Blog - 22 Jul 2021
4 minute read
Data Science & Analytics
Data Strategy
The Data Conversation

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Data strategy creates a clear narrative about how a business will use data to achieve its business aims. 

data strategy, digital strategy, business strategy, technical strategy, data & analytics, data-driven, digitalisation

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2021-07-21T23:00:00Z

Why you need a data strategy (and also why you don’t).

Ascent Chief Data Scientist, Rich Pugh, explores the data strategy paradox and its relationship with modern business planning.

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Data Science & Analytics

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Let’s start by playing Strategy Bingo!

Which of these does your organisation have?  Award yourself one point for each:

  • A business strategy

  • A technical strategy

  • A digital strategy

  • A marketing strategy

  • An HR strategy

  • A communications strategy

Well done! Chances are you’ve scored at least 3, if not the full house.  Most businesses today have as a minimum a business strategy, a digital strategy and a technical strategy (note: if you don’t have a business strategy, stop reading now – you have bigger problems).

But over the last 10 years we’ve heard increasing buzz around the latest must-have: a data strategy!  But what is it, and why might we need one?

A data strategy.

Quite simply, a data strategy creates a clear narrative about how a business will use data to achieve its business aims.  Done well, a data strategy is a (short!) practical and pragmatic guide that connects disparate parts of our organisation via the medium of data.  It allows your leadership team to look beyond the ‘what are we doing’ of data to a better understanding of ‘why we’re doing it’ and how it helps to drive real-world outcomes. This should include:

  • A simple statement, outlining the vision for your use of data in your organisation

  • A mapping of your business goal ‘domains’ - broad themes that