The previous chapter provided context on why you might embark on creating a data strategy, along with some of the key pointers to consider to ensure its success. The rest of the book will provide more detail on how you build on this, guiding you through the key considerations in developing the data strategy before you switch into implementation.

One of the challenges with developing a data strategy, particularly if this is the first time the organisation will have had one, is determining the scope. There are a number of reasons why an organisation embarks on developing a data strategy – a senior executive may have read of the benefits such a strategy has brought to other organisations, or recently joined from an organisation where a data strategy was in place and seen to have been of value; there may be an increased focus on data, whether due to compliance or opportunities having been identified to exploit it; or you may have been hired specifically to bring your experience in data or analytics into the organisation and therefore want to start with defining a data strategy. Of course, these are only a few reasons why a data strategy might be seen to be needed, but they give a sense of the diverse ways you might find your organisation seeking to embark on defining a data strategy for the first time.

Those organisations that have previously had a data strategy may be coming at this anew, determining whether there is a need to refresh what is in place or identifying that the data strategy hasn’t delivered what was expected. This is not unusual as so many strategies fail to reach implementation, or stall at an early stage. Sometimes they fall into disrepute and it takes time for the organisation to feel it can embark on devising a strategy once more. In such cases, it is always useful to learn from past mistakes, but evidence shows that most strategies fail due to an inability to follow through into execution.

There are also organisations that simply do not recognise the strategy gap – they work in an operationally focused way, dealing with what lies ahead of them but failing to see what is a little way off but certainly heading their way. My analogy for this is being prepared for the next hurdle but failing to recognise it is a race involving ten to be navigated (as in the 110 metres hurdles in athletics) and falling over by the third one. There is a need for a strategy if you are to pace the stride to meet every hurdle in a pattern which suggests prior preparation and meticulous planning. Unsurprisingly, such organisations often find themselves in an endless cycle of restructuring, realigning and redefining their purpose and resource needs through a lack of strategy and planning.

There have been significant fines levied for breaches of regulations. Citigroup was fined £43.9 million in 2019 by the Bank of England’s Prudential Regulation Authority for failings in its governance of regulatory reporting between 2014 and 2018.² Goldman Sachs and UBS have been fined £34.3 million³ and £28 million⁴ respectively for misreporting transactions. Perhaps most eye-watering in scale, Standard Chartered was fined $1.1 billion following allegations of bad anti-money-laundering practices and breaching sanctions by various American agencies and the UK’s Financial Conduct Authority (FCA).⁵ All of these had one common theme – poor data management practices that undermined the ability to conform to regulations.

Whatever the reason for your organisation to have determined that it needs a data strategy, the key is to have clarity on the scope of the data strategy and an awareness of what the organisation believes it requires, allied to an understanding of what the evidence suggests is needed. This is an important step to defining the scope of the data strategy; unless there is agreement from the outset then there is a high likelihood of failure due to neither party being clear on what a successful outcome looks like.

This chapter explores how scope is critical to developing a successful data strategy and what you need to ascertain to be sure you have clarity on scope as well as the reasoning behind the development of the data strategy.

3.1 WHAT IS YOUR GOAL IN DEVELOPING A DATA STRATEGY? THE IMPORTANCE OF CONTEXT

The data strategy needs to be carefully positioned within the organisation to ensure it has the profile to push the organisation towards being data-driven, and so that it is clearly visible how the data strategy is a critical enabler of all the other strategies across the organisation. As has been mentioned already, data is a common factor in the delivery of most activities, even if the organisation itself hasn’t fully appreciated this to be the case; whether verbal, documented, captured in a system or tacit knowledge within the organisation, all of these form data and need a strategy to be able to provide cohesion, direction and purpose.

The counter to this perspective, of course, is that the organisation has operated effectively without a data strategy, so what difference will it make? There is a strong argument to say that if an organisation is not open to the concept of having a data strategy, then culturally it is probably a risk that even the most perfectly crafted data strategy will fail to make it through implementation, and therefore it is a futile exercise to devise one. However, I think this rational perspective is flawed unless it is explored further – let me explain.

If an organisation has never had a data strategy, then a resistance to having one is probably based on misconceptions: either a data strategy is seen to be irrelevant as the organisation has never had one, or seen the need for devising one; or resistance is based upon a perceived negative experience within the organisation or a previous experience elsewhere that senior executives have had. This may not even be specifically related to data – it may be a broader resistance to investing time in strategy. As this book will illustrate, strategy development and exploitation are littered with more failures than successes, and many senior executives are not effective in both the strategy definition and execution arena.

It is important to be able to surface these issues as the more you understand the rationale behind the resistance, the more you will be able to navigate a path to provide reassurance that you have listened, learnt and intend to act in a way that avoids the pitfalls put to you. Chapter 6 covers the importance of storytelling, but it is key to understand your stakeholders, their concerns and experiences, in order to build a compelling message that they will get behind.

If you are tasked with devising what should be in the data strategy, or have been given the task of writing one without any steer whatsoever, then do conduct some research within the organisation before determining the content. It will be critical to have people on board, and so consulting widely – canvassing opinion as to what issues people see, what constraints they have to operate within, how they could be more effective or efficient if only the right data of the appropriate quality was available – and investigating initiatives already under way which could be incorporated into the data strategy is key to making the end product recognisable to your audience such that they can align to it and help you deliver it. The context of the data strategy needs to be grounded in what your colleagues recognise as barriers or constraints to be both deliverable and also likely to succeed in driving change within the organisation.

Does a data strategy have a dependency upon an overall strategy for the organisation being in place? Whilst I would argue that a data strategy needs to align to the corporate strategy, if your organisation does not have a corporate strategy, or at least something clearly documented as such, then I would suggest there is still a compelling case to have a data strategy. This may seem contrary to the rationale I have set out elsewhere in this book, but let me illustrate through describing some of the corporate risks that a lack of a coherent approach to the management and exploitation of data can subject an organisation to.

In an environment in which data compliance and regulation is omnipresent, especially for organisations operating across borders or in mature markets such as the European Union, the minimum requirement is to be able to demonstrate that data management is compliant. To do this requires an understanding of the range of data sources within an organisation, how these are controlled, and how maintenance and retention routines are applied. These are foundation elements of a data strategy, and as such they mark the first steps to producing a data strategy.

The challenge of operating across borders that do not have clear guidance on how this is to be managed, nor reciprocal agreements in place, is perhaps becoming a more pressing issue. For instance, EU law is very clear on the risks of data being managed outside its jurisdiction due to different regimes, regulations and standards at play. Data containment – the physical constraints on where data is hosted geographically (including back-ups and other risks of data leakage) – is therefore critical for some organisations, as they need to be able to evidence no risk of data leakage across geographies despite being global enterprises. This tends to lead to constraints on how organisations might choose to work and, in an era in which cloud technology is becoming much more prevalent, rigour having to be applied to show data cannot escape via back-ups, test environments or other ways in which data could move outside of prescribed geographies. Once again, fines may be levied for transgressing data containment.

