Episode 64 Transcript

Banoo: Hi, everyone. I'm Banoo, and welcome back. Today, I'm joined by Eisha Armstrong. You'll see that this is my second recording in 2024. The first one was with Greg Daines. We tackled some of the previous topics we've tackled before, but with nuance and challenge.

With Greg, we delved into whether a customer experience is really what drives retention, and we argued that it is not.It's actually being able to measure value and show results to the customers.

Today, we are tackling a topic with Eisha that we've, again, done before around productizing your services, but I think you'll really enjoy the topic because it's a completely new angle around what the impact of artificial intelligence is, and we'll leave you with some tool sets around what things to avoid or think about as you're looking to productize service offerings.

We are very happy to have Eisha join us.She is the co- founder and executive chairman of Vecteris, which is a subscription - based advisory company supporting B2B service companies to productize their offerings.Eisha is also a strategist in the B2B SaaS space, has a wealth of knowledge in regards to blending technology with strategic business planning, and has an interesting perspective on the evolving landscape of professional services.

She's also the author of the book Productize, which is a guide to turning professional services into scalable products. Stay tuned because we'll be offering some of her books at the end, and you'll find out how you can get access to them.

Welcome, Eisha, after that very long introduction.Welcome to our show.

Eisha: Thank you, Banoo. I really am excited to be here today.

Banoo: Fantastic. Why don't we start with you telling us a little bit about yourself? Tell us about Vecteris and how it came to be. By the way, am I pronouncing that correctly? Vecteris, I think. Right?

Eisha: We pronounce it Vecteris. But it’s a made-up word.

Banoo: Yes, how Vecteris came about being and your experience and the kind of services you provide to your customers.

Eisha: Sure. Well, we have to go back about 25 years, when I started my career working for an organization that really pioneered the productization of management consulting. They provided benchmarking data, best practices research, and executive education, all in a subscription model that was designed to reduce the amount of money that companies had to spend on management consulting.

I started my career in a product development role, then moved into product management and, eventually, product leadership.That's where I spent the bulk of my career before confounding Vecteris in 2018 with one of my former colleagues, because we saw an opportunity in the market that more and more B2B service companies that had provided custom services now wanted to figure out how to standardize, automate, and scale those services so that they could grow faster.

That was really our hypothesis when we launched the company six and a half years ago.Since then, we've worked with about 100 professional services companies around the globe, primarily mid-market, large enterprise professional services firms across all different sectors, marketing agencies, accounting, legal, consulting, architecture firms, you name it, guiding and supporting their productization journeys.

Banoo: That's awesome. I've got to tell you that just the fact that we met and discussed what you do opened my eyes to the fact that I've always thought about a product manager as something that's in a SaaS software provider. But to have product managers in the context of service and management consulting and other industries, it was great. I know you have a wealth of knowledge just by discussing what that rule is for it to be effective in a service organization and what they can do. But I digress. We'll get to that, maybe at another time.

But for today, I know that in preparation, you've put out a number of white papers, and obviously, you have your book and a new one coming, I think. I read multiple of your white papers, but in the white paper titled Generative AI, which we will, by the way, provide a link to in the show notes so that the audience can refer to it as well, you speak to recent research that was done on the impact of artificial intelligence on professional services.

I'm going to actually read this section out of the white paper because I thought the information and statistics were very informative. You say in there that the research was looking at estimates of time and labor acts across 17 different industries and found that of all industries, professional services are the most vulnerable to disruption from generative AI. Over 41% of existing work can be automated using generative AI. This includes not only software developers using tools like GitHub and Copilot but also professional services across legal, management consulting, accounting, architecture, engineering, and marketing using generative AI to improve the speed and quality of research analysis and the creation of a large part of their core knowledge work.

That’s all on your white paper.But it was shocking to me that 41 % of the work in an industry that is dependent on its people and their knowledge would be automated.What are some of the ways that you are seeing AI reshape the PS industry?

Eisha: I'm so glad you brought that up, Banoo. What’s even more shocking is that when I share that statistic, which labor economists use by looking at time studies and activities to come up with that estimate, the companies that I'm working with say they think that number is low. I was talking to the head of product at one large professional services organization. He said their software developers are now using generative AI to create 85% of their code base. An architecture firm told me they've got this new proprietary software that they've entered into a JV that can do 50% of the work that an architectural engineer used to do.

