Strategy. For those of us who work in organisations in the 21st century, it is hard to imagine a world in which the term ‘strategy’ would not be heard. Yet the reality is that it is a relatively new concept for business. This is even more so when the term is applied to data, with a significant number of organisations lacking a data strategy despite it being ubiquitous as the means to conduct business: data is fundamental to drive operational activity, undertake financial transactions, engage with customers, deliver products and services, and operate the internal functions without which an organisation simply could not function.

The English term ‘strategy’ originates from the ancient Greek strategos, meaning the ‘art of troop leader; office of general, command, generalship’. However, it was the Chinese who have often been regarded as the founders of the principle, with The Art of War, attributed to Sun Tzu and dated to the 5th century BCE, acclaimed as the pioneering work on military strategy. Remarkably, it was not until the 18th century that ‘strategy’ was translated into Western vernacular languages when it was used in its military form by Count Guibert in France and Claus von Clausewitz, the famous Prussian general.

The military use recognised strategy as the series of engagements that lead to winning the war, with tactics the activities that take place in the context of an engagement. The business use of strategy and tactics remain intertwined in much the same way today.

It was not until the 1960s that strategy became part of business language (see the timeline in the box), largely through academia finding its way into the growing sphere of management consulting, with strategy becoming a new revenue stream for these organisations who to that point had concentrated on organisational structure to derive income. It also led to consulting firms being formed which were focused on strategy alone – Boston Consulting Group being one which formed in 1963.

Since the 1960s, strategy has evolved but the balance between strategy and tactics remains. Today, strategy is a recognised business discipline in its own right, and there are a myriad of consulting firms offering strategic capabilities across every domain, sector and geographical location. It is surprising, therefore, that so many organisations are still unable to execute strategy effectively.

Henry Mintzberg was one of the first to call out the complexity² of defining a strategy and seeing it through to implementation almost three decades ago. Many had focused on the definition of a strategy, but there seemed to be an almost inherent assumption that the organisation would simply ‘get on’ with implementing it as if that was the easy part, which Mintzberg identified in linking the two. In the meantime, complexity in our organisations has increased dramatically, with multiple channels, globalisation, the velocity of activities and pace of constant change becoming just a few of the things our strategies have to adapt to, comprehend and incorporate.

1.1 DATA IS EVERYWHERE

A similar scenario, in terms of the evolution of awareness and focus within the business world, has taken place over the last 40 years or so with regard to data. The initial explosion of data volumes that arose as technology moved into the workplace and provided us with the means to conduct business on a global stage, message one another frequently, process large data sets in spreadsheets and communicate to our customers and employees at scale took us into a different business environment. Data became accessible to many, systems started to present opportunities for reuse rather than single purpose, and expectations grew about the speed at which decisions could be reached by using computer processing power rather than the limitation of our brains, paper and pen.

The world of data has changed beyond all recognition since the 1990s – it has been my career throughout that period and change has occurred at an unparalleled pace. Today, we take for granted having computer devices all around us – the latest mobile phones are more powerful than the laptop many of us use for daily tasks. Indeed, the smartphone is faster than a 1980s Cray-2 supercomputer and, more remarkably, faster than the computer on board the Orion spaceship NASA is testing for its mission to Mars.³

The world is a smaller place, with the internet in many ways removing geography altogether as a barrier or constraint. Something can happen the other side of the world and within seconds everyone can see it on social media as well as news sites. Through video conferencing, the office is less a fixed focal point and people operate from wherever suits them – as long as there is bandwidth and a willingness to work flexibly, it is possible to conduct business almost anywhere, at any time.

All of this consumes data, generates data and builds a rich landscape of data points that can tell a lot about an individual. Whilst cookies were invented in 1994 to aid with shopping and recording items of interest on the internet, they escalated to be able to build a browsing profile of an individual that became of particular interest to hackers, which alerted authorities to crack down on compliance and has led to a reluctance amongst some to surf the internet without resorting to virtual private network to access sites incognito. This demonstrates how the development of a technology enabler has led to a dramatic increase in data traffic – a website would typically have around 20 cookies,⁴ so in the course of a week the volume of cookies stored would be significant for an active user of the internet, unless there is active blocking or screening taking place – and introduced a whole new security risk that has led to a major industry forming to tackle cyber-security and provide products to mitigate the risk for individuals and organisations alike.

