Analytics Beyond The Boardroom: Activate Your Analytics Superpower To Drive Cultural Change

Dennise Yeh at UXDX Community: Central Europe. Video: https://youtu.be/95VAIreNST4

Readable transcript: edited from the recording's captions for readability (fillers and false starts removed, punctuation and section headings added). Wording is the speaker's own. Timestamps are positions in the video. Names marked [?] could not be verified against the audio.

Introduction and inspiration

[00:00:03] Hello everyone, and welcome to the webinar. My name is Dennise Yeh, head of digital analytics at LeasePlan Digital. Today I would like to share with you how you can activate your inner superpower to drive analytics beyond the boardroom, to drive that cultural change within your organizations. Let's begin.

[00:00:26] Before we talk about the content, I must bore you a little bit about myself. Who am I? Why do I qualify to talk to you about such a topic? It sounds rather controversial, doesn't it? I spent more than 15 years working in various different roles in digital fields, of which nine years I focused on digital analytics. I've lived and worked on three continents; if I put it into a data visualization, it would look like this. Since 2015 I'm living in Europe. Here are some of the brands and the focus I've been working with in my career. Since 2018 I joined LeasePlan Digital, focusing on smart mobility.

[00:01:16] I like to draw my inspiration from my day-to-day and take it to work, and I'm sure, like many of you, we've been watching a lot of Netflix lately. I got my inspiration from Michelle Obama's Netflix documentary Becoming, in which she talked about this: don't worry so much about stats, focus on your story, because the story is yours; use your power. And I surely hope that by sharing my story here, I'm able to help you identify and activate your inner superpower.

From sportswear to car as a service

[00:01:49] In my last positions I have worked with brands with great heritage: adidas, Reebok and now LeasePlan. What do they have in common? Well, they are all more than 60 years old, and they're all operating in more than 32 countries. adidas and Reebok are footwear manufacturers. They manufacture the shoes for sportswear, distributed over the globe for you as potential customers to feel them, to experience them, and if you like them, then you purchase them, you put them on your feet, and there you go, you run and you play your football. That's what the business model is about.

[00:02:34] What about LeasePlan? LeasePlan is a global leading car-as-a-service mobility provider. We have 1.8 million cars in our fleet and we service 130,000 customers over the globe. And you might ask, what is car as a service? I'll explain later. In both positions I worked in digital, and you might be thinking, what is the role of digital then? The way I see it, digital is where we can create a direct relationship with our customers. And why digital? Because digital is where our customers are. We obviously want to be where our customers are. We want to be in a channel where they feel comfortable, for their convenience; therefore, digital.

[00:03:27] And why do we want to be where our customers are? That might be a simple but maybe a complex question: because customers are our starting point. Who are our customers? Our customer segments are three primaries: corporate, small and medium enterprise, and private. And here is an example of our real customers, no joking.

[00:04:00] I promised you earlier that I would explain what the car-as-a-service business model is. Let's say you're interested in getting a car from us. You have an interest to purchase a car or lease a car. From that point onwards, we also provide you leasing or financing options. We also provide insurance. Once you get the car, the car is delivered to you. If you need fuel cards or fuel management, we can do that for you as well. Your car needs maintenance, needs repair, if you get into an accident, or you want to change the tires, we're there for you. And all the way at the end of the customer lifecycle, if you are no longer interested in the car and you want to give it back to our fleet, we're happy to take it so we can resell the car, and maybe get you another car to keep you going.

[00:04:51] This full cycle would take a minimum of two years, but our customers don't care. They just want to go to work, or maybe in this time stay home, but then pick up the kids, go to a restaurant with the wife, and if they go to a restaurant or go somewhere, they want to go home with their car. And maybe on holidays we hope that you will use our services as well. In this whole thing, you can imagine that it generates a lot of data.

Piecing together the data

[00:05:22] What is the role of analytics in LeasePlan? Our role here is to piece together the puzzle of all the data being generated by our customers along their customer journeys. Here are just a few examples. Using that data, we want to build and deploy solutions that suit our customers' needs. How do we do that? Well, we focus on desirability, feasibility and viability, and we use data to validate those points. In the meantime, for our customers, what is the thing that they really want from us?