I would suggest that, for most organisations, it is well worth expanding on a review of data compliance (which all organisations should have undertaken to assure legal and regulatory controls are in place) to recognise how the data is utilised and exploited, and to propose streamlining data sources where duplication occurs and to reduce rekeying of data. It is then only a short step further to devise a data strategy, which in turn provides a prompt to the wider organisation to think about what it is seeking to achieve, a reversal of approach to prompt corporate strategic thought based upon the potential opportunities to exploit data.

3.2 READINESS AND MATURITY OF THE ORGANISATION

The key to any successful strategy implementation is to understand the starting point in your organisation. Some organisations will be familiar with the concept of strategic planning and thinking, and may even have a highly structured process in how strategies are defined and approved within the organisation. This may not, however, be the same thing as being effective in deployment, and it is imperative to identify how successful the organisation has been in translating its current strategy – whether at a corporate level or divisional/functional level – into practice, embedding change into the organisation.

By contrast, there are organisations that are less structured at strategic thinking and work instead on a more operational basis, running from year to year in setting goals and defining targets. In certain instances such an approach can be a commendable one, for example in the crisis of rapid descent in a recession, where decisions need to be made quickly in a rapidly changing environment. However, these tend to be short-lived as the impact of such approaches is usually cost-driven and highly focused on retrenching to core activities, and are not sustainable for an organisation looking to thrive.

Alongside the readiness of the organisation to embark on a data strategy, there is also a question regarding its maturity to be able to do so effectively. This can best be explored and quantified using an assessment of the data maturity of the organisation, and Chapter 6 explores several models.

As highlighted above, a data strategy should, ideally, align to a corporate strategy. Therefore, the first challenge is to assess (a) whether the latter exists; (b) whether it is actively being implemented; and (c) how easily your intended data strategy can align to it. You should also find those responsible for defining and implementing the corporate strategy, and in a number of organisations these may be two distinct groups of people, possibly in completely different functions.

Let’s work through these options in turn.

3.2.1 Lack of a corporate strategy, or failure to execute it effectively

If the organisation does not have a clear corporate strategy it may tell you a lot about the readiness of the organisation to embrace your plan to create and implement a data strategy. In some instances, it may be a case of having to approach the problem with an innovative solution, or alternatively being prepared to find senior stakeholders who are willing to support (ideally sponsor) why a data strategy makes sense for the organisation and be your champion at the top table.

If there seems to be little hope to engender the concept of embracing strategy into your organisation, and the maturity of the organisation is such that there is little understanding of why a data strategy should be the starting point for a change of direction, then look at alternative ways to tackle the problem. For instance, your organisation is likely to have some formal processes around risk management and mitigation strategies and, whether from a compliance angle or simply to minimise risk, tackling data issues will almost certainly assist and therefore gain support from the relevant executive owner. In addition, a data strategy is likely to have many audiences, but don’t forget that those who are most likely to be the authors of it are also beneficiaries.

At its simplest level, a data strategy is a vision for where you want to be that helps the organisation achieve its overall goals more efficiently and effectively. As well as a number of key inputs required from the wider organisation there are a number which are self-driven and therefore can be instigated with minimal external input. For instance, most organisations are riddled with Excel spreadsheets containing data either taken from source systems or created/manipulated locally to add to the chaotic data landscape (‘Excel – the Japanese knotweed of data’, as my former colleague Godfrey Morgan used to say). Simply reviewing the key systems in the organisation to identify where data resides and cataloguing it is the starting point of a coherent approach to master data management, providing clarity on which sources of data are to be used (the master data), defining the metadata to underpin a common understanding of that data, and taking the first step to a data quality programme to improve quality and hence reliability.

Does a data strategy touch other teams, outside a data and analytics function? Yes, of course it does, but as a small project to drive greater coherence and compliance – as there is a fundamental principle here about being on the right side of the law, whether the General Data Protection Regulation (GDPR) or similar – it typically makes it easier to get buy-in from the likes of the architecture team in the IT function, legal professionals (or wherever accountability for compliance resides) and even the end users themselves, who may be relieved to be released from the burden of maintaining the Excel data sets that need regular feeds and maintenance. If it is possible to put a cost to all of this then it may appeal to the finance function, and often a chief financial officer (CFO) or finance director is a great ally if there are cost savings that can be achieved, compliance or regulatory fines that can be avoided or corporate risk that can be averted – after all, reputational damage can extend to limiting the careers of those serving on executive boards if they have failed to fulfil legal obligations in such situations.

Starting out on a data strategy without revealing it as a strategy may seem an odd approach to endorse, but in reality, the notion of a ‘strategy’ can sometimes slow progress rather than focus attention on the direction to be taken and forging a common set of goals. I have taken such an approach in several organisations, determining that the organisation’s appetite for a strategy or highly structured process to get a strategy endorsed would thwart the progress it was intended to make. There is no harm in sharing the data strategy at a later point, especially as the organisation starts to see the value being realised in the approach you are taking and becomes curious as to whether there is a ‘bigger plan’, with colleagues looking to you because you seem to have an idea as to what the next project should be.

There are, of course, other areas that are liable to be in the data strategy that could be a good place to start to mobilise: for instance, resolving duplication and enhancing consistency in management reporting is a productive place where improvements can be made through greater control and governance. However, getting the data right has such profound benefits for wider activities it is often a good starting point. The current environment within the organisation, issues it faces, starting point for a data strategy to unfold and the ease to find willing volunteers are all likely to influence where opportunities lie.

If there is the potential to benefit from a senior stakeholder sponsoring your efforts to introduce a data strategy then I would always recommend pursuing that option. The key is to find the connection – what can you deliver that would benefit that stakeholder to enable them to spread, based on a practical example, the benefit to be achieved in the wider organisation if it were to similarly adopt the approach. It would be wise to guide your sponsor to where low-hanging fruit might be found, to be able to identify another area where there is either something that could be easily resolved or a blocker removed. This could even take the form of a two-pronged approach, in which your sponsor works at the board level to influence, whilst you work at levels below to get commitment in advance of any positive intent shown by the new business function or division.

