The Innovation Show
Business Experiments with Sarah Spoto and Vincent Ducret
In the latest episode of the Corporate Explorer series, brought to you by Wazoku, we discuss the importance of balancing personal instincts with data and evidence in business decisions. Guests, Product Marketing Manager for Electric Vehicles & Customer Experience with Cadillac, Sarah Spoto and Vincent Ducret from ChangeLogic share their experiences of implementing experimental frameworks in China for General Motors. They emphasize the critical steps of assumption analysis, prioritizing hypotheses, and iterative experimentation, while also addressing challenges in corporate environments, such as maintaining cultural buy-in and celebrating failures as learning opportunities. Sponsored by Wazoku, the episode offers deep dives into innovation management, strategic risk-taking, and the use of connected collective intelligence to drive business success. 00:00 Introduction: The Pitfalls of Instinct-Driven Decisions 00:40 The Role of Data in Corporate Exploration 01:07 Sponsor Message: Wazoku's Innovation Ecosystem 01:56 Incubation and De-risking New Business Ideas 02:19 Meet the Corporate Explorers: Sarah Spoto and Vincent Ducraix 02:50 Sarah Spoto's Journey in Corporate Innovation 04:40 Vincent Ducraix's Background and Experience 06:55 The Business Learning Life Cycle Framework 08:10 The Importance of De-risking in Corporate Ventures 13:04 Challenges and Strategies in Corporate Experimentation 14:33 The Role of Leadership and Team Buy-in 21:08 Case Study: Experimentation in China 30:28 Final Thoughts and Contact Information Find Sarah here: Find Vincent here: Key Takeaways This conversation explores business experimentation using a framework outlined in the Corporate Explorer book. Here are the key takeaways: Challenges of Corporate Innovation: Reliance on past experience can lead to failure in new ventures due to high uncertainties. Traditional methods like surveys might not capture the right data for untested ideas. The Business Experiments Framework: Identify Key Assumptions: List all critical assumptions about your new venture (customer value proposition,problem addressed, etc.). Prioritize Assumptions: Focus on the riskiest assumptions that could derail the project. Design Experiments: Create creative experiments to test these assumptions with real customer data (not just surveys). Collect Learnings: Analyze experiment results to validate or disprove assumptions. Iterate: Use learnings to refine your approach and potentially conduct new experiments on remaining assumptions. Benefits of Business Experiments: Reduces risk by validating assumptions before significant resource investment. Provides data-driven decision making for building the right product for the right customer. Challenges of Implementing Business Experiments: Balancing Speed and De-risking: There's a tension between demonstrating progress and taking the time to properly de-risk the project. Cultural Shift: Organizations need to embrace experimentation and see failures as learning opportunities. Team Buy-in: Both leadership and working-level teams need to understand the value of experimentation. Success Factors: Strong Leadership Support: Having advocates who understand and champion the approach is crucial. Cultural Investment: Educate teams on the process and celebrate failures as learning opportunities. Focus on Learning: Value the insights gained from experiments, even if they disprove assumptions. Example Implementation: Sarah Spoto's experience in China highlights the importance of setting the right incentives and building a cross-functional team for experimentation. Assumptions analysis is a valuable starting point, even if full experimentation isn't implemented. Overall, business experimentation offers a structured approach for de-risking new ventures and making data-driven decisions in the face of uncertainty.