In a relatively short period of time, data volumes have exploded, making it harder to manage effectively and compliantly – the so-called rise of ‘big data’ that was coined in 2005. Multi-channel has often led to multi-systems and platforms, duplicating data and failing to join it up in a way that enables the organisation to understand it, manage it or exploit it. The race to maintain a competitive edge has led to inefficiencies that those organisations that started out as dot.com businesses have not had to wrestle with, such that the levels of service in established organisations can often be woefully behind their competitors. One major UK retailer was recently advertising a 3–5 day delivery time frame as its standard, when competitors such as Amazon were offering same or next day delivery.

In effect, data is now the battleground of every market, every sector, in virtually every place. It is no longer the prerogative of the large organisation to be smarter than those of more limited means. Every organisation has data, the means to be able to manipulate it have become more commoditised through developments such as cloud computing, and a start-up can be nimbler and more targeted than a large corporation that is grappling with legacy technologies – a culture that is still operating in a traditional way and a lead time to make change that is beyond the comprehension of its smaller rivals. If ever there was the time for a return to David defeating Goliath, this is it!

Yet, only a minority of organisations appear to have identified the need for a data strategy and very few have successfully developed and implemented one. If you have identified an interest or responsibility to do something in this sphere it makes you a relatively rare breed. If you are able to pull it off by convincing your organisation of the need for a data strategy, defining it and implementing it successfully, then you truly are in a scarce pool of data strategists.

This book combines practical experience, academic research and input from many other experts in their field to try to guide you through the process of identifying the need for a data strategy and the case for change that it necessitates, determining what it should include, defining the content and then executing it through a clear implementation plan to achieve a successful outcome. It is a guide, as each organisation is different in the sense of maturity and readiness, but is intended to provide sufficient insight for the road that lies before you to enable you to map out your own journey and navigate through the potential pitfalls on the way.

1.2 WHY IS GAINING AGREEMENT TO DEFINE AND EXECUTE A DATA STRATEGY SO DIFFICULT?

The logic for a data strategy might be clear to you – if not, then I am hoping to convince you by the end of this book of its merits! – but this is probably not the case for the vast majority of your colleagues in the organisation.

In 2012 Cynthia Montgomery published a book anyone interested in strategy should know well as a great starting point to understand its purpose – The Strategist.⁵ Montgomery ran the strategy unit at Harvard Business School and turned her insights from her oversubscribed course on strategy into the book. She states:

Some … find it extremely difficult to identify why their companies exist. Accustomed to describing their businesses by the industries they’re in or the products they make, they can’t distinguish them from competitors on anything beyond a superficial level. Nor have they spent much time thinking concretely about where they want their companies to be in ten years and the forces, internal and external, that will get them there.

If leaders aren’t clear about this, imagine the confusion in their businesses three or four levels lower. Yet, people throughout a business – in marketing, production, service, as well as near the top of the organization – must make decisions every day that could and should be based on some shared sense of what the company is trying to be and do. If they disagree about that, or simply don’t understand it, how can they make consistent decisions that move the company forward? Similarly, how can leaders expect customers, providers of capital, or other stakeholders to understand what is really important about their companies if they themselves can’t identify it? This is truly basic – there is no way a business can thrive until these questions are answered.

I have sought to highlight in this book, through many sources, how ineffective senior leaders often are across the world at strategy definition and execution, how frequently such programmes fail and the evidence as to why this happens. When considering what Montgomery has to say, just reflect on the fact that these were senior executives and company owners who had sought out her course and therefore had an appetite to learn. Yet clearly they were unprepared in terms of thought or evidence about strategy.

Bear in mind that Montgomery and others are talking about strategy as a whole, typically focused on corporate strategy, which is an essential component to any organisation – if you don’t know where you’re going, how do you know whether you’re on the right path to get there, you might put it.