The impact a committed sponsor can have is clear. It projects the benefits of a data strategy amongst a peer group with a level of authority you are likely to lack, simply due to the fact your sponsor will be a regular attendee on the board and known to their colleagues. The invitation you might get to address the board will always have more impact if it is set up by the sponsor, otherwise you are effectively ‘cold calling’ the board with something you may be passionate about but, in the short space of time you are given to do your pitch, may not be top of mind for those around the board table. Even the most sceptical board may give your sponsor some leeway to show the potential, along the lines of ‘you’re clearly enthused by the possibilities of this, even if we can’t see it, so feel free to pursue on that project you’ve outlined where you see it having benefits’. By contrast, you may instead get a ‘thanks, but it’s not our priority just now’.

It should go without saying that you have to deliver for the credibility of your sponsor to remain intact. Do not overpromise and under-deliver, and ensure the activity you undertake is time bound so you are able to demonstrate progress. Although the data strategy may be intended for a period of years, if this is your first foray into delivering any of its content into the organisation be mindful you are being judged in weeks, not years. I will discuss adopting an Agile approach in Chapter 4, but remember to structure your first project into rapid phases so you can keep your sponsor engaged with clear signs of progress and, ideally, deliverables that amount to a real change that can, ideally, be quantified or, at worst, recognised.

Consider the feasibility of success in those early initiatives you are embarking on, as it is important to get a degree of momentum. Within the approach of PDCA enshrined in Agile, reflect on the attainability of the plan and the value it will deliver. There is little to be gained from a perfectly executed plan that is seen to deliver little, no matter how well it is done or how important it may be as a supporting activity to those higher-profile things to come later. Whilst it may sound a bit fatalistic, in reality your first three months will start to form opinions in the mind of your sponsor and other senior stakeholders; by six months the die will be cast and views will be shared amongst the group. Do not find you are failing to demonstrate meaningful progress. Communication is absolutely key, and I have devoted Chapter 7 to this topic to underline the importance of getting communication working for you in managing your stakeholders.

In pitching the rationale and compelling reasons for embarking on a data strategy to a potential sponsor in an organisation unfamiliar with the concept of having strategies – especially for a data strategy, since data is probably not ‘owned’ at an executive level and so lacks coherence in how it is managed in the organisation – it’s probably best to start with a more modest goal. You probably need a series of interlocking projects, a programme, as the way to get started. This way, it keeps the vision, sets a number of deliverables as the goal, but focuses heavily on shorter-term objectives to be met to be regarded as a success. Once there is sufficient interest garnered in the path being followed, the concept of the data strategy can be introduced as the longer-term vision.

I have listed below a number of ways you could be embarking on a data strategy for the wrong reasons, and destined to fail. I’ve done so to try to illustrate the pitfalls of these, should you find yourself in this situation, so you can determine whether any of these apply to you and what it might mean. Through understanding the pitfalls, it may help you reorientate the positioning to a place which is more likely to lead to a successful outcome.

3.2.1.1 Strategy in name only

There are many organisations that invest time and effort in developing a strategy only for it to fail to make it to implementation – it becomes shelfware. The strategy may have been partly implemented, not as a strategic implementation, but simply because it made good sense to do so, and you should guard against finding fragments of the strategy and concluding it must have been implemented. I suggest that if you cannot draw a clear link between the strategy as you have discovered it and a coherent implementation, then it is reasonable to put it down to a coincidental link rather than a structured implementation programme.

If this situation describes your organisation, then you need to guard against falling into the same trap.

3.2.1.2 Strategy is owned by the strategy team

In some organisations the commitment to strategy is such that it has its own team, or even function. This might suggest that such an organisation is a strong advocate of defining and implementing strategy, but there is a common trap that occurs in such a situation, which I shall call the theorists dilemma. Often, the strategy team has been formed with the best of intentions, with the senior executives within the organisation being aware that there is a need for a strategy but not having the skills or the time to define one. The answer? To recruit and develop a strategy team to lead this important activity. The problem? It has instantly created a siloed approach in which strategy is a stand-alone function in the organisation.

The intent is fine but the execution has divorced it from the very people who need to define and implement the strategy and have the skin in the game to both make it realistic and enable it to be held to account. The strategy team sees its remit to devise the strategy; implementation is done elsewhere. The chasm grows, and hence the strategy becomes a theoretical construct that has divorced itself from the day-to-day activities of the organisation.

Does this mean that every organisation with a strategy team is doomed to fail? Clearly the answer is no, but the risk is high. The strategy team has to ensure it is not seen to be a theory team, divorced from the ‘real world’, and must be able to bridge the gap into implementation. It can do this by engaging the wider organisation every step of the way, facilitating the organisation to define the strategy, or seconding and rotating staff from across the organisation to spread a greater awareness of what purpose the strategy serves. Linking in with a recognised and effective governance group, such as a portfolio management group, within the organisation will also help provide the traction and visibility to the wider stakeholder network. Any or all of these approaches can be beneficial in bringing the strategy expertise closer to the organisation and making strategy implementation seamless from devising the strategy.

What does this mean for the data strategy? The approaches outlined above to overcome the strategy function being seen to be siloed are just as valid in the approach to defining the data strategy. Data permeates every part of the organisation, so it is essential that all are included to some degree in the construction and approval of the data strategy. The most common failures with data strategies are a lack of engagement, with too many people within the organisation being totally unaware the organisation even has a data strategy. In some cases, this includes staff within the data and analytics teams, who you might have thought would have been involved or consulted to some degree!

The next chapter talks in more detail about how to ensure engagement in defining and implementing the data strategy in your organisation, so I will merely state here that you can’t engage enough.

3.2.1.3 Strategy is for an external audience

Some organisations are expected to map out a vision and some high-level objectives to satisfy external interests, whether these be shareholders or regulators. If the strategy process is heavily focused on meeting that expectation, it is a good indicator that the organisation is doing this because of external pressure rather than because an internal driver has set the direction. This isn’t always the case, and in more enlightened organisations the benefit of setting a clear strategy makes the provision of the view to be shared with shareholders or regulators a much simpler exercise.

The challenge in being driven by the external expectation is that it urges a strong focus on meeting what is needed to satisfy that audience. Inevitably this is a particular view of the organisation, whether aligned to realising shareholder value or achieving/retaining compliance, and as such it does not provide an integrated view of the organisation to enable it to be used as a blueprint and then translated into an implementation plan. Data may be seen to be important as part of this exercise – certainly the focus on GDPR (and similar regulations in other jurisdictions) has led to an element of the data strategy related to compliance given an airing, though this may be a light touch given that many organisations would have been ill-prepared for the advent of GDPR, especially with unstructured data.

A data strategy is usually a key enabler for an organisation to enable value to be gained from its data, encompassing the whole lifecycle from capture to utilisation whilst doing so in a compliant manner. Any focus which is predominantly for an external audience is likely to be limited in scope and therefore of little use to anyone trying to promote the concept of a data strategy. If a strategy is seen within the organisation as ‘something we do for others’, then the likelihood is that this is not going to be fertile ground for the author of a data strategy.