- Duration:
- 31m
- Broadcast on:
- 14 Jul 2024
- Audio Format:
- mp3
There are many examples of how even the most successful entrepreneurs and business managers can fail when they put personal conviction, when they put personal conviction and opinion ahead of data. Andy Grove, Intel's legendary CEO, committed the business to video conferencing equipment in the late 1990s. Jeff Immelt, another storied CEO, bet GE's future on the industrial internet of things. The browser company Mozilla reportedly spent $400 million on a new phone operating system. These are decisions made on instinct that failed. So how does a corporate explorer replace or at least supplement instincts and opinions? With data and experience, with data and evidence to demonstrate whether an idea is worth pursuing or if it requires a pivot or even a shutdown. How does a corporate explorer answer questions that have a major potential to jeopardize the projects, the projects progress and ultimately its future success, if not addressed upfront? Big questions to get through on today's episode of the corporate explorer. Just a reminder that the corporate explorer series is brought to you by Patreon. Wazoku helps large organizations create effective, sustainable innovation ecosystems that accelerate efficiency gains and new value growth and it does this through intelligence, enterprise software that connects and harnesses the power of employees, suppliers, startups, universities and a unique Wazoku crowd of over 700,000 plus global problem solvers, Wazoku calls this connected, collective intelligence and you can find our friends at Wazoku at www.wazoku.com. So today's episode describes how incubation tests unproven assumptions of an idea. Sorry I didn't say that again. Today's episode describes how incubation tests unproven assumptions of an idea for a new business by de-risking each element before committing scarce resource to the project. We have two corporate explorers, one that worked alongside the other to bring a great success to life and it's a great pleasure to welcome the co-authors of the corporate explorer fieldbook and a chapter entitled business experiments de-risking executions and spend through experiments, Sarah Spoto and Van Sonn-Jukre. Welcome to the show. Thank you. Thanks so much for having me. Thank you. It's great to have you guys. Sarah, maybe you'll start by introducing yourself and how you got involved in this chapter and then we'll come to Van Sonn and then we'll get stuck into the chapter. Thanks again for having me here. I'm Sarah Spoto. At the time when this chapter was written I was working in China in Shanghai with General Motors. I was the director of strategy innovation as well as brand strategy for the organization and it was really an incredible opportunity for me. I had been working at the headquarters in Detroit for GM for a number of years and go to a region to really build a startup within this large multinational corporation. Was honestly a dream come true for me. I consider myself an entrepreneur but of course being in corporate, sometimes you don't always get those opportunities to do something truly entrepreneurial and in this case I did and so I'm really proud to say that we had leadership who very much supported our efforts in taking an experimentation approach to how we developed the offerings for this new business model and doing it in conjunction with more traditional methods like market research. I think those complement each other very well. My role there I was actually employee number four on the team so while I have this fancy sounding title I wear a lot of hats and it was really helping to drive innovation and agile methodology and bring this experimentation approach to the business while at the same time also building our brand there as well. Brilliant Sarah and so great to have you and it's great to have somebody who's done the work and has all this car tissue and all the arrows in the back for doing that work as well which really makes it real and Van Son maybe you'll introduce yourself as well and then we'll describe the chapter but also the frameworks that exist in the chapter. It's great pleasure and thanks again for the invitation and so nice to see you again Sarah. So in fact I have a computer engineer background okay and by the way I'm just calling you today from the place where I graduated more than 20 years ago EPFL in Lausanne. So I started really my career as a software developer so I was exposed very early to all those extreme programming a giant way of thinking of working and I worked several years for Sun Microsystems probably some of you might remember this company and then I moved to the other side of the mirror I used to say because I spent 15 years in corporate environments. So when I joined Sarah on this project I was used I will say to the corporate world so I know what might be the challenge, what might be I will say the problems they may face. So I spent 15 years in corporate environments having worked for different departments and the last six seven years I was part of the transformation organization moving a very famous company from business centric to customer centric so really adopting a much more customer centric approach for this company and I have also the opportunity today to teach business transformation and innovation principles in the difference university in San Galand or in Geneva and I joined ChangeLogic two years and a half ago as a consultant to help company to grow beyond their core business. So really more or less I will say helping company like Sarah was working for to explore test and scale new venture and new business and this is how I was I will say working with with Sarah on this very interesting and passionate project for GMPI in China. Brilliant we have the perfect people in the room to get it both sides of the story as well and I thought we'd start by that so Van Son you've taught other people the frameworks but also you've used those frameworks in organizations which is a totally different thing than just teaching them the whole time. So we're going to tee us up for one of the great diagrams that's in this chapter the business learning life cycle and I'll show that on the screen in a moment but just to tee you up you'd say the first impulse for many corporates is to trust their employees experience knowledge and skills to address uncertainties. They have earned this trust by delivering high performance results in the past from the existing businesses for many years however the reality is that rarely an idea survives its first contact with a customer. The uncertainties of an emerging business make your first ideas susceptible to bias meaning that there is a strong correlation between the trust approach and the failure of corporate innovation and then you outline steps to perform iterative experimentation from assumption identification through experiment design and execution to data driven decision making and you use an approach that Sarah used in China with General Motors China premium import and we'll talk about that in a moment but first upon song I'd love if you'd introduce us and I'll show on the screen it's great diagram. Thank you Aiden so in fact one of the challenge of corporates where they are launching new