Data strategy is even less understood, so the chances of success can be further decreased, simply because you need organisation-wide commitment and buy-in to succeed. Data does not exist in a bubble; it is not the preserve of a function that can fix it for all, detached from touching everyone else. It is core to how you run the organisation, and without a focus on where you are heading, it is going to trip the organisation up at every turn – regulatory compliance; operational effectiveness; financial performance; customer and employee experience; essentially, the efficiency in managing virtually every activity in the organisation.

The key point to make is that you need to regard data as an asset. In the right state, data is one of the most valuable parts of your organisation. But data needs to maintain compliance, to be fit for purpose to avoid some potentially fatal decisions being made and to enable your organisation to function effectively. Then, it is truly an asset.

There are many horror stories of data misuse that have got into the public domain (clearly, far more never make it outside the organisation). IBM has estimated that bad data costs US companies $3.1 trillion a year, equating to 12 per cent of revenue.⁶ I have listed a few examples, just to show how simple it can be to misuse data and reach a conclusion that has major impacts on your organisation:

• The Mars Climate Orbiter, launched in 1999, was run on software, supplied by two different organisations, that failed to convert imperial measurements into metric, with the result that the thrusters fired at the wrong time – 105 miles closer to the planet than intended – which led to the craft disintegrating in the Martian atmosphere. The entire multimillion-dollar investment was lost. Numerous organisations have made the basic error of mixing the two measurement standards with often significant impact.
• The Enron scandal in 2001 was a result of data being provided to shareholders falsifying the true position, and a lack of controls prevented this from being identified.
• In 2012 an error in risk calculation led to the UK West Coast Mainline rail franchise tender process having to be suspended and compensation of £40 million being made to the bidders.
• The UK National Audit Office found that 375,000 people who should have been contacted by a call centre in 2020 to advise on shielding during the coronavirus pandemic could not be reached due to missing or inaccurate phone records. A further 126,000 people were contacted and advised to shield who did not need to do so.

There are many examples of data being at the heart of significant costs being incurred, businesses lost and reputations left in tatters. This is caused by poor data quality and errors that go unchecked through the many processes at work in the organisation encompassing data collection, utilisation and manipulation that underpin how it works. In addition, there are then the increasing scale and number of fines levied for data breaches and data protection failings that are becoming more commonplace. If this is not a cause for concern for your organisation, then it is either oblivious to the risk or has control of what eludes some of the biggest organisations across the world today.

1.3 DATA IS BECOMING READILY ACCESSIBLE

The coronavirus pandemic has brought data to the forefront of public consciousness. The plethora of data gathered has led to a surfeit of information, which has been both beneficial and confusing to navigate. The interpretation of the data has led to the rapid development of vaccines and impressive programmes to inoculate adult populations in many countries. There has been international cooperation and information sharing to enable knowledge of variants of the disease to be identified and traced to provide rapid testing and learning, so there is a continuous process of iteration and improvement in the way nations tackle the pandemic.

Whilst this level of cooperation isn’t necessarily new, it is one of the clearest examples in how data has been used globally to provide information, from an individual and aggregated basis, that has been turned into intelligence and is informing positions that national governments have taken. It is transforming expectations, with the UK government highlighting in its national data strategy⁷ that there is a duty on it to do more, using data for the benefit of society and enabling a more integrated and rewarding experience in engaging with public services, whilst also protecting individuals from harm and treating them fairly, and also, potentially, extending to related private sector services.

Barriers to accessing data are becoming more recognisable as an issue and are being seen as a blocker to enabling the smarter use of data through technology and innovative propositions. Offsetting this is the concern over data privacy, the rights of the individual and the need to hold data, all aspects of an evolving and more clearly defined data protection regulatory landscape. The term ‘responsible’ is often incorporated into governance controls and legislation to try to strike the balance, but of course the challenge is finding an agreed position as to what constitutes ‘responsible’, especially when operating across national boundaries.