In such cases, the approach described earlier, operating more covertly to deliver the data strategy via a series of small projects and hence focusing on the implementation as opposed to promoting the concept of a data strategy, may be your best route to making progress. Alternatively, if the external audience has a significant impact, there is the potential to use this to your advantage in pitching the strategy in such a way that it commits the organisation to something more than a minimalist solution to the immediate problem. For instance, if there are risks such as the potential for a serious data breach or a health and safety issue, then there could be the opportunity to go beyond remediation to identify a broader, more proactive approach.

3.2.1.4 Strategy has little credibility due to implementation failures

I have often said to those faced with defining a data strategy, ‘Wait till you get to the implementation, if you think this part is hard!’ I don’t say this to diminish the challenge of getting a data strategy defined and approved; however, it is true that many strategies fail not because of their inherent weakness but because of the inability of the organisation to implement it successfully. This topic is discussed in more depth in Chapter 8.

If you are working in an organisation which is seen to be great on ideas but lacking the ability to execute them effectively, then this category is probably for you. The best strategy can be undermined by poor implementation, so I stress that every strategy needs to be defined with implementation in mind. If you are not thinking about how to implement it at every step of the way of the strategy definition process, then you are setting yourself up to fail. Even if you are not going to be part of the implementation team, why put the effort in to define the strategy if you cannot see a clear path to how it will be executed?

So how do you avoid being yet another statistic in the failed strategy count? The challenge is to learn from other failed attempts to implement a strategy and avoid the same pitfalls. However, many organisations don’t like to publicise their failings or even conduct the sort of post-implementation or lessons learnt reviews that shed light on where things went wrong (I know of at least one organisation that dropped the term ‘learnt’ and instead called it ‘lessons observed’, given the same mistakes would still be repeated). Also, in all too many organisations, any lessons captured are stored away and never see the light of day; it is a tick-box exercise to conclude a process rather than one to facilitate improvement in future activities.

The best way to try to avoid such failure is to engage, engage, engage! Don’t develop your data strategy in a vacuum: instead try to be as wide and all-encompassing as you can, and do your preparation in advance. Anticipate that you will receive a negative or, at best, lukewarm reception from some people in your organisation, especially amongst those you need to engage, influence and get involved, and have strategies in your mind as to how you will overcome this perception based upon experiencing past failures. Indeed, some of those with such experience may have been in your shoes, trying to lead change in the organisation: they may be really useful to learn from as you start on your own journey.

Chapter 4 talks about this in more detail, but in short, and as so often in life generally, the more preparatory work is done, the greater the likelihood of success.

3.2.2 Aligning to the corporate strategy

The organisation has a corporate strategy and is in the process of delivering against it, and you have been tasked with devising a data strategy. Sounds great, so what could possibly go wrong? Well, there are a number of potential issues which might scupper your brief to deliver a data strategy. In fact, you may be about to bring into sharp focus why the implementation of the corporate strategy isn’t going as well as hoped, or may even be about to undershoot against expectation.

The corporate strategy sets out the blueprint of what the organisation is seeking to achieve over a given period, its key deliverables or programmes, and targets to achieve. Underpinning the strategy is an implementation plan which has distilled this into a series of activities and assigned responsibility and accountability across the organisation. The external impacts have been assessed as best as can be achieved in the absence of a crystal ball, and some assumptions about competitors, customers and your own capabilities have been integrated to give a rounded picture. This would be ideal if there wasn’t a very big assumption built into much of the strategy – the accessibility, accuracy and therefore the reliance to be placed upon the data.

The data strategy should be developed on the basis of the corporate strategy, as its goal is to enable the corporate strategy be delivered. If there are inconsistencies between the corporate strategy and data strategy these need to be addressed, so it is wise to engage those who are the architects and owners of the corporate strategy from the outset to develop the data strategy to be complementary. As soon as there are any points which seem to be at odds with the corporate strategy these should be explored and worked through.

If there is a compelling reason to revise the corporate strategy based upon something which has subsequently come to light in the development of the data strategy that looks like an opportunity that the organisation may wish to pursue, then this should be possible, and most importantly, needs to feed into the implementation plan for both the corporate and data strategies. Examples of such issues may be compliance constraints on being able to manage data in a way that was anticipated (for example, a company may acquire a competitor but be told it has to put a firewall between certain parts of the integrated new venture due to anti-competition regulatory constraints), or delays in system implementations preventing the delivery of insight to drive a new venture as soon as was anticipated.

On the whole, instances in which the data strategy is at odds with the corporate strategy should be few in number, but it is always worth checking and engaging those who constructed the corporate strategy from the outset. Indeed, it may be that the data strategy highlights opportunities which the corporate strategy had not anticipated, and so the corporate strategy can be enhanced to realise benefits which previously were not understood, for instance adoption of tools or techniques that enable an accelerated approach or opportunities for new product development. On the other hand, it could also flag a potentially significant failing in the corporate strategy and be pivotal in avoiding significant problems ahead for your organisation, such as a lack of awareness of data issues in a merger or acquisition that could unearth some significant corporate risks if not addressed urgently.

One final observation I want to make is to never assume that the published corporate strategy has actually succeeded in making it through into practical implementation. As this book will explain, the evidence that the majority of strategies do not succeed in implementation applies as much to the corporate strategy as to any other type of strategy you might find in your organisation. You may even find a reality gap between what the executive board believes to be the case and the practical situation on the ground – the board members may even be unaware of the existence of the corporate strategy if it hasn’t been cascaded and explained in a way to engage them and relate it to what they do on a day-to-day basis.

Therefore, test your assumption that the corporate strategy is indeed in use to determine the direction of the organisation at every level of the workforce. It may be that there is a variant to the corporate strategy, a reality that manifests itself in the operational plans in various parts of the organisation, that is loosely aligned but is seeking to achieve a similar goal through different methods. If this describes the situation in your organisation, you are better off aligning to the practical reality of the ‘unofficial’ corporate strategy, as this is what the workforce is actually focused on delivering. Do continue to recognise the corporate strategy as documented, but don’t make it a constraint on your ability to get successful engagement in defining and delivering the data strategy.

3.2.3 Why now?

Let’s assume the organisation has a corporate strategy. The need for a data strategy may not have been identified previously, so why is it required now?