ventures is that they are most of the time entering a ward of uncertainties something that they never explore before and the high risk they can take is just to rely on the past experience to take decisions for something which is completely new for them and this is the big difference between explorations and expectations. Explorations you have probably decades of success where you have fine-tuned everything to work perfectly but usually you cannot use this experience this knowledge to explore new world and this is why you need to adopt this their risking approach that we have illustrated through this loop called business experiments and for this you usually start by stating all the key assumptions I put this is you are making about your new ventures those might be related to the customers you think you will deliver a value proposition it might be related to the problem you think you are addressing as well as to the value proposition itself and maybe the ecosystems you think you need to put in place to deliver the value proposition so you start first by listing establishing all those key hypotheses you are making usually you can say what must be true for my idea to work okay because if this is not true I might be I would say doing the wrong stuff for the wrong people okay so once you have done this one you can move to a steps two which is about prioritizing those assumptions hypothesis because you cannot address everything at the same time will you be able to de risk at one hundred percent of business no okay if you do this in six year you are still there risking I will say an idea but they are very burning risk that you have to tackle as soon as possible because you know that if you are wrong you might probably I will say to move back a few weeks if not months in the past to correct something so this is why you need to prioritize your hypothesis and look looking usually at what I call rats your riskiest assumption to test okay this is I would say the one that are the most dangerous for your project this is where usually sometimes you put the dust below the carpet expecting that the dust will never pop up again don't do this okay look at those one even if this one is putting in danger the project you are working on then once you have identify those riskiest assumption to test this is where the most interesting part starts for me and probably the most creative one is designing experiments how can you invalidate your assumptions by getting real data evidence from your target customers and this is also applicable for b2c and b2b model from your partner as well okay in the b2b models and when I means this is where you need highly creative because most of the time you don't have anything tangible to show to your customers you are still at a very early stage so how can you test with your customers typical willingness to pay willingness to acquire your solutions okay when this solution still does not exist and when I mean you need to be creative because you need to go beyond the traditional way of testing with your customers which are asking them or making a survey okay which is the easiest way I will say to get data from your customers but maybe the easiest way as well to get biased data okay and to not get any proof of what you are really I will say doing if it is right or wrong for your customers once you have done your experiments of course you will collect learnings okay they done and those learnings might be telling you that you are right or wrong at the end it doesn't matter it just gives you I will say the data you need to take decisions and based on those learning then you can decide to go for the next iteration for the next loop where you will look maybe at the second risk assumptions you have to test okay and maybe sometimes you will have collected enough evidence after a few loops that you can move forward with your project okay that for example it's time for you now to start building really your first version of your product like your MVP okay to test it further with your customers but this loop is to remind to the people that the most important in incubation is not about I will say prototyping is about their risking you need to dare risk as much as possible to bring all the data the confidence that you are doing the right thing or the right customer to address the right problems so this is why as long as you don't have enough data evidence to tell you that you are right you need to keep I will say looping it's so difficult though Vansong and Sarah when so Sarah for example you're going to China you have a bias for action you really want to get stuck in you want to show progress and then you have to take a step back and you have to use a diagram like this you're like oh I just want to get I just want to get started and when you have to go through that loop first of all the discipline to go through that loop and then the discipline to perhaps do it a second time it's really hard for a corporate explorer because of this time you know you feel like the sands of time are slipping away all the time and and I'd love to share how you manage that when you're talking back to HQ and say look I gotta go through this process otherwise I'm going to be squandering money for the company or how did you position that yeah it's such a good question and it's a totally valid concern that I think all of your listeners who work in corporate will understand and sympathize with they're always trying to balance de-risking to have that confidence especially if you're building a new organization or leader in that organization as well as showing that you're making progress and moving quickly and sometimes you really have to move quickly to build that momentum in the broader organization right and get that buy-in so I think there's a few different tactics we use to accomplish this I think making sure that you have strong leadership support is really key making sure that you have advocates in your organization who can support you and your different or innovative approach to doing business because it is very different right and the already the business model that you're working on is going to be different in itself and then you add a layer of okay our methodology is totally different as well so make sure that you have the right voices in the right forums to support what you're doing which I'm saying it very simply but it's not simple right so we actually took a very strategic approach to thinking about who we needed to bring on board along with us and and thankfully we were able to do that with our within our organization and the broader organization but that's just one level because the experiments are going to get done by your working level team and in in a lot of cases your team is really lean you might be under resource everybody is doing a lot of things outside of their typical scope and that can be hard to motivate folks to say okay we're going to take an approach that you are not familiar with at all outside of your normal work but we think it's the right thing to do so there's also I think the buy-in that has to happen at the working level as well like the cultural piece of it and giving folks that that psychological safety to see failure as part of this process and that takes a lot of effort and I