The technology landscape, too, is changing as the evolution of cloud computing becomes increasingly the norm for many organisations. The notion of the cloud is a way of describing an ‘off-premise’ solution to storing data, as it is still physically held in a location – often multiple locations – and so the regime in each nation in which the data is held needs to reflect the same safeguards as those countries to which it relates. This can lead to a tricky challenge of identifying backup systems in cloud computing, tracking how resilience impacts on storage, and other issues which need careful consideration and ongoing monitoring. The continuing dependency on maintaining public trust in organisations to manage their data safely and securely is also a major factor. This can be undermined very quickly; it only takes one major incident and the trust can be eroded.

The increasing prevalence of advanced capabilities in organisations, such as artificial intelligence (AI), is very data dependent and also data hungry. These applications require good quality data in large amounts to work to maximum effectiveness, so the investment in, and accessibility of, data is critical for success. This requires progress on data sharing and trust to be established in the first place, used as the basis from which to invest in the quality of the data in order to materialise the benefits of the advanced capabilities.

1.4 HOW DOES A DATA STRATEGY HELP?

By identifying the alignment of data-related activities – from the effective management of data through to its exploitation – you are putting in place a vision for how a critical asset in your organisation is going to support achieving corporate goals. Establishing common objectives in how the organisation will manage and exploit data is an essential step towards ensuring compliance, operational integrity and consistency in what underpins decision making. It provides a framework to enable the organisation to move to managing data as an asset, recognising the need to invest to be able to turn it into something that generates value rather than simply consumes cost. Through the choices made and the focus given in the data strategy, the opportunities that will be available to the organisation to accelerate corporate goals and to realise benefits that might otherwise have been overlooked will be determined.

The vast majority of data in an organisation is not exploited, yet is obtained for some reason, whether historic or still relevant to the present. In itself, this is quite concerning. Regardless of its use, that data needs to be understood and maintained compliantly, and whilst estimates vary, the consensus seems to be that less than one percent of unstructured data is effectively catalogued and exploited in organisations today.⁸ Aside from the potential that may be hidden in plain sight, how compliant is your retention of that data?

This doesn’t just hold true for unstructured data either. Most organisations are regarded as exploiting less than half their structured data,⁹ that which is held in systems and therefore is more accessible.

If you are focused on the goals set out in a corporate strategy, how do you know you are delivering these effectively if you overlook the majority of the data within the organisation? Any use of data is limited to ‘that which we know’ and may be missing real insights into performance, costs or opportunities through the failure to join up the data across the organisation to give a more informed view.

Many organisations start a data strategy from a need to get data into some sort of organised state in which it is feasible to demonstrate compliance. In my opinion, compliance should be a component of a data strategy, not the data strategy in itself. It is referred to in this book as balancing a defensive view with an offensive position, and it rarely works to focus solely on defence.

If this is where you find yourself, then it is likely your organisation has either been caught in the glare of a regulator or has suddenly become aware it may well be in that position soon. It is an opportunity to use compliance to pivot attention in the organisation to data, but I am passionate that this presents a window to expand it into so much more. Whilst you have executive attention, consider how the cost of compliance could also be pitched as the investment opportunity to deliver real value to the organisation – open eyes to the offensive opportunities that are virgin territory and hence a potential gold mine of revenue or other gains to be achieved.

This book explores both defence and offence as strategies. A data strategy should accommodate both – to use a military analogy, there is no point in an all-out attack and leaving your base unguarded. My advice is to seek to operationalise both approaches within your strategy and to seek out the sweet spot arising from the opportunity to devise a data strategy. Over time, the focus will shift, typically towards a more offensive strategy as the elements that form the foundations of good data management practice become embedded into your organisation’s ways of working. There will be a need to revisit these, as over time the discipline will waver and need reaffirming and re-establishing, but the value of a data strategy is most visible through the impact it can make in delivering the corporate strategy and raising awareness and expectations of ‘the art of the possible’.