This is a question you may know the answer to, and could have been one of the key orchestrators in convincing the organisation of the merits in developing a data strategy. If not, then it is an opening question to ask the person tasking you with the responsibility. Understanding what has made a data strategy relevant at this point in time will give you a clear comprehension as to what those commissioning it believe it will deliver. Do understand, however, that there is every possibility that there may be a misapprehension as to what a data strategy is – it may have been mentioned in an article the executive has recently read, come up in conversation with a consultant or been highlighted at an industry conference by a competitor. There is a strong possibility that the original expectation is actually some way from what a data strategy entails, and therefore you need to check in regularly with your executive sponsor to inform on progress, clarify any outstanding issues and seek an ongoing mandate to proceed based on feedback.

There are three scenarios I will explore further (there are undoubtedly others) to provide advice to those who have just been briefed with the important task of devising a data strategy for the first time in the organisation.

3.2.3.1 ‘I’ve just heard that every organisation should have a data strategy, where’s ours?’

The first scenario is the executive returning from a conference or some sort of training event who calls you into an office or fires off an email saying a data strategy is just what the organisation needs, everyone these days has one and you are the right person to do it. As already explained, it is important to use this first ever reference to a data strategy to get things straight. Assuming you have a notion of what a data strategy is (if not, you need to do a rapid bit of homework before having the follow-on conversation), you could even set out a loose framework of what you think a data strategy might entail and send this for comment in advance of the discussion.

If the pitch for the data strategy goes well, then you may have seized the initiative and be able to build confidence in your capability to deliver it, in which case you then need to maintain that confidence through building momentum and providing regular feedback. You will need to ensure you move quickly into identifying what resources you need, including those outside your control, and obtain access to those staff who have developed the corporate strategy. However, there is a lot of groundwork to be done and you will need to prepare your sponsor for this – if a rapid turnaround of the data strategy is expected, then you will have to either produce little more than a scoping document to give a flavour of the headlines to come in the final document or let your sponsor know that this is unrealistic, but do at least set out an outline of your approach to demonstrate the progress you will make and touch points to show what has been achieved.

If you can, ask your sponsor to provide access to other senior stakeholders to gain their insight as to the problems they face, the challenges in implementing the corporate strategy and the quality of information at their fingertips to make reliable decisions. Consulting widely at the outset gives you an opportunity to gather qualitative inputs that will help in prioritisation as you progress towards having the data strategy ready to go, such that the implementation plan becomes easier to devise based upon the early insight on how to get engagement amongst the senior stakeholders in your organisation. Do bear in mind that they too might have either little or no understanding as to what a data strategy is, so structure your questions generally rather than lead on the notion that everyone understands what a data strategy is. A senior stakeholder will not want to be embarrassed by questions on something they do not comprehend, and a short meeting may result to avoid their ignorance being revealed.

3.2.3.2 ‘Make me compliant!’

Another scenario is that there has been some sort of review, either external by a regulator or the ICO, or internal by the audit team, and this has highlighted the organisation’s non-compliance with some form of regulation or practice that it should be following. Whilst the latter needs rectifying and will not go away – audit committees like to flex their independence by reminding senior executives that there are outstanding actions remaining, especially if chaired by non-executive chairs – the former may come with the threat of a forthcoming fine if rectification is not undertaken, or a fine regardless, as described at the start of this chapter. In extreme circumstances, it may mean dismissal or even prison for the senior accountable executive.

This tends to concentrate the mind, and if there are data issues at the heart of the transgression – as is invariably the case – then it is likely to lead to a programme of some sort to resolve the issue(s). It is an ideal opportunity to define the solution not as a compliance task, but instead as a means to instigate a wider review into data management – its capture, storage and exploitation – and pull it together in a data strategy.

How do you engineer the opportunity to take control and reorientate the requirement into a broader solution, one which requires a data strategy? It really depends on the situation, both in terms of the compliance issue and the appetite of the organisation. It may be seen as further delay to putting out a burning platform to embark on a data strategy at a time when the organisation is firmly in the spotlight, but there is just the opportunity to link several activities together to be able to demonstrate how a data strategy is both timely and a key enabler to solve the compliance issues for good.

The key is to get to grips with the problem at hand. What was the compliance issue and what brought it to light? Without knowing the problem you are unlikely to address the key issue that was core to the thinking of those instigating the data strategy. It isn’t unusual to find that the compliance issue is symptomatic of something much broader that isn’t working, and the issue has simply become the point at which the problem emerged into the spotlight.

Undertaking a root cause analysis or similar approach to get to the heart of the problem will almost certainly bring to the fore several more issues that need to be addressed. When these are added to other key issues that are probably simmering in the background that are relatively easy to uncover – systems migration/replacement programmes are often flawed through poor-quality data (more of this later), whilst inaccuracies in MI through manipulation of data in multiple departments producing different results is another issue – you are well on your way to being able to justify why a data strategy is needed.

Of course, it is a little more complex than presenting a ragtag bunch of issues to someone caught in the glare of negative publicity. These loose strands need to be woven together and presented in a coherent way, and a high-level plan should be sketched out to demonstrate how these can be resolved with the priority being the cause célèbre – the non-compliance issue which started this in the first place. You may discover that your key stakeholder doesn’t comprehend the problem, but simply wants it to be solved, and quickly. I refer back to CLEAR from Chapter 2, especially relevancy, as focus and stakeholder engagement will be key here. Remember, the data strategy is actually solving a hot problem, and so there is a need to lead with the solution as an introduction to the wider strategy.

However, this is a great opportunity to paint the picture of how something that started out as a compliance headache can become something of significant benefit to the organisation as a whole, and that you are the person to take the lead on delivering it. Build the trust of the key stakeholder on this one and you have credibility to be recommending the progression with the data strategy as the right thing to do.

3.2.3.3 ‘We really need a data strategy’

A third scenario is to have an organisation at an appropriately mature stage, with an understanding and track record of successful strategic implementations under its belt, that has realised it has an omission – a lack of a data strategy. In other words, the time has come to put this right, and it is over to you for delivery and alignment to the corporate strategy.

This might sound the ideal situation and in many respects it is, but there is likely a very structured approach to devising a strategy and the failure till now to spot the lack of a data strategy may suggest that those in the strategy space are not particularly familiar with what it entails. Therefore, it is important that you have sufficient latitude to be able to define the approach you need to take for this to succeed and avoid the pitfall of having a predetermined format and approach foisted upon you.

When developing a data strategy it is crucial to reach out to all parts of the organisation, get the right level of engagement and flex between a high-level vision and the detail of how data is to be managed – governance, standards, metadata, master systems, quality and so on – to ensure the key inputs enable the critical outputs to be delivered coherently. More so than many strategies, a data strategy covers all areas of an organisation: from comprehending the detailed activity and the baselined starting point, in order to ensure the route to successful implementation is feasible, to the visionary elements that comprehend, in the period covered by the data strategy, the art of the possible. It encapsulates people, process and technology, all of which are data-dependent to function.

