams part of the business case say we've gone in. We've scrape data together. And we've done X.. Imagine what we could do. If you went back and invested in these other capabilities upscale you maturity, we've saved thirty percent on some task, and that was with the cobbled together data. The we have if you go through these phases than you'll have an even stronger business case so. The business case of one foams the business case of another. If you will, so it does work like that. It's not just a huddled. There are benefits to starting with anything. Yet and this, this is actually this rings. A bell and I've got a question from one of our emerged plus readers. It's related to this which all all ask in a second, but we you're saying really resonates with a recent interview that we conducted with a fellow by the name of Babic founded sentient technologies out in the bay area, and he's now with a big consultancy, but he mentioned that through these initial projects are often going to be the catalysts for modernizing data infrastructure, finding new ways to work together with cross functional teams, educating executives on Ai that often that maturity isn't going to happen unless a project has been decided on I. I kinda brought up with him. It almost feels could be a downside if we have project a project be project, see kind of sparking off in different corners of the business, and we have kind of data maturity, anecdotally sparking off in different corners of the business. Maybe that's you know disjointed and potentially the wrong way of thinking about maybe a smart enterprise would be thinking about digital ai maturity at a broad level and have a constant template to refer to any time they do i. do you see scattershot being the only way or even maybe the best way, or do you think that some central planning from an enterprise would be? Ideal I wonder what your take us. I think the for that I think that hybrid approach is much better. SCATTERSHOT is great. If that's how you got that, we started with one team. We did work with them. And then it trickled through the maturity came about it perfectly valid but I do think it is much better to be thinking while you're starting these little things somewhere atop. Quote Unquote needs to know. This is going on needs to know. This is coming on then, so start out as on the sooner you do it. Because as I said that long term strategy is key. The sooner you do it, the less you have to. Fit. All those cobbled together projects back into your strategy, because then you potentially end up with fifty projects whose code down to line they don't have metrics, and by the time you get in with you'll, you'll ai platform. Those kind of redundant. You might have to again. You've been getting value from them so it is that balance of meeting somewhere in the middle at the bottom down that maturity spread buses top down trying to get a policy. Get a framework in place. You know that we very much strategy motivated and It is just much better for long term success. So it's it's better if we can get our internal data, scientists together our business leadership together and say look. We're GONNA start kicking off pilots. We're GONNA have sandbox projects. We're GONNA have early deployments. Have things that we're going to move based on shared priorities, what should we have is our norms for how? Modernize or harmonize data. which should we have as our norms for how we retain the learnings in these projects? which should we have as our north you know. Is that the kind of conversation that should be had before we start these little spark off projects in different corners are what should happen in that conversation? I think that's right. It doesn't have to necessarily have him before as I said, but it needs to happen soon. Because what you find is questions of Rep Likability, if your little small spot, what? Could. You do it again and yes, you could, but you're essentially going to start from scratch so those conversations about how will you support re-use? How will you ensure some standards? How will you support? The data scientists who are they're all installing different python libraries on that different machines in different versions. How will you have that consistency like sort of any software engineering library, but then with ai you also need to start looking at governance responsibility ethics. Data Quality, and that can happen in the pockets, but it's so much more of a strong argument restaurant business case if it's constantly coming down from the top and the data, scientists played big part in that the quality control as the strategy teams. You know the larger the enterprise, the most stakeholders you will have again in the mall time. It will take to to pull this together, but. Those are the conversations have to happen. What do I need data scientists to support my work to make things easier. What do you need is the rest of the business to make this effective and work for you? Yeah! Why am I the Golden? Ideal I. Think would be that businesses would have that conversation like you said maybe not ahead of time. Certainly early on I'm imagining myself is a smaller. Ai Services AI product vendor of some kind. You know maybe I'm an adviser are on cell technology in some way. I go into a business I'm sort of wondering. Should I push this pilot through and get this thing to work with whatever the initial budgets are, or should I try to do my best to get some kind of that higher level alignment around what this maturity Models GonNa. Look like longer term because maybe GonNa, let me have a longer project in bigger customer lifetime value with this client, but at the same time. Maybe it's GonNa. Take an extra eight months to talk to all the Darn Sea level people. People and get on the same page. It really feels like a bit of a catch twenty two. If I'm selling into these big companies WanNa, do right by them. I WanNa have a good clv with the client, a longer term value for me, but an deliver longer term value for them, but then again it's like I. Want to move the Damn needle and kind of get started. He Serum Middle Ground. Is there a way to think about that? As an outsider, selling into or working with big impress? You're right because it's a very. It's an interesting point that you can have different perspectives on so a former CEO, once told me would back in Australia that there's nothing worse you can do than to lie to a client and the so much hype and underperformance in. You. Know even have this concept of a winter. You know we have this ocean. That could just stop at any moment. And I think the last time. I you had me on. The focused I, said Hey. I is harden. That's okay. Yup is still true, and from my perspective from ABC Perspective View. You have to help cons understand this. With Peter BBC that honesty, the integrity is is cool to who we all people trust us with the critical parts of the business, but I'm also aware that in our role we. Have the ability to help the clients. Step back to slow down and say look. These. Are the things you need to get in place? I'm very aware that we can have a strategy. All who can come in the implementation team will just