1.5 THE ROLE OF THIS BOOK

The intention in writing this book was to transfer more than 30 years of experience gained in data and analytics into some practical use for those who are faced with one of the most challenging – but most rewarding, if you get it right! – tasks: defining and executing a data strategy successfully. It is based on the knowledge I have amassed of nearly 20 organisations across a dozen sectors, along with the workshops I have run on this topic. I have seen tremendous change in the scale, opportunity and professionalism of the data and analytics community. It is my goal to use my experience to my utmost to help ensure that the current and next generation of data and analytics leaders are as well informed as possible to enable them to succeed.

I have covered the significant breadth of activity that is required to enable a data strategy to move through an extensive effort from identification, into definition, through execution to releasing benefits to the organisation. There are many different ways to tackle an undertaking of the scale of defining and executing a data strategy, especially in some of the larger organisations. It is a process which I have distilled into ten phases, though it is highly iterative: so do not be concerned if you find yourself oscillating back and forth so long as there is a purpose in so doing. These phases are summarised in Chapter 12: five for definition (positioning; readiness and scope; definition; route map; content, structure and alignment) and five for execution (communication, culture and change readiness; mobilisation and planning; delivery; flexibility; demonstrating value).

My hope is that you are able to use the framework, learn from the content and find a way to implement it within your own organisation. It is often a misconception that it is a technical task, for whilst there is a need to comprehend the technical aspects with sufficient depth of knowledge to lead this process, it is more about culture, stakeholder management, communications, leadership and strong programme management skills. These are often misrepresented as ‘softer’ skills, but as a practitioner I can certainly tell you there is nothing ‘soft’ about being able to marshal some of the biggest challenges anyone could face to drive change in your organisation.

If you believe the data strategy is an exercise to be done and then you move on, then this may not be the book, or the task, for you. This is about dedication, drive, perseverance and commitment to deliver change in an organisation based on a subject which is possibly not well understood. And yet it goes to the heart of the organisation, its people, processes and technology, influencing its ways of working in a way that will probably take you into every function to some degree. If you don’t understand your organisation at the start, you will certainly know it well by the time you deliver the data strategy implementation, and almost certainly will have played a significant role in changing it in ways never comprehended when you embarked on your task.

I have sought to provide some useful reminders at the end of each chapter, primarily as something to reflect on rather than as a shortcut to the answer. Each chapter builds and takes you through the process from identifying the need for a data strategy to executing it in all its glory. My final chapter brings together some of those themes alongside some further observations.

I hope you find the book to be an informative, challenging but instructive guide to take you through the end-to-end process of delivering a data strategy. I have structured it to flow in such a way that I provide my experience and advice at the appropriate stage of the process. Every organisation is different: there will be parts which may not apply to yours and other instances that resonate loudly with what you are facing. However, remember that every organisation has data, and so every organisation should have a data strategy. You are not alone in dealing with this challenge and you are developing a rare skill, as data strategists are a relatively rare breed that will become more in demand in the future.

1 Patrick Dixon, Building a Better Business: The Key to Future Marketing, Management and Motivation. London: Profile Books, 2005.

2 H. Mintzberg, The Rise and Fall of Strategic Planning. Hemel Hempstead: Prentice Hall, 1994.

3 S. Nunez, Your Phone Is Now More Powerful Than Your PC. 2020. https://insights.samsung.com/2020/08/07/your-phone-is-now-more-powerful-than-your-pc-2/.

4 Cookie Checker: Is Your Website GDPR and CCPA Compliant? 2020. https://www.cookiebot.com/en/cookie-checker/.

5 C.A. Montgomery, The Strategist: Be the Leader Your Business Needs. New York: HarperCollins, 2012.

6 In T.C. Redman, Bad Data Costs the U.S. $3 Trillion Per Year. Harvard Business Review, 22 September 2016. https://hbr.org/2016/09/bad-data-costs-the-u-s-3-trillion-per-year.

7 National Data Strategy, GOV.UK. www.gov.uk.

8 L. DalleMule and T.H. Davenport, What’s Your Data Strategy? Harvard Business Review, May–June 2017.

9 L. DalleMule and T.H. Davenport, What’s Your Data Strategy? Harvard Business Review, May–June 2017.