One of the key artefacts to review will be the corporate strategy. How well can you align the data strategy to it? Will there need to be some rewriting of the corporate strategy to accommodate the data strategy? Could there be opportunities which the data strategy will introduce and need to be considered for inclusion in the corporate strategy? All of these points need careful consideration, as your organisation is relatively mature in its strategic thinking, and your task is to integrate and grow what is already in place rather than develop it in a silo. Engage those who have knowledge and experience of the corporate strategy, its content, drafting and key stakeholders, and it will save you significant time in your own process.

If the organisation is ready to embrace developing a data strategy, then the next chapter will guide you through the composition of the data strategy.

3.3 SETTING THE BOUNDARIES – UNDERSTANDING SCOPE AND THE RATIONALE

As demonstrated by the numerous examples of your starting point in defining a data strategy, the importance of having clarity as to the scope and the rationale for defining it is essential both for you, as the lead on it, but also for those you engage with going forward. If you are not able to provide that clarity and reasoning then it becomes challenging to get buy-in to the direction you are going, as it is highly likely every individual will have a slightly (or markedly, in some cases) different view as to the problem to be solved and the approach required.

There are challenges just in aligning others to a common understanding as to what a data strategy actually is, let alone why it is needed (as set out in Chapter 2). The way you approach developing the data strategy, from the moment you step forward to do so, is almost a strategy in its own right, as you will need to determine whom to involve, at what level and on what aspects, and how to ensure what you are doing continues to be visible to those who are not so directly involved. Having clarity behind the purpose and authority the data strategy carries is your first step before you seek to engage others. By all means refine and iterate to some degree, as this is a key way to draw your stakeholders in, but have a clearly defined scope and defensible terms of reference as to what you are tasked to achieve.

There is a lot of evidence in the public domain – through academic papers, conferences and books – that will enable you to understand why strategies fail, but these predominantly focus on the execution stage of the strategy, rather than the definition of the strategy itself. This may suggest that defining a strategy is the easy part, and I would tend to agree that the step beyond the strategy into execution itself is extremely challenging in most organisations.

Strategy, going back to its origins as the art of generalship or command, necessitates a general, or commander, without whom a strategy is likely to lack cohesion to see it through to being completed, agreed and ready for implementation. If there is a lack of clarity as to the long-term or overall goals in the organisation, then there is clearly a lack of strategic thinking to provide clarity of purpose. In such a situation, it is not unreasonable to conclude that without a driver of change any attempt to deliver a strategy is doomed to fail, not for the quality of the strategy itself, but the lack of understanding as to the why and the what, before even getting to the how, when and where, aided by the which (perhaps the most sophisticated, in terms of determining choices within the strategy).

Of course, if the strategy is never completed, or approved, it will not count amongst those that failed in implementation. The fact that data strategy definition may fail through a lack of effective leadership and sponsorship only increases the number that start but never make it through to successful implementation.

This matters in your task of defining a data strategy. I am making the point that there is an assumption in much of the literature that strategies lack implementation skills, communication or buy-in (amongst many others). However, a strategy that is well defined and employs effective stakeholder engagement and communication from the outset will avoid many of the pitfalls which perhaps only become readily apparent later in the process, when implementation stalls. As a result, getting the scope and the rationale for the data strategy agreed and communicated from the beginning is critical for success – not only in defining the data strategy but through the implementation stage too. Remember the 5W1H method from the preceding chapter: asking the same root questions (who, what, when, where, why and how) at least five times will enable you to explore the thinking to establish clarity and purpose as you embark on the challenge of developing a data strategy that will see it through to successful execution.

If probing highlights potential weaknesses in the scope or approach then call these out from the outset, as once you have started it can be hard to get a reset, and a failure to do so will formalise the brief to which you are working in such a way it may become impossible to deliver. The leader may also have to engage more widely before any change can be agreed, which will also lead to delay and doubts arising. Therefore, make sure your brief is coherent and has a clarity of purpose before you commit to taking responsibility for defining the data strategy. Changes will be needed along the way, but it is always easier to tack and adjust as you demonstrate progress than to appear stalled at the very beginning.

Do remember the point on terminology made in Chapter 2 that the term ‘data strategy’ can have very different meanings, so be clear on what your data strategy is focused on. Is it a full-spectrum review of the entire information cycle, including those items verging into a digital and technology landscape such as machine learning and AI, or more narrowly defined, restricted to selected elements of the information ecosystem (Figure 2.1)? Also, bear in mind the criticality of leadership in terms of the CLEAR approach. Effective stakeholder engagement at all levels will be essential.

It is also key to establish the type of output expected and the support you can look for from the wider organisation to ensure the process is collaborative throughout, and to have an understanding of how the strategy is approved and can then move into implementation. These represent your end goal, unless of course you are also seeing it through implementation.

Finally, this is your opportunity to revise the scope before you start work on defining the data strategy through engaging widely and ensuring all parties are agreed on the direction you are likely to head. Get a collective view on what they believe is needed – it is always easier to engage other stakeholders if their views have been sought and incorporated at the outset. If you are uneasy with the definition you have been given, the scope, timescale or the approach, then say so. It is essential that you get clarity and confirmation on these key points, as otherwise your progress will be hindered every step of the way, so articulate any concerns and reach agreement on how to deal with them from the start.

If you cannot reach agreement then it may be that this project is not one for you, but it may be a tough challenge to extricate yourself from it – be aware, the vast majority of strategies of all kinds fail to execute and realise benefits, and if this is ‘your’ project to lead you may wish to consider whether you are willing to commit to a project with a high propensity to fail to deliver all the benefits expected of it.

3.3.1 The role of sub-strategies in your data strategy approach

As the information lifecycle becomes ever more complex, with more channels, ‘big data’, AI, and an increasingly complex regulatory and compliance environment in which to operate, the scale of an all-encompassing data strategy becomes quite challenging. As a result, the data strategy can become encyclopaedic in size, trying to embrace every facet of the landscape and do justice to all to be considered within the data strategy.

The solution, which may seem both obvious but also a bit of a distraction from the issue, is to create the concept of sub-strategies within your data strategy.

The sections of the data strategy should align to the sub-strategies, if this is the approach you are seeking to take, which can help the difficult balancing act of keeping those who want to convey more information engaged whilst also making the data strategy an executive-level key document that is reviewed and approved at board level. Further, if you have stakeholders engaged in helping to shape the data strategy, operating as subject matter experts (SMEs) in various domains, what better than to empower them to take ownership of the sub-strategies and follow a similar path in creating these as has been employed in compiling the data strategy?