[00:06:05] Let me give you examples. We developed the click and drive showroom, where our customers can browse, at a time that is convenient for them, through the options for the budget, mileage, whatever they have in mind, in their own time, on their preferred digital devices. This is convenience, and 80% of the process can be done digitally.

[00:06:28] Another solution that we deployed is what we call proactive maintenance. This means that before the car needs to go into the garage for maintenance, our algorithm is able to predict it and prompt an appointment message to our customer for a garage that's near to them. In that way we want to ensure that the customer spends the least effort to make an appointment and spends the least time without mobility, so they can spend more time with their family and make sure that they have their mobility needs met, getting from point A to point B.

[00:07:07] This thinking helped us to stay growth and result driven. It's a very important notion that we want to make sure we're going in the right direction. We know it's hard; therefore results and growth are everything that we keep in mind. This also helped us to avoid going this way, and nobody wants that for our customers.

[00:07:35] Our aspiration obviously is that we want our customers to experience this as smoothly as if they are listening to a world-class orchestra. This analogy basically means the audience is the customers. The conductor is the person or the function making sure that we are deploying the right solution, with the true north in mind, playing the harmonized symphony. And where is the team? The people actually building the solutions: that's the cross-functional team in the middle of the stage, the orchestra.

The DNA of an analytics organization

[00:08:10] It might sound like we have figured out a perfect formula, we nailed it, right? You probably have the impression that we know. The fact is, maybe not. Having the above characteristics doesn't really guarantee that an analytics program will be successful. What I think about the DNA of an analytics organization is critical to ensure we are on the right path: to be part of the organization, to be part of the conversation, and what really makes the most impact, and also the purpose. Having those two characteristics helps us to differentiate the conversation and the mentality: not just focusing on data but really focusing on impact and the purpose.

[00:09:02] And the spirit is: without data, you or I am just a person with an opinion. Also, if you can't measure it, you can't manage it. Well, that's a lot of negative terms in there, but maybe let me say it this way: what gets measured usually gets improved and optimized. So the whole notion of measuring is that you want to exercise influence on the business, and I think that's the key notion of analytics.

[00:09:37] Now let's talk a little bit more in depth. What do I mean by that? If we talk about measuring, that is an analytics focus. Oftentimes when we talk about measuring, we focus on what happened, in the past tense. If we go a little bit more advanced, we talk about why did it happen; we go into the diagnostic field. The next step, as you can imagine, we want to think about what will happen, going into the predictive field. The last mile is how can we make it happen, given a context that we know, but again at the scale that we want it to be, or even at a larger scale. Here are more of the primary analytics focuses, as you can find in a lot of the modern analytics maturity models.

[00:10:31] What I'd like to emphasize here is that this analytics focus actually drastically reduces the human input, and increases the scale and the frequency. So this is the beauty of it: analytics is not just about measuring things with your tape, but how do you empower the organization to reduce the human input, to get to faster, more frequent, larger-scale business decisions. I call this still under the category of business output. You make decisions, and then you want to take actions; it's still under the business output, it's not an outcome yet. The outcome comes at the last mile, under the business results. So this is a rather long process, and this entire process really matters and helps you to see that what gets measured improves, because improvement must show up under results.

Talent and analytics as a product

[00:11:30] In order to do so, as you can imagine, it will require quite a diverse pool of talent and different expertise to fulfill such a vision. To make it simple, I think there are three different skills that we focus on here: business skills, technology skills and analytical skills. If I map them onto different functions in LeasePlan Digital, it looks like this, and these are the roles that actually exist in our current organization, which we're very proud of.

[00:12:07] Let's say that's how the talent pool looks, how the different domain expertise looks. What are we building? Within the analytics portfolio we have products and services, and for the products and services we adopt the software development methodology and thinking. So obviously they need to have a clear purpose and need to have a critical business problem to be solved, while keeping the customer's needs in the center. Yes, you guessed it right: I'm a big fan of sprints and scrum methodology. The reason why I like this is because you take the customer feedback and you're not looking for a perfect solution. The bi-weekly rhythm is really the key, building from MVP towards a better, optimized product and service, and this applies to everything that we do.