really I think that's something I definitely want to emphasize on this podcast in particular because maybe you read it in a book and okay great the framework let's follow the framework but there's that other element of that cultural piece that's so important and making sure as a leader as a corporate explorer in your own organization that you're taking the time to get buy-in worth your working level team as well so spend and dedicate that time to educate them on the process they're the ones that are going to make it happen bring them along for it make sure they understand the impact that they're having the power of the frameworks that you are using and then make sure also that you're celebrating the failures as well and I remember the first moment the result of one of our experiments came back working with Fincinency and it was a failed experiment and it was a very celebratory moment for us because we got information it was like oh this is not what we thought and that's great it was actually clear really clear right the experiment allowed us to have that clarity even in our failure and it allowed us to pivot so making sure that you're taking time to pay attention to the cultural aspect as well great point and that failure piece so many people would try to cover up that failure but how you position that and go we saved ourselves millions by not actually going here because we proved it wrong Vanson for you yeah this is one of the key roles of the consultant here exactly and I would like just to emphasize what you just say Aidan this is sometimes very important to show to the management that by not doing something how much money you are saving because this is where sometimes you may have the spark in their eyes and say oh no I got you okay we have spent maybe three weeks to do these experiments but we are saving six months of doing something that nobody needs and by the way you saved me half a million because that was the plan we had okay because usually when you start experimenting people have the feeling that you are slowing down everything you say oh but why are we experimenting let just build it okay and I say yeah that's fine because if you are measured just on delivering something perfect build it deliver it but then if nobody is using it and you are also measuring about the customer adoption you might be in trouble okay so that's why yes you might have to invest a little bit time at the beginning to start understanding how to experiment but as soon as you start doing this one you are saving a lot of time money and resources that you can use on stuff which are demonstrating real progress real data and evidence okay but this is hard at the beginning for your leaders to understand this one because they have been so used to go to some leadership meetings where you just show the way I'm sorry to be brutal but the way you are burning the money you got for your project here you are much more adopting a small step approach where you show progress and you are not measuring the progress in the same way that you are measuring an exploitation project because here you have lots of unknown so you have to also measure differently I will say your progress but showing the way you are wasting you are saving money it's a nice way for some people to get it very quickly these are the conversations that don't happen early like this doesn't happen and it's great Sarah to hear you say that the culture allowed you to even engage with event Vansan and the change logic teams they actually go we're going to do this slowly we're going to go through these steps so that we don't squander money and waste resource and waste our time as well and ultimately get to a failure but if we find those failures or those cracks early that that's actually a huge win that's a very tough chasm to cross for corporate explorers and I've been guilty of this as have so many erodians where we're going if I build something even if it's not successful at least I've built it and I can point to it but that's not what you want to point to so there's a lot in there but I wanted to bring it back a step so you so Sarah I'm just thinking about you as a template for many corporate explorers so you've been given this huge opportunity the first step is then you go okay I need to map this out you had an existing relationship with change logic Vansan becomes your account manager and then do you guys map it together and you kind of go this is how we're going to approach it and then you go for it because there's a diagram that I have from the book that I thought it looks like this was the next step then and I just want to help our audience go because there's lots of little bits in between that we skip when we have these conversations but I really want to help other corporate explorers so they get it so maybe I'll share on the screen this diagram and maybe you'll talk to us because this maps to very much to the framework and this is how you actually stepped into China well it's a great question because I think the concepts is really important you know when I think it's worth actually taking a step back on it because I was fortunate enough to join the team as I mentioned as employee number four and so we were really lean and then we could all really take a strong leadership position and in building the strategic vision for the organization and for us I think that was why we were successful with implementing experimentation because even before we knew who change logic was we are the managing director and the rest of the leadership team we spent a lot of time being really clear on what our objectives were as an organization and I think what helped us be more open to accepting this process of experimentation is that our objectives weren't as more typically focused on get XYZ done but really more focused on the learnings we wanted to generate and so I to simplify it it was really making sure that we had organized the team around the right incentives that then made it possible to even explore something like what we did with change logic and with Vincent and so we didn't explicitly have that relationship or that process in mind I was not familiar with experimentation at all not since taking science classes in in school right I was very familiar with like at a broad and broad level obviously the importance of getting data and or very data centric business and the importance of market research and getting in front of your consumers and that kind of stuff but not experimentation explicitly but I think taking the time to build the right incentives and the right vision early on then let us down this path of thinking about how can we really be successful and it became clear that de-risking was really important and that we needed or that as a leader to team we wanted to look beyond the typical approaches to do Ignat and that's where change logic became involved one of our leadership team members he had a relationship with change logic and so we brought them in but honestly it was mid-stream and so that's why I think I mentioned that cultural piece because even by the time that Vincent came involved the team was growing really quickly and we had people running we had experts doing sales right we had experts doing marketing and they were running down the path