In this respect, it is quite feasible you could create sub-strategies focused on:

• data management, to include aspects such as data accessibility, security and compliance, master data management, data architecture, standards and quality, unstructured data, amongst others;
• MI/reporting, which can also be a driver to rationalise and focus on what KPIs are actually driving the organisation and are therefore needed to support decision making;
• analytics, including predictive analysis and moving the organisation up the value curve to exploit data more effectively by looking forward and preparing for change;
• insight, to encapsulate the gathering and exploitation of primary and secondary research and how it is managed and utilised in the decision-making process;
• advanced analytics/AI, increasingly an important area for all organisations, whether a consumer of such activity, a provider of services that utilise it or perhaps an organisation exploiting the technology.

These are commonly produced sub-strategies which underpin specific activities that will be incorporated in the data strategy.

There are others, not least the approach to data ethics, given this is often at the edge of compliance and may be driven by the balance between the efficacy of what is possible and the ethicality in what your organisation wants to be seen to be doing (often key to the brand perception). This can be a sub-strategy in its own right or a key aspect of the sub-strategies themselves, but it is almost certainly a growing area for consideration and likely to feature in some way in the overall data strategy.

I advocate in this book the concept of a rolling view in defining the data strategy, rather than fixing an end date and then not considering how it needs to evolve until the latter stages of that period, when a new data strategy needs to be defined. In much the same way, sub-strategies should be live documents supporting the data strategy, and any significant changes would lead to a revision of either the sub-strategy or data strategy, depending on where that change is driven. I would also recommend staggering the release of sub-strategies, for whilst the data strategy is in flux it would be a significant distraction to try to author the many sub-strategies. Instead, have a rolling programme in updating and reviewing the sub-strategies, keeping these current but devoting time and resources in a revolving basis such that there is work always under way to keep the strategies at all levels moving forward and avoiding peaks and troughs of effort needing to be provided.

3.3.2 The impact that type of organisation has on a data strategy

It is a reasonable assertion to suggest that data is the same the world over, and so why would a data strategy vary from one type of organisation to another. It is less about the data itself, more the nature of the organisation driving the focus behind the collation and use of data to provide context, strategic purpose and, importantly, the culture of the organisation.

One of the obvious areas to highlight in terms of how organisations do have differing key drivers is the variation between those operating in the private sector compared to the public sector.

A private sector organisation is dealing with competition (mostly: some may be in monopolistic areas, which I will come to later); usually customers are able to come and go depending upon price, service or a combination of the two, and therefore the exploitation of data is seen to be a key differentiator from competitors through a range of actions (for instance, pricing, propositions, customer targeting).

In the mid 1990s Treacy and Wiersema⁸ identified that there are broadly three generic competitive strategies:

• operational excellence, in which the organisation seeks to be as efficient as possible in its operational activities and reduce cost through automation of processes and activities such as just-in-time logistics;
• customer intimacy, providing a tailored range of services to the customer and using personalisation and a differentiated service offering to deliver to customer needs;
• product leadership, delivering a customer experience and brand recognition for innovation, product quality and being able to charge premium pricing in return.

Organisations must focus on which one they want to seek market leadership in and perform acceptably in the other two. Whilst this model is not exclusive to organisations in the private sector, the options are somewhat constrained for those operating in other markets.

To achieve operational excellence, the key driver is cost, as customers are not perceived to value choice. This fits most closely with mature markets where the output is commoditised, business volumes are high and hence cost leadership is essential. To succeed, organisations must be able to measure key processes and benchmark costs, not only their own but against known benchmarks competitors might be attaining, and to drive down cost through ever more effective and efficient processes. To deliver this, data has to be able to demonstrate performance but be readily available to support activities to drive cost initiatives. If your organisation is in this space then it has probably adopted process efficiency and quality control strategies (such as Six Sigma or total quality management), and the culture will be one driven by measures.

If customer intimacy is the goal, then there will be a focus on personalisation of the customer experience by delivering a service which has been customised to feel tailored to suit needs. This is likely to include bundling of services or products to provide a solution rather than the customer needing to identify what forms that solution for themselves. Clearly this is also data intensive as it needs significant amounts of customer data to anticipate needs and devise solutions which are likely to have a high success rate. Whilst the service is tailored, it isn’t necessarily one driven by innovation or price, but its success is built on the anticipation of meeting needs as the customer has them, through existing products or services and presenting them in a personalised manner.

Finally, product leadership is absolute on being driven by product innovation and leadership. The products are seen to be one step ahead of the competition, driven by quality and branding that ties the customer in to that organisation’s ethos of being first and hence superior to its rivals. It invests heavily in research and development, product engineering, marketing and hiring the brightest talent to drive innovation. It needs scale to do so effectively, which often necessitates expanding to markets beyond immediate geographic markets and acquiring organisations in their infancy that are seen to be on the cusp of developing products that are potential leaders of the future or opening up new, but related, markets to the organisation. Data is key to be able to provide collaborative working environments, accessing the latest knowledge within the organisation but also beyond, and to process large volumes of data to solve problems and drive innovation.

Whilst data drives each of these strategies, it is apparent that the drivers in each are quite different. Even though this model has been in place for nearly 25 years, the relevance of it to support those of us operating in a data strategy space remains. Comprehending where your organisation sits in this model will inform the priorities you need to focus on in defining the data strategy to align with the goals your organisation is seeking to achieve.

What does this mean for a public sector organisation? Well, for many, the notion of operational excellence is key to delivering high-quality services at low cost to ensure good use of taxpayer funds. The profit motive may not be as overarching as in the private sector, but this does not mean that the need to innovate is lacking – far from it. Public sector organisations have to be as smart as private sector organisations to fund change from within, and to ensure that talent and knowledge are accessible to maximise capabilities.

The challenge for organisations that are in less stable sectors, such as charities and other not-for-profit organisations, is the need to be effective across all three strategies within this model. With income less stable, continued delivery of projects which are seen to be of high importance to those providing funding has to be maintained to stay relevant and retain support. If this is not achieved, then those funding such organisations can fail to renew subscriptions or withdraw grants. As a result, operational excellence has to be the mantra, but customer intimacy is an equally important part of the organisational DNA.

This makes operating in such environments especially challenging, and innovation features strongly in the field of data and its exploitation. The need for a data strategy is particularly important for organisations operating in these sectors. It establishes clarity on how data can support the critically important activities to be delivered and how these can be achieved more effectively through better management and utilisation of data. It also provides a point of innovation, to establish new opportunities as well as significant improvements in the effectiveness of the ways of working through better insight.

In addition to the sector your organisation operates within, there are many other factors which will determine the nature of your data strategy and the approach to be taken in compiling it. For instance, an organisation operating in a regulated environment has to reflect the controls and constraints under which it operates, and ensure it stays compliant in its operations, which requires a strong hand through a coherent data strategy. In some markets, regulators publish their own data strategies and expect organisations within those markets to do likewise. In some instances, the justification for funding capital projects requires transparency in the data and analysis underpinning the rationale to gain approval from the regulator.