[00:13:05] I often also hear people wonder: you build analytics products and services, but if you're not part of the business, you cannot really make this work. Remember I talked about our customers at the beginning? In order to make analytics products and services beneficial for our customers, they must be embedded end to end in the customer journeys. In this case, it's no longer analytics supporting the business; analytics is part of the business, and we work with all the different functions, as you see here. This is a really powerful model for all of us to work together.

[00:13:47] Here is an example of the full-fledged products and services that we offer from the analytics area to the end-to-end customer journeys. The end goal obviously is to get to the result, and we can see the results showing that on our books. I must admit that it's not always easy. It might sound like a walk in the park, but it is not. Why is that the case?

People and culture as the engine

[00:14:21] Well, because remember, we talked about wanting to be impact driven and purpose driven. Impact driven involves change, and that also means involving people. If you are familiar with change theory, it's not about how you make it work, how you make it ready. Before we can make it work, the point is how do you make it last? How do you implement it? In the era that we had one fearless leader and we followed this leader going left or right, it was simple. We're in a much more modern and autonomous environment where we are connected to our colleagues and our customers over the world digitally, so it's very different from this simple one-fearless-leader model.

[00:15:04] How do we really make this work, then, thinking about it under the lens of data-driven and analytics? People and culture. People and culture are the engine of any organization or community. Here is a picture of LeasePlan Digital. You won't be able to see who is the big boss in here, because he is one of us. He is hidden somewhere in the photo; he is also participating in the workshop. And here is a photo of my team, and I'm right here as well. It's those people that made it come about, not me, not the big boss.

[00:15:39] So having that in mind, what is my proposal? If you're used to this organization chart, I think it really just does not represent the work environment, does it? Because your work environment more probably looks like this. You have all the colleagues focused on different areas. The colleague who is really focused on commercial knows everything about commercial, and people actually value this person's opinions, and this person has his own network when it comes to the topic of commercial, the same with operations, the same with marketing. So the organization actually has more influencers, depending on the topic, and it's not limited just to the org chart and our fearless leaders. The point is that we can use those influencers to activate more of the data-driven notion.

Mega, macro and micro influencers

[00:16:39] If you're still not convinced, let me show you what it looks like from an influencer marketing point of view. In influencer marketing there's a theory that talks about three different levels of influencer: mega influencer, macro influencer and micro influencer. Who could be a mega influencer? Beyoncé, 141 million followers. That reach is pretty broad; she definitely belongs to the mega influencer field. A macro influencer could be Mustafa Seven [?], a worldwide famous photographer with 1.6 million followers. Pretty big, but probably more focused on photography or the topics that he photographs; still quite a big reach, but not as big as Beyoncé.

[00:17:28] A micro influencer example would be creeping on Sudan [?], with 130K followers. She is a food stylist and photographer, not as big as Beyoncé or Mustafa, but she probably has quite an engaged community here in the Netherlands, as well as Amsterdam, and that gives her a different level of engagement and reach with her community.

[00:17:56] So if you think about that, going back to the org chart: the leaders help us define the strategy, the goals, the priorities and the results, linking back to our true north. But really it's the people who are working daily, who look like this, helping us to look into the results and the management, to take actions, to take decisions using the data so they can improve and innovate. And among these people, if you are able to identify who the catalysts are, you will be able to deploy more actions for bigger impact. All of that goes back to the true north, the business KPIs and the customer KPIs we're hoping to move. And note that whether they are a mega influencer or a macro influencer doesn't necessarily have to do with their org chart hierarchy. So you could be an influencer yourself as well.

KPI trees, ownership and accountability

[00:18:56] And you said, "Dennise, the theory sounds great, but we often get caught up with who is going to do what." I hear you. That is quite a common problem, a challenge that we have encountered. How do we solve that? Well, this is what we do at LeasePlan: we demystify the data-driven notion, the ownership and the actionability, with KPI trees. Here I'm showing you an example of a business target for customer journey X that has a direct relationship linking to the gross profit. In this case, this business target obviously has a full-fledged KPI tree that looks like this. A lot of details, I understand. We're talking about an end-to-end customer journey; of course it's complex. I'm sure your organization, your business, also has this level of complexity as well.

