Assessment of data-driven innovation by the Supervisory Board: does the innovation lead to customer value?


Companies share the universal ambition to become more data-driven. Access to data and knowledge about how it can be used are fundamental building blocks for innovation. The companies that are currently making quick progress in developing new products and services are aware of the importance of bringing together data and knowledge from various disciplines. As a part of their data-strategy, companies are investing substantially in technologies and the people who implement and embed them. But for a transformation to be truly successful, the role of the Supervisory Board (SB) is crucial. The Supervisory Board oversees the policy adopted by an organization’s management and is responsible for the organization’s continuity. It is up to them to assess whether the decisions made by the executive board are in line with the general course that the organization strives to follow. In this threefold of articles, we will ask a series of key questions that help guide Supervisory Boards to optimally monitor data-driven innovation. The first part deals with the key question: does the innovation lead to customer value? 

Lifetime value 

In the digital world, a company’s value is determined by the lifetime value of its customer base. Customer spendingcosts per acquisition and cost to serve are several decisive factors, but none of them are as important as customer loyalty, which influences them all. For every decision made, organizations should therefore test whether the decision demonstrably contributes to increasing customer loyalty, by improving the customer experience, for instance, and thus increasing customer value. To assess whether a decision will contribute to increased customer value, you will have to approach your business model from the customer’s perspective.  

Data-driven pizza pickup 

Domino’s Pizza is a great example of a company that has taken this lesson to heart. The company attaches great value to customer journeys and its performance at the various touchpoints on these journeys. Customer behavior data and the company’s performance are the source of valuable innovations. An example of such an innovation is their ‘just in time’ pizza baking: pizzas leaving the oven at the exact moment the customer arrives to pick them up. This will improve the customer experience (indirectly boosting customer loyalty), because pizzas are at their best when they are fresh from the oven. The process used to predict the customer’s arrival time is entirely data-driven: the time at which a pizza is put into the oven, for example, depends on customer location data and traffic on the route to the pizzeria.  

Data-driven fitting room 

Another example comes from the world of e-commerce. Fashion retailers typically have to deal with high return rates: as much as 42% of all products sold by Wehkamp are returned. This not only puts pressure on results, but demands as well additional efforts from the customer, which negatively influences customer loyalty. In 2012, Wehkamp’s online competitor Asos had a return rate of 26%. Considering this rate to be too high, Asos decided to launch a digital catwalk, showing customers how clothes fit on real people, helping them to make more informed decisions.

The next step involved augmented reality, a tool showing how a particular item of clothing looks on different body types. The primary aim of this data-driven equivalent to fitting rooms is to improve the customer experience and thereby increase customer loyalty. From the comfort of their own home, visitors to the e-retail platform can now ‘try on’ items of clothing online, allowing them to make better decisions. This, in turn, will reduce the total number of returns, which is both cheaper for the e-retailer and better for the environment. 

Supervisory Boards that aim to stimulate data-driven innovation have to focus on customer value in the business model and assess investments driven by data and analytics based on the extent to which they contribute to the customer experience. This, however, is just one of the three elements that Supervisory Boards in data-driven organizations should assess. In the following articles in the series, we will discuss the importance decisions and policy for the long term, and the importance of having the right personnel.


Edited article in English.

First published in Dutch on Management Impact:

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Frans van Helden and Hans Spaan
Frans is Managing Consultant at ORTEC. With several years of experience in consulting at ORTEC and his mathematical background, he combines an open and fresh mind with thorough knowledge of algorithmic optimization, analytics and applications in various business areas. Hans is Director Data Science at ORTEC and supervisory board member. He has profound experience in business transformation, business restructuring and strategy formulation. He has a Master's degree in Economics from Amsterdam VU University and participated in the governance program from Nyenrode Business University.

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