What we're seeing here is technology that is different from other types of automation that we've seen in the past because now, with AI, what it can do is actually make inferences and judgments based on pattern recognition.It's not just allowing us to capture and categorize knowledge more effectively; it's helping us make better decisions, or decisions that only humans could previously make using that information.I do think that the headlines that talk about professional services being the last industry to be disrupted by technology are over.I think those days are over and that AI will disrupt a good portion of professional services.I don't think I'm using hyperbole again, based on the conversations I'm having with leaders at other ProServ firms.

Banoo: That's amazing. Again, in the white paper, you do reference that, obviously, with this change, service leaders have to fundamentally rethink how they create value. I talked about the other podcast that we did around value, and being able to show results is really critical to repeat business. Based on that, what are some of the biggest pressures and opportunities that you're seeing for these service leaders that have to look for ways to change and adapt?

Eisha: I'll start with the pressures. Obviously, with this new technology, if you're not starting to experiment and actively use it at your firm, you risk being disrupted by competitors who are using it and can therefore do things more efficiently and at a lower cost.

That disruption, I think, is very real.I think this is actually, though, good news, because what I hear from a lot of ProServ leaders is that labor continues to be a sticky part of their business, that they have low retention rates, and that they can't find enough qualified professionals to do work. If this is a real opportunity to maybe take away some of that labor pressure, it could be a really good thing.

I think the other pressure that professional services firms are facing is a decline in customer loyalty.If you go back in time, people used to go with the same professional services provider year after year because of relationships.

But now procuring professional services is becoming more professionalized, and the procurement department is getting involved.That means that looking more closely at pricing and the structure of service agreements, that's putting downward pressure on margins, and it means that we need to find new ways to compete, not just on price but perhaps new solutions and services.

That gets to the opportunity side, which is anytime there's something as big and disruptive as what we're seeing right now with AI, it also means there's a huge potential for opportunity to develop new solution offerings.

Banoo: You specifically referenced four categories for PS firms to be able to leverage and incorporate AI to become more productive. Can you take us through each of those areas and their application?

Eisha: Sure, happy to. The first one is efficiency, or what we like to call automating the mundane, and that's the one that's getting the most attention right now. That's writing 85% of the code base using GitHub's Copilot or automating low-level tasks, whether it's in accounting audits, legal discovery, copy creation, or things like that.

Certainly some of the larger firms that have access to early access programs from the tech providers have already made some big splashes in terms of announcements on how they're using generative AI to be more efficient. You see things like Deloitte talking about their DARTbot, Marsh & McLennan talking about their LenAI, or things like that. Those are all things that help professional services workers do their jobs faster. It could be about doing research faster, analyzing, creating content, or anything like that. That's the first category, again, automating the mundane and getting more efficient.

The second one is knowledge work quality.If you're able to automate some of the more mundane tasks, it frees your professionals up to spend more time doing complex analysis and thinking for clients, and it also helps free up more time to understand client needs and aspirations, build relationships, and do other things that are really, if you think about it, uniquely human and should be areas where people get more job satisfaction.

One leader recently shared with me that the most common motivator for professionals in their working lives is to deliver high - quality advice to their clients.AI actually makes this possible not only by giving us more time but also by giving us more information to do better analyses and make better recommendations.That's the second category: improving the knowledge work quality.

The third one is around workflow, using AI to perhaps decrease the amount of time that we spend in meetings or trying to figure out weaknesses in our own business models.The fourth one is what I'm most excited about, and that is new growth opportunities. This is where firms realize that AI allows them to solve new problems for customers that they couldn't previously solve, either by creating or white - labeling AI tools to use with their customers or by helping their clients understand how to use the AI tools that are already out there.

Banoo: I love it. I bring it back to the whole value and results piece. All of these, I think, bring value to the consultants. I'm a consultant, and I live for the challenge of providing even more value to my customers. By taking some of the mundane out and giving me the information that is easily accessible to make my analysis richer, it brings value to me as a consultant and as an employee, but also to the customer in terms of their investment.

It's exciting because I think it can also be very scary. When you look at statistics like 40% or 50% automation, you think, Oh, well, where's the job of the consultant going to go ? Where it's going to go is that it's just going to become richer, and it's going to enable them to make richer and more valuable results for their customers.

I love that.It's exciting. It's extremely exciting.But with that comes a lot of change management considerations, I would imagine.If you're making that shift, there is a lot to consider and drive to make sure that change is effective and that you're driving adoption.I know you referenced six considerations to effectively manage change.Can you walk us through what those six are and why you think they're important?