[00:20:00] Let's move on to the KPI ownership and accountability. If we split between KPI 15.1 and 15.2 using color coding, we can see that KPI 15.1 and below belongs to the marketing department, where the KPI owner of 15.1 is the marketing manager, and his team are the individual KPI owners beneath. For KPI 15.2, the owner is the product owner for customer journey X, and through this product owner and his team, his organization, we further identify who the KPI owners and the KPI groups are.

[00:20:40] What I would like to stress here is that the KPI is not set in stone once, never to be touched anymore. The KPI is something that we look at daily, weekly, monthly, and when the KPI is moving, either negatively or positively, this gives us a clear indication of whether the KPI owner or the group needs to take actions. More importantly, the KPI tree is built in a direct indicator way. What do I mean by that? Let's say KPI 15.2 is the highest in the hierarchy of the product organization. The direct indicator model basically means that if KPI 17.1 goes up 5% while the rest of the KPIs remain flat, KPI 15.2 will also go up by 5%. This demonstrates the impact and contribution that an individual or a group can make towards a higher level of impact and contribution to the business.

[00:21:49] This becomes extremely powerful for analysts, because all of a sudden, for the growth that we have within the customer journey, we know who to talk to in order to influence the decisions and actions. For our performance analyst, here is the function that she will be talking to. For our data management specialist, here are different functions. Our data visualization developers have a different focus, and so do our data engineers. The goal here is to empower the organization to be more data proficient, so we can take decisions and actions to impact the business outcome.

Breaking the echo chamber

[00:22:32] We keep talking about building a community to inspire people, to enable people to take decisions, because we perfectly understand that to be data-driven as an organization, it's not just the analytics job. We want this notion of data proficiency and data literacy to infiltrate the organization, as if the rain is raining down on the land, like this. It is important because it helps us to break down the echo chamber of analytics. What is the echo chamber of analytics? Sometimes you might have analysts and some data scientists talking about how the organization doesn't care to be data-driven, nobody really cares about data, and it's just those people talking about the problems. Yeah, that is the echo chamber, and we need to break the echo chamber.

[00:23:22] You might ask: spend all the effort for what? To help the organization prioritize decision-making and take action faster, more frequently, at a larger scale. Because we know that only by taking actions are we traveling from point A to point B, and that's the most important notion of being data-driven. Empowering and infiltrating the organization is the key to the inner power that we need to activate here. Analytics is both defense and offense, and helps the organization possess the sharpest spear and the most sturdy shield: the unstoppable force and the immovable object. We want to empower the decision-makers on the front line to make decisions and take actions.

You can be José

[00:24:18] Everyone, yourself, myself or colleagues, could be influencers. If you still do not believe me, you might be surprised. Here is an inspiration I would like to share with you. This is an old adidas commercial; the commercial is called José +10. Who are the plus 10? The people here, you can call them football Hall of Famers. You can see the young become [?], you can see Beckenbauer, you can see Kaká, you can see Zidane; they're all in there. And who is José? José is your star influencer. He played football on the ground, and before that he called the shots for those footballers. Obviously we need more Josés. You can be José. The more the merrier.

[00:25:10] To sum up what will keep us busy in the 2020s. First, turn the analytics output into business outcomes. The full cycle only ends with faster decision-making, action taking, and actually yielding measurable business results. Second, no matter what you do within your organization, I'm sure all of you have KPIs. The KPI is not the most important thing; remember to establish the ownership and accountability. This helps you to eliminate the question of who is going to do what. Remember that we eliminate it through KPI ownership and accountability.

[00:25:55] Last but not least, identify your inner power, your colleagues' inner power, to deploy the influencer network to help drive the organization's data proficiency and literacy. You might be pleasantly surprised who the real bosses are. That's what I would like to share with you in this webinar. Thank you for your time and attention, and also thanks to UXDX for hosting this webinar. Let's stay connected on LinkedIn.