take a step back on white for year while the strategy team. Does that thing in the long term success? That's great. The context the Yoto him out. Though you know not, everyone is in that position. If you have this niche capability, you really do need to sell. You have a technology. I think that is a pot where advising on some of these aspects and you can't. You can't entirely shoot yourself in the foot by saying you're not ready for what we have. You not ready to what we have because I think you'd find. Most people aren't ready for what you're selling. So you then get that scattershot approach that we told you about. You can get a team so long as the team you'll coming in with understand this situation in in, you can help guide them. And by taking that approach that it doesn't have to just stop top down. Then? You can get that in and then maybe there is room for it, and you can get long term success with one team but I. DO agree that being opened that this would be so much better if you know absolutely what we have can work for you bought. We can see opportunities in the rest of the company. It's almost being there chilly. Though coach Your Business, you can have a great success with them, but you want them to be a success to you know we'll build this view This might apply cases, but we'll build this view. We'll help you take it to the rest. The business will help you help the rest of the business. Understand how they need to transform in order to you know how do I. Get some of that I mean that that's something we see very. Very much here, if someone's implementing something, someone will see it in. That wants some of that the ADS. Yeah, child does your business champion. How do you help them? Go on and become a champion within their organization. So you're it is a bouncing act, we a- In a good position that we have both those arms can take time with that yet, but I think other people have a role to play in that too I I don't agree with just the short term sell with a capability that may fail and may not lost. The middle ground of kind of being the internal adviser I think sort of different in some sense, but at the same point, it's a big opportunity. I think a lot of I know. A lot of our subscribers run services or product companies in their selling into the enterprise to be able to be the catalyst that actually gets that smart conversation to happen Scott that kind of centralized conversation that that allows a company to actually mature in in the big picture. That's actually a pretty big cool responsibility. If you're able to help a company that much I think, there's a big win. Win To be had their final note. I'll ought to be briefed on this one, but I want to squeeze it. It in Stephen S is one of our many emerged plus members here and the question is. Is there a market for digital maturity? Itself ease worded it a little bit differently. But you and I have talked about kind of upgrading your enterprise upgrading their capabilities to be able to adopt Ai Stephen saying that maybe not all consultancies have a I-. Chops are not all going to build algorithms, and not all gonNa write python. Is there a market for selling those AI prerequisites in terms of training teams to work together in terms of helping structured digital infrastructure in a new way, etc? Do you think there's a market purely for that or do? Those companies also have to quote unquote due the. One hundred percent that there is again we're in a privileged position Peter EC. We say strategic to execution. I work with the implementation team. My Team Legend has imitation, but we also have strategy. We have the business specialist and you could easily decouple those. We see a lot of projects where. their capabilities. One consultancy firm has done the as is assessment. One has done the then. Up and down the strategy design, another has come in to implement or technology vendor will do the implementation at the end there is absolutely a market for that for the education about a I for having those conversations in upscaling people in how to have a conversation to act as data advisor the as is benchmarking. There is a lot of work to be done in the strategy. I do think if companies are willing to take the time to invest in that I think it's part of the long term strategy to understand. Data maturity a lot in the data transformation that it's the first stage. Where's your data? And what does it look like right now? So there is a role to be played only doing that without necessarily being able to implement. If you can help, understand what's needed to implement. That's great. If you able to do a vendor assessments say like you with the client you put together. The are pay and you help evaluate the respondents, but now I don't think implementation. Capabilities or not? Having them rather are a barrier to work in that space. Cool Awesome, so Stephen. Hopefully, that's a satisfactory answer Scott I appreciate you throwing in that little bonus question at the end era did I wanted to make sure I got this went in before the interview was out, but anyhow I know that's all we have time. Thank you again so much being able to join us here on the podcast. Thank you, Dan. That's all for this episode of the A and business podcast. We did three use. Case episodes Monday Tuesday Wednesday this week. What did you think about that taught me a note on Lincoln Search Dan Fa Gela that G. G. E. L. L. A. on linked in pop me a Lincoln note or send me a request and let me know your thoughts. You like more volume more frequently something listen to every day, or are you just as fine with having two a week or even have a different preference? Let me know bought me a note on Lincoln I'm interested to know. This was a bit of an experiment for me and I. I really would love your genuine feedback for those of you who are actively selling AI products or services in other words. You pay your bills by making the business case. If you're not already in emerged plus subscriber, please do consider This is a resource we've put together for people who are the catalyst people who need to basically get the C. Suite to say yes, not with fancy sales tricks, but by finding the right AI applications. So this is our AI use case library, our Ai Whitepaper library where you can find Roi Information and deep dives into specific use cases as well as our full breakdown of Ai Best Practices so. For Measuring Roi our best articles on adoption and deployment, and these are resources exclusively for plus members, so if you're involved in a services, if you're a consultant, even management consultant working on a strategy checkout emerged, plus it's e. m. e. R. J. Dot, com slash P, one P, plus and then the number one you can learn more about emerged plus there otherwise just be sure to go to emerge dot. Dot Com sign up for the newsletter at the bare minimum. If you're not already subscribed as it stands, so who? That's it for this week? Four episodes hoof I was a lot of recording, but I. Hope you enjoyed it. I look forward to catching you next week. We're GONNA BE DIVING BACK into use cases next Tuesday for our usual Tuesday, use case episode here on the and business podcast.