of the tasks that they needed to get done and so we introduced this mid-stream and had to really get everybody at that working level on board with us with experimentation so that's kind of how how it happened truthfully it took it did take some time for us to to educate the team to get them on board to build the right group of folks who were going to focus on the experimentation we wanted it to sit very cross-functionally we didn't want this to be siloed with market research experts or marketing experts or commercial experts we wanted everybody from or at least a representative from every discipline as a part of the process so obviously that requires some education as well but once we had lined up those right teams then we were able to work effectively with Vincent and team to start generating experiments it took always takes a bit to get the first few off the ground lots of questions and trial and error and then I think once we did that and we got some in market then that we were able to build momentum and really start to get the data and results and to Vincent's points earlier demonstrate to our leadership the value of this process as a complement to the traditional methods we were also using to de-risk our business so tell us about so the first experiment say for example or maybe it was the one that you proved was wrong the wrong approach so what actually happens and maybe we'll use this diagram on the screen to to map the steps those steps that you took the first was really the assumptions analysis and I think this is so critical it's important not to skip this piece of it and honestly even as a corporate explorer if you are not fully on board with experimentation as a process just start with the assumptions analysis because that alone is going to reveal so much about your biases as an organization and help frame your thinking from the very beginning it's still attractive that I use even in my own work as a marketing professional even if I don't go into fermentation but anyway so we started with the assumptions analysis and really saying what must be true for this business to work and then of course applied that to different offerings that we were exploring and that was not a short process necessarily because again it was cross-functional we wanted to have the input from the right teams we wanted to be robust enough from there we prioritized the assumptions based on some assumptions we could really quickly answer either with existing data or a data that already existed publicly third-party data are results from recent market researcher things like that or somewhere to simply question we could get answered within the organization and then some were true unknowns and that's where we focus the experimentation even building this framework during the process was what happened right so we had what you can the screen here is this nice neat framework but it looked different the first time we were using it and it evolved to fit what I think you make it most effective for our use but yeah so then we were able to you to define the experiment and I think if I can add on this Aiden and Sarah thank you what's on the screen is a great example of one of the experimentation among I will say I don't remember how many were run over the last probably one years and half of this project but that was an experimentation where probably most of the time people would have just I will say ask customers to get a response to the questions in that case we really use like community in China to test I will say people's behaviors and figuring out without I will say asking them if they will rather opt for solution A rather than solution B but they were not knowing that we were really testing them it was made in a way that it was natural for them to get I will say this offer in front of them and select A or B but we were here testing really customer behaviors and this is where experimentation is very challenging for most of the corporate is how can I cross the border between people saying and people doing and this is a good examples where we were testing this idea about vehicle subscription services to see if the model we had in mind where we have multi branded would get preference to a model where you have only cars for the same from the same brand okay and again you can have just I will say question a few people around and say do you prefer to run always car from this brand or you would like to have a portfolio of brands and maybe they will have tell you yes but the problem is that they tell you yes and the day where the offer exists they don't use it okay because what they say is not what they do so here we found a way using community that was existing in China to really test their behaviors and to see to which level they are ready to even subscribe for service which was not yet existing at this stage okay so this framework is helping you structuring your assumptions and turning it into something that you can test measure and you can take decision and decision maybe just accept that you are wrong and that's okay that's a learning you are not failing you are just learning that you are right or you are wrong or you have enough data telling you that you are right sir did you want to add anything or just in terms of like the application of the experiments because we we were in in the middle of the pandemic we only executed our first set of experiments and so we started out with more digital focused experiments and think in China they have of course an incredible ecosystem of digital tools we chat being at the great example of that and to Vincent's point then we could really leverage that for community understanding community behavior but eventually we were able to pivot into experiments in in real life and I think that's really important because it's so easy to stay within your corporate environment stay within your your building and something that change logic really challenge us to do is to get out of the building to get in front of customers because a secondary benefit to doing these experiments is you give your team exposure to customers in a way that they might not typically get in their normal roles and I think those learnings go even beyond the results of the experiment as well fantastic guys for people who want to reach out and find you where is the best place sir you first where's the best place to find you you can find me Sarah's photo at LinkedIn same for me linked in vasson du crev in san jukre you will find me multiple ways of saying advance on but it's vasson du crev which is the the best way and it's been a pleasure having the authors of the corporate explorer field book and before I finish it for I thank our guests I want to thank our sponsor wasoku who helps large organizations create effective sustainable innovation ecosystems that accelerate efficiency gains in new value growth and does so through intelligent enterprise software that connects and harnesses the powers of employees supplier startups universities and the unique wazuku crowd of problem solvers of 700 000 plus what azuku calls connected collective intelligence and you can find wazuku at www.wazuku.com for now authors of the corporate explorer field book vasson du crev and sarah spoto thank you for joining us thank you for inviting us