EY’s Mark Powell On How To Use Data To Take Your Company To The Next Level

The proper use of Data — data about team performance, data about customers, or data about the competition, can be a sort of force multiplier. It has the potential to dramatically help a business to scale. But sadly, many businesses have data but don’t know how to properly leverage it. What exactly is useful data? How can you properly utilize data? How can data help a business grow? To address this, we are talking to business leaders who can share stories from their experience about “How To Effectively Leverage Data To Take Your Company To The Next Level”. As part of this series, we had the pleasure of interviewing Mark Powell.

Mark Powell is a business writer, consultant and entrepreneur. Over 30 years, Mark has held Partner roles at Cap Gemini, Kearney, KPMG, Aon and Accenture. Currently, he is Lead Partner for EY’s UK Data and Analytics Practice. He focuses on the application of data, analytics and AI to drive business transformation. Mark is the author of The Fifth Phase: An Insight-Driven Approach to Business Transformation and four other business books.

Thank you so much for joining us in this interview series. Before we dive in, our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?

I have had a few different careers along the way — started out as a professional photographer. That did not go as well as hoped so I joined the Royal Navy (the obvious thing to do — not!), then ended up doing a PhD and becoming (briefly) an economist. I quickly got bored doing that and then ended up as a Strategy and Transformation consultant for 30 years working mainly in the energy and utilities sector. Then a few years ago, I started exploring what you could do with data and analytics to transform organizations, and this became my new mission — to help individuals and organizations better understand how to leverage data and analytics. Despite all the hype around AI and “mutant algorithms”, the actual reality is that few organizations are anywhere near leveraging the full power of data and analytics.

It has been said that sometimes our mistakes can be our greatest teachers. Can you share a story about a humorous mistake you made when you were first starting and the lesson you learned from that?

Like most people, I have made many mistakes along the way — and strangely enough, they never seemed to be that funny at the time. My biggest lesson early on came from a project I had worked on for many weeks. I believed I had found a brilliant solution to a really difficult problem and that the client would be simply delighted. What I hadn’t fully understood is that having a great answer, or a solution is only half the problem. I hadn’t done enough work to build a relationship with the client so that they had faith and trust in me and could believe that what I proposed was the right way forward. It was a hard lesson to learn at the time, but ultimately, it’s relationships, engagement, trust and faith that drive things forward; without those things no solution, no matter how brilliant, will ever get implemented.

Leadership often entails making difficult decisions or hard choices between two apparently good paths. Can you share a story with us about a hard decision or choice you had to make as a leader?

The hardest choices I have had to make have always been between choosing the path I think is the right one, when the organization at large wants to go in a different direction. I have always chosen the path I thought was the right one and the best one, but when you do this and the organization at large does not agree with you, it can be very painful. Sometimes it has been at a great cost to myself personally. I have never been a very good ‘corporate soldier’, but I have never regretted going in the direction I thought was right, even if sometimes it was difficult and painful.

Are you working on any new, exciting projects now? How do you think that might help people?

I am on a mission — pure and simple. I believe that there is a growing problem with fear surrounding AI and associated technologies that is simply out of all proportion to the reality. In fact, it goes beyond this. The world and most organizations are not taking the right approach to leverage the power of data and analytics to drive better outcomes for themselves, their employees, their customers and the world at large. We have been obsessed with data for the sake of data and have still not yet fully delivered on the huge benefits that data and analytics can bring. AI has the power to absolutely supercharge what data and analytics can deliver in terms of new and better outcomes. This is my project; this is my mission.

My main project at the moment seems to be talking about my new book — THE FIFTH PHASE. So far there has been a lot of interest and I am being asked to speak to groups about it which is great. I love to engage with executives around the ideas in the book and I really enjoy lecturing and speaking at events.

You are a successful business leader. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?

Team Orientation — you can’t do anything without the right team around you. I have been fortunate to work with an amazing team over the past few years. My main role is to get the right team in place, empower them to do what they need to do, and do everything I can to direct, support, protect and encourage them. Too many organizations adopt an approach of focusing mainly on the performance of the individual. I believe you win as a team, and you lose as a team — and if you adopt that approach you almost always win. I am very people and team oriented, and this has helped me to put together great teams of people who deliver results.