If the organisation is a monopoly, whether in full or part of its operations, much of the regulatory framework will likely apply. In such instances, a monopolistic organisation may be focused almost entirely by regulatory risk, hence the focus of a data strategy may be compliance-led. However, much like others operating in a strongly regulated environment, there is scope to drive greater operational excellence through better use of data.

The scale, ambition and resources of your organisation will have a bearing on the scale and scope of the data strategy you develop. In particular, resources will be critical enablers not just of the data strategy but also of determining the pace and scale of the implementation to achieve the ambition. There is more detail on the capability of resources, the maturity of the organisation and the importance these play in Chapter 6.

In setting the ambition of the data strategy, the complexity of the organisation and the legacy issues it faces will inevitably play a role in determining the scope. However, for a new start-up, the priorities are all based in the future. Their focus is on constructing the way in which the organisation intends to capture, use and manage data securely and effectively, and planning for the future when, for example, the need to upgrade systems and the exponential growth in data become critical issues.

An established organisation with a host of legacy systems and data quality issues is more likely to need to balance solving those issues with plotting a bold course for the future. The data strategy has to fit the organisation in which it will operate, and whilst the headings or chapters may be similar across data strategies (see Chapter 6 for more on content), the nature of the content is likely to differ significantly.

3.4 BALANCING CONTROL AND EXPLOITATION IN YOUR DATA STRATEGY

One of the key aspects of defining your data strategy is recognising the need to strike the right balance between implementing controls in your organisations versus exploiting data to generate insight and, potentially, competitive advantage. Of course, organisations tend to look at the return of an investment in committing to significant activities, and implementing a data strategy could easily be recognised as an investment. However, there is a delicate balance to be struck between investing in those things which are necessary to make the organisation compliant, better organised and decluttered (in terms of multiple data sets and conflicting reporting) and being able to generate insight and opportunities that may well change the dynamic of how well the organisation performs.

Building the foundations, establishing control, is often the unseen value of a data strategy implementation. The foundations may not be visible to those who benefit from their having been put in place but they deliver more secure outcomes than would otherwise have been the case. Progress without the necessary foundations, and the whole edifice could easily come tumbling down. Investing in what you cannot see does not equate to those elements having less value – indeed, the value is in the assurance it gives to what is visible.

You may therefore find yourself drawn into defining a data strategy which is focused heavily on those elements which are largely about data exploitation. I tend to suggest that the balance between data management and exploitation is not about focusing exclusively on the control – the foundations – in your data strategy: in the vast majority of organisations you do need to present ways in which the data strategy can make a visible difference to your stakeholders to sustain their support and commitment to your programme. Identify ‘quick wins’ amongst the easy-to-improve exploitation tasks, some of which may be obvious at first glance.

These could include rationalising the disparate reporting activity into a more coherent and reliable set of reports issued once and used across all of the organisation, so that all decision-makers operate to the same set of information. You will be making small compromises in the integrity of approach, yet still releasing value to the organisation, albeit in a sub-optimal way until the foundations are in place to do this more effectively. However, in the meantime, you have succeeded in demonstrating some value, getting traction behind being able to deliver change and whetting the appetite of your stakeholders to deliver more.

3.5 TEN TO TAKE AWAY

Here are the summary ten key points to take away from this chapter.

1. Assess the readiness and maturity of the organisation at the outset.
2. Identify the key drivers for the commissioning of the data strategy and adopt the appropriate response to navigate your way through to deliver something of value to the organisation.
3. Consider the sponsorship of the data strategy – who is the key influencer, who is behind the data strategy, who has most to gain? Getting sponsorship right makes a substantial difference to your likelihood of success.
4. Review the scope and reset if appropriate before you make a start. Be clear on what is expected and the timeline to achieve it.
5. Most strategies fail, with many falling short in implementation. Consider how to avoid the common pitfalls that lead to failure and keep a focus on these as you progress through definition into execution.
6. Stakeholder engagement and communication will be key to avoid failure. Ensure you understand your starting point – what the stakeholders believe and expect of the data strategy, their commitment to it and how you maintain a dialogue.
7. Reflect on the structure of your data strategy, and the need to underpin it with more extensive sub-strategies to bring more detailed intentions out on specific strands of the data strategy.
8. Assess your organisation type – core strengths and positioning in the market (the types of organisation as defined by the three competitive strategies) – and align the data strategy to enhance the organisation in that organisational type.
9. Think about how you strike the balance between getting the foundations in place to support the exploitation of data, and the ‘sell’ of this to the organisation with your data strategy.
10. Don’t discount quick wins to gain support through being opportunist. These may be imperfect in the longer term, but will build confidence and establish credibility if there is any doubt about the value a data strategy might bring to the organisation.

1 Michael Porter, What Is Strategy? Harvard Business Review, November 1996.

2 Bank of England Prudential Regulation Authority, Final Notice, 26 November 2019. https://www.bankofengland.co.uk/-/media/boe/files/news/2019/november/pra-decision-notice-citigroup.pdf?la=en&hash=4030FC4D482DF4C330A367A7A1A97E4649FB2968.

3 FCA Fines Goldman Sachs International £34.3 million for Transaction Reporting Failures, 28 March 2019. https://www.fca.org.uk/news/press-releases/fca-fines-goldman-sachs-international-transaction-reporting-failures.

4 FCA Fines Goldman Sachs International £34.3 million for Transaction Reporting Failures, 28 March 2019. https://www.fca.org.uk/news/press-releases/fca-fines-goldman-sachs-international-transaction-reporting-failures.

5 Standard Chartered Fined $1.1bn for Money-Laundering and Sanctions Breaches, The Guardian, 9 April 2019. https://www.theguardian.com/business/2019/apr/09/standard-chartered-fined-money-laundering-sanctions-breaches.

6 Intention to Fine British Airways £183.39m under GDPR for Data Breach. https://ico.org.uk/about-the-ico/news-and-events/news-and-blogs/2019/07/ico-announces-intention-to-fine-british-airways/.

7 Intention to Fine Marriott International, Inc More than £99 million under GDPR for Data Breach. https://ico.org.uk/about-the-ico/news-and-events/news-and-blogs/2019/07/intention-to-fine-marriott-international-inc-more-than-99-million-under-gdpr-for-data-breach/.

8 Michael Treacy and Fred Wiersema, The Discipline of Market Leaders: Choose Your Customers, Narrow Your Focus, Dominate Your Market. Cambridge: Perseus Books, 1997.