In conversation with Ian Shepherd
Ian Shepherd is a CEO and CMO who has held senior roles in a range of world-renowned consumer brands in the last 25 years, including BSkyB, Vodafone, Game, Bensons for Beds, and Odeon & UCI Cinemas. Ian sat down with The Collective by LS to discuss the themes explored in his new book, ‘The Average is Always Wrong’.
During this conversation, Ian leveraged his practical understanding of the power of data and customer insight, delving into how businesses in the luxury and lifestyle space, as well as consumer-facing businesses more widely, can overcome obstacles faced when adopting a ‘data-centric’ approach.
The Collective by LS (TCLS): Tell us, what prompted you to write this book?
Ian Shepherd (IS): I have had a slightly odd career of two halves. I spent the first part in subscription businesses –namely paid television and the mobile sector. Many data-centric disciplines and business models, such as the segmentation model, the predictive model and the rise of AI terminology, started precisely in these subscription businesses.
When I moved into the retail, hospitality and leisure industry, I was confronted by businesses with little data and even less experience of working with data. I experienced two main things. First, businesses making worryingly important
strategic decisions based on skin-deep summary statistics. Second, management teams that grasped the importance of getting under the skin of data and who had made investments to build databases and hire data scientists but saw no real difference.
I wanted to optimise data-centricity in businesses by bringing practical lessons from the early part of my career but from the perspective of a CEO or CMO.
TCLS: It’s interesting to hear that some businesses attempting the pivot to data are struggling with the change. What does this have to do with the average always being wrong?
IS: The phrase has stuck in my head throughout my career and is one that I have often used. My thesis is that when you hear of an average, it is often either the answer to the wrong question or the wrong answer to your question. In truth, many opportunities to turn data into money sit underneath top-line figures.
Real data analytics is not about averages, but about the complicated wiggly lines the granularity of data – scatter charts, machine learning and AI.
Frankly, when you get past the overblown terminology, the application of machine learning techniques to business is about looking for patterns in the data. Where are the pockets of data that look different What do these tell us? This is how we can gain commercially valuable information about groups of customers – who they are, what they want and how we can tailor services to them in a specific way.
TCLS: Thankfully, an increasing number of businesses seem to be alive to this now, but what kind of mistakes do you see business leaders continue to make?
IS: I would split the challenges I see management teams wrestling with into two parts. Firstly, many businesses are not awash with data that they can interrogate. The very best online retailers, for example, are essentially data analytics businesses with shop fronts. In comparison, a high street retailer you can walk into and pay in cash without identifying yourself secures very little data. The first problem many businesses run into, therefore, is where to get data.
The second, more insidious and challenging problem, is the leadership and cultural change required to become a data-centric business. I come across this issue more than anything else, often in businesses that already understand the importance of data, but where actions such as hiring data scientists are not making a difference.
This usually means something more subtle is going wrong – a cultural problem. Being confronted with large data sets can be existentially challenging, particularly for senior management teams, who can perceive this as a threat to their seniority and authority, especially if everyone beneath them is more comfortable handling data. I have seen many instances where senior figures dismiss moves towards data-centricity as a result.
This behaviour is toxic, ensuring that data will not get traction and that nothing will fundamentally change. Many of the conversations I have with CEOs about data business challenges are about people and psychology as much as about technology.
TCLS: So, securing the buy-in of the key stakeholders driving business culture is clearly of the utmost importance. What practical next steps should businesses take once they have decided to be data-centric?
IS: They should consider what the data opportunity might look like and how to transition the business to data-centricity in a united way. Understanding that data has value is good, but you need to know where the data has value and an idea of what difference it will make. For many, the natural place to start is marketing and sales, as data use can drive more sales and because marketing is where the data in a business is usually found, especially in e-commerce. As business leaders, another way to think about opportunities is in terms of where cash is tied up in the business, where the opportunity is and how data might help.
If data does not change the cash flow of your business, it becomes irrelevant.
The second thing to focus on is the cultural change transformation journey. To boil it down to a single point, I would say that fear does not survive in the sunshine. What I encourage leadership teams to do is to make the journey that they are going on explicit and admit that it is a learning curve and quite an intimidating journey. Once you do that, it becomes much easier to cope.
Imposing data-centricity on a business is a hiding to nothing, however, making it a journey the whole business goes on is incredibly powerful.
Want to join The Collective, and contribute to the debate?
Email us at: The.Collective@lewissilkin.com