Eisha: I'm so glad you brought that up because that is one of the things that leaders who've made significant investments recently in AI tools are now concerned about, which is how do we get the level of adoption to make these technology investments really worthwhile and then see this growth that we're hoping to see? I'm really glad you brought that up.

The first one in the six - part change management handbook is workforce transformation.You're right. Roles are going to change. New skills will be needed, and there may be some existing roles and skills that become less important or need to be restructured. For example, business domain knowledge to check and edit the quality of work created by generative AI will become more important. Administrative roles will probably become less important, as we've continued to see.

But honestly, I think we're not going to know, probably for another 18 to 24 months. What specific new skills will we require? We do know that new behaviors are needed, so we need people who are really interested in experimenting, who will get in there and just start playing with the technology to learn it, so they can learn quickly and they're able to think more broadly about what the potentials are and not come at it from a place of fear.We may not know all the skills yet, but we do have a good sense of what behaviors we need to see in our workforce.

Workforce transformation is the first one.The second one is culture change.As you mentioned, this does require professional services firms to think differently about how they create value and what behaviors they value.In the past, a lot of professional services firms really valued knowing the answer and providing near - perfect deliverables to clients, but things like knowing the answer or having a perfectionist tendency can really keep a lot of organizations from experimenting with technology and new solution ideas.We need to create more tech - friendly, product - friendly cultures in our ProServ firms that prize learning, collaboration, speed, and things like that.

The third big change in the change management playbook is go - to - market changes.Right now, one of the most frequently asked questions I'm getting from organizations that are running hard after AI is how to manage changes in pricing. For example, does it make sense to migrate to flat-fee pricing or value-based pricing as our billable hours are now decreasing because we're using generative AI to do some of the work ?

But the generative AI costs more money, so the bill rate should go up because that needs to be reflected.There are a lot of really interesting questions around that, and I think the most important thing is to focus the conversation with clients when you're having conversations about pricing and how you're using Gen AI, to your point, on the value that's created. So we're trying to get away from how we're solving the problem and focus more on what the value of the problem is.

The fourth component of the change management playbook, again, gets to managing client expectations.Beyond pricing, we do need to be having discussions about how we’re ensuring deliverable quality and accuracy and how we’re protecting sensitive data and information.That’s table stakes and really cannot be skipped as part of this.

The fifth one, again, back to clients, is co - designing and co - developing with our clients.As we're thinking, especially about that fourth category of how we use AI to generate new service opportunities and new service lines, we want to be talking to our clients and understanding how they are starting to think about it. What are some of the problems that they wish they could solve that perhaps technology, if we apply it in the right way, can help solve for them?

The last components of the change management playbook are performance measures and rewards.Are we still focusing on billable hours and utilization rates ? Or are we starting to focus on margin ? If we're using technology more, our margins should be improving for our projects, and I'm seeing some really innovative ProServ firms take emphasis off of top - line revenue and instead put it on project margin, which I think is great.

We also want to be talking about, again, those behaviors that we want to see.Are people actively learning ? Are they moving quickly ? Are they collaborating, embracing the technology, and embracing intelligent failure ? Again, those are all attributes that we want to see in our professionals, and we'll have to reward those if we want people to change.

Banoo: Every one of these topics can have its own podcast series. But I love the fact that you’ve made workforce transformation number one. I don’t know if that was intentional in terms of priority, but to me, that’s such a key component. To be able to sit back and redefine what your job descriptions and requirements are for specific positions just because the world has evolved and what you’re embarking on next requires a different set of skill sets, so at least as you’re looking for new talent to account for that change in your requirements, that’s such a critical component.

But every one of these, too, like the performance measure and rewards, is another really important reason to rethink what you’re rewarding.Is it still the same basis of measurement ? I love them, and maybe we’ll come back and dive into each one.

But as companies, then, as professional services organizations, are taking on looking at productizing and product offerings and then looking at how artificial intelligence and other technology are doing that digital transformation and seeing how they can drive more efficiency and therefore value, it’s tough.They’ve got change management that they’ve got to think about.It’s a huge undertaking, and there are some mistakes that are typically made.

What are some of the pit holes, things that they should watch out for, and mistakes to avoid ? You’ve seen them many times before.

Eisha: Unfortunately, they're pretty predictable, which is why we spend a large part of the book, Productize, outlining what we call the seven deadly mistakes of productization. I won't go into all of them, but I'll talk about some of my favorite ones.

The first one is developing products or solutions that don't solve an urgent or expensive customer problem. Sometimes we see this a lot with new technology like generative AI. We get so excited about the solution and the technology that we forget to ask: Does the customer really need this? What problem does it solve? Is this a problem that they're willing to pay to solve, or would it just be a nice - to - have problem to solve ?