Positive Thinking — I am a very positive person by nature, I look at what is going well and focus on the good things. I have boundless energy and enthusiasm and that can really help, especially when you are trying to do new things that no one has really done before.

The Vision Thing — I would never pretend to be the best person at ‘the detail’. I can do the detail (as an economist you have to), but It’s not my natural place to be. I have always been good at seeing the big picture, having a clear vision and strategy for what I wanted to do and being able to articulate it in a way that has got my team behind it.

Thank you for all that. Let’s now turn to the main focus of our discussion about empowering organizations to be more “data-driven.” For the benefit of our readers, can you help explain what it looks like to use data to make decisions?

Firstly, I would have to say that I don’t really like the term “data-driven” as I think it drives the wrong mindset. As I point out in my book, this mindset has led to large amounts of money being invested in large data projects that have, for the most part, failed to drive business value. That’s not to say that using data for business intelligence is not important, it is, but it’s more important to move beyond using data that shows you where you have been and to leverage insights from data that can show you new directions to go in. This is the core of the message in THE FIFTH PHASE — that data has limited value on its own, it’s by focusing on the articulation and understanding of what new insights can open real value and then looking for the data you need to unlock value. Using data to make better decisions is important, but leveraging data to drive new insights can be much more transformational.

Based on your experience. which companies can most benefit from tools that empower data collaboration?

Pretty much every company in all sectors can benefit from data collaboration. Governments can be a large winner here due to the interconnected nature of policy and public services, and governments can potentially deliver across all parts of the public sector. Most organizations could also benefit from sharing data with peers and sometimes even with competitors. The challenge is that most organizations are very protective of their own data and spend little time exploring the value that could come from sharing data with others.

Can you share some examples of how data analytics and data collaboration can help to improve operations, processes, and customer experiences? We’d love to hear some stories if possible.

The UK government’s National Situation Centre is a great example. It was built during the COVID pandemic to enable a much faster and quicker response to crisis situations. COVID highlighted just how badly prepared we were to deal with a major crisis. By bringing together over 1000 data sets across government and also outside of the public sector, the Situation Centre can now enable the UK to respond to crises 100 times faster than it could before. At the start, many observers didn’t think it would be possible to get so much data shared across government, but the reality is that, as long as you work with them to understand the value that their data can help generate when linked with other data, most departments are willing to share and collaborate (https://www.bbc.co.uk/news/technology-59651706).

Another great example comes from a large consumer products company I worked with. They had millions of customers and had a massive online business, but there were still several million other potential customers that they simply did not know and could not access. By using machine learning and linking large numbers of data sets, including live social media feeds, they were able to actively segment and target these potential new customers, almost in real-time, to improve the effectiveness of their marketing, drive online sales and turn these potential customers into new, loyal customers.

From your vantage point, has the shift toward becoming more data-driven been challenging for some teams or organizations? What are the challenges? How can organizations solve these challenges?

My view is that the concept of being ‘data-driven’ is the wrong one. The idea that data has intrinsic value is a fallacy that has driven thousands of organizations to spend billions of dollars on ‘data programmes’ which many surveys from Gartner and others have shown nearly always fail to deliver any significant return on investment.

My view is that you have to think in terms of being ‘insight-driven, and data-enabled’. Unless you are clear on what outcomes you are looking to drive and able to then link the data sets to enable you to find new insights to drive new outcomes, you are just going to spend (and waste) huge amounts of money on data management and the associated technology. I see data and analytics as the next concept in business transformation — what I call the FIFTH PHASE of business transformation — rather than as simply a set of tools and technologies. The other challenge you get is that driving the outcomes from insights and data almost always requires a significant amount of change to happen in organizations to enable the outcomes to be delivered. In my experience, this is the biggest challenge. The degree of organizational inertia and resistance to change often makes it very difficult to actually deliver all the benefits that could come from delivering new insights from data.

Ok. Thank you. Here is the primary question of our discussion. Based on your experience and success, what are “Five Ways a Company Can Effectively Leverage Data to Take It To The Next Level”?

1. Be value-driven — stop thinking about data, start focusing on the insights that could drive better outcomes and then look for/acquire the data that will drive the insights. My journey started with an old friend who was the CFO of a water utility company. They had played around with analytics but had not achieved any meaningful results. We sat down with the board for two days and re-imagined the company as a series of linked optimization problems with associated insights that would drive improvement in each key area. This “value map” identified a number of opportunities they had not imagined, the key one being whether it was possible to identify underground leaks on a water network. Turns out you can if you link a number of data sets together. Underground leaks are a massive issue in the water sector and by taking a value-driven approach we unlocked a huge transformational opportunity.
2. Think transformation not tooling — neither the insights nor the data that underpins them is likely to drive successful outcomes unless you are prepared to transform processes, functions and structures to enable the insights to deliver the benefits; to drive the change and take no prisoners along the way. To go back to the water company example, I developed the leakage solution for a couple of clients, but it was never fully implemented. In the end, they built some tools which helped the existing teams do things a little better, but that was all. They were not prepared to change the processes and the structures and the working processes to enable the analytics to deliver the full potential benefits. It was a sobering lesson. As I said earlier, it doesn’t matter if you can develop great solutions that have huge benefits if organizational inertia stops you from executing.
3. Not all data is created equal — it’s vital to develop a much better understanding of the linked value of data so that you can have a better understanding of what data can actually deliver outcomes when linked to other data. In the above example, when I first started to look at the area of leakage it was not clear how you would do it. In the end, what enabled the solution to be developed was the linkage of real-time pressure and flow data on the network to historic work management records. The work management records were a historic data set recording work done to install, replace or fix aspects of the network. The company placed no value on what was just a set of job sheets BUT… when you could link this data set to the pressure and flow data you could then identify leaks before you saw them. They were going to throw the work management records away. This is a perfect example of the power of AI to interrogate large data sets to find patterns and linkages where none were previously thought to exist.
4. Drive from the business side, not the technology side — it’s time to re-imagine the roles of CIO, CTO etc. and how much more closely they need to be aligned to the strategy and transformation process from a business perspective. Consider developing the role of a CHIEF INSIGHT OFFICER. One client I was working with had the role of Chief Data Officer (CDO). Over time they realized that they needed to create a second CDO role that was not focused on the management and utilization of data, but on engaging with the business to better understand how data could be used more effectively to drive outcomes. It was still focused on data-up from a mindset perspective but was a great start in terms of changing the way the organization was looking at the link between data and outcomes.
5. Educate, Educate, Educate — when I talk at conferences and business schools about AI and data and analytics I am always surprised by how little most senior business executives actually know about AI and analytics. They don’t need to be able to write algorithms or build data maps, but it’s important they understand what data and analytics can do. Organizations need to educate all of their executives to be more knowledgeable about how data and analytics can be used from a business and transformational perspective. I am seeing a growing interest in this. For example, I am speaking at a development conference for over 50 senior executives from both the public and private sectors in a couple of weeks. The topic is very much about understanding how AI and data can be used to transform organizations. This one is unusual as I usually get asked to talk about the dangers of AI and why it’s going to destroy the world!

Based on your experience, how do you think the needs for data might evolve and change over the next five years?

We are going to see exponentially increasing amounts of data being generated. The key issue will be in working out how to focus on the right data which can drive better outcomes, whatever they may be. We are going to have to get much better at linking data to insights to drive positive outcomes. There will be a growing focus on issues about how personal data is used and the potential for AI to drive negative outcomes, but we will need to keep a focus on the benefits. For example, my own first instinct would be that I do not really want my health data being given away or sold, but if we all allowed that to happen, it might enable us to more specifically target treatments which could save the lives of millions of people. If I was going to be one of the people who enabled that then, quite frankly, you can have my data. As data continues to grow, we will need to have a more grown-up and sophisticated conversation about the trade-offs between digital sovereignty and outcomes we could potentially drive that could be of huge benefit to mankind.

Thank you for your great insights, We are nearly done. You are a person of significant influence. If you could inspire a movement that would bring the most amount of good to the most amount of people, what would that be?

To see AI and the associated world of data not as a threat, but as the basis for the next evolution of our organizations and the world in general. We can’t stop it, and we must be careful and manage and regulate it, but most importantly we have to embrace it (in the right way) for the benefit of all mankind.

How can our readers further follow your work?

You can see my new book THE FIFTH PHASE (https://www.businessmole.com/how-data-can-help-drive-profitability-for-businesses-a-new-book-explains/)

You can also find more about my other books and a large number of my previously published articles at www.powellgifford.com

Thank you so much for sharing these important insights. We wish you continued success and good health!