This is where we try to work with companies to teach them the fundamentals of design thinking to really understand what the pain points are that customers have, what the root causes of those pain points are, and then design a product or a solution after they're very clear on what the customer needs.

But it breaks my heart when I go into an organization where they spent all this money developing this new solution and no one's buying it. It's because nobody wants it.Nobody needs it.Maybe just one client asked for it.

Banoo: You didn’t do market analysis in a sense.

Eisha: That's a big one that I like to talk about. The other one, which I think is especially relevant to professional services firms that are productizing, is letting this fear of cannibalization of service revenue get in the way of the success of the product. Typically, if we're selling a product alongside a service, it's probably at a lower price point than the service. There can be an irrational fear that a customer is only going to choose one; they're not going to choose both, and they're going to choose the lower-priced thing.

First of all, that typically does not happen, and second, there are ways to mitigate that by either making sure your products complement your services or competing with them.Alternatively, if you plan to develop products that could potentially compete with your services, consider targeting a different market segment, such as one that is more price - sensitive.There are some really easy ways to mitigate the risk of cannibalization.

But again, I see a lot of companies develop great products where there is a market need, and then they fall flat.They don't sell because they sabotage. The sales force or the delivery team sabotages it because the price point isn't the same.The top - line revenue potential is not the same, even though the margin is so much better.

Banoo: Again, it comes back to measurement and reward as well, in terms of how you're rewarding your sales team and your consultants for selling those products.

Eisha: Absolutely.

Banoo: I really enjoyed the topic. I do hope we'll have another opportunity to continue the discussion. But are there any other thoughts you want to leave with the audience? I know you have another book coming out. We will be providing an opportunity for the listeners to ask for the Productize book, but tell us a little bit about your book that's coming up and how it will be a continuation of Productize.

Eisha: This spring, we'll be launching a new book that's called Launch Boldly. It's all about the go-to-market motions that a professional services firm needs to develop—the capabilities, the strategy—if they're going to successfully bring productized services or pure products, products as a service, alongside their services because they are very different selling motions and marketing motions. That's coming out this spring. It'll be called Launch Boldly.

I think the last thing I'll say, just taking it back to generative AI, which is getting all the attention right now, but productization in general, is that if we're thinking about it just in terms of efficiency, then we're missing the whole opportunity. We're really underselling the potential of technology to not only make our jobs as professionals more enjoyable but to really create entirely new opportunities for how we serve our clients, create value, and grow.

Banoo: I love that. I know that in your white papers as well, you provide a number of examples that demonstrate that there is data that can be pulled by the customer versus a consultant interacting with it. Maybe you should change your model. That becomes a subscription pool, which is still a revenue stream but allows the customer to take advantage of that data that they can easily access through your technology.

There are a lot of great ideas and concepts in your white papers as well.Again, we'll provide links to that. But let me go to the last question. I wanted to ask you if you can tell us about a mentor, someone who's been impactful to where you are today, career - wise, personally, et cetera.

Eisha: I love to talk about Professor Amy Edmondson at Harvard Business School, not only because of her personal impact on me but also because of the research that she's put out in the world. She's the one who really developed this idea around psychological safety and how important it is for innovation, which again is a key part of successful productization, technology, and development.

She also just came out with a new book that I love called Right Kind of Wrong.It's all about how to design intelligent experiments in our organizations so that we can quickly learn whether we're innovating or trying to apply new technology like AI, but do so in a disciplined fashion so we learn the right things and can move on.

Banoo: That's great. I love it. Thank you again for making the time and joining us. If the audience would like to read Eisha's book, Productize, we're doing a giveaway to the first ten listeners that click the link in the show notes. It's a great guide for any professional services firm looking to deliver highly customized services, new product development, and commercialization that are typically outside of their core skill processes and mindsets.

Thank you, Eisha, for joining us.

Eisha: It's my pleasure, Banoo. Thanks for having me.

Banoo: Of course. As always, thank you for listening to the show. If you have any follow-up questions for Eisha or myself, please feel free to email them to podcast@kantata.com, and we would love to answer them. Thanks again. Have a great day.

Brent: If you enjoyed this podcast, let us know by giving the show a five - star review on your favorite podcast platform and leaving a comment.If you haven't already subscribed to the show, you could do so anywhere you get podcasts on any podcast app. To learn more about the power of Kantata’s purpose-built technology, go to kantata.com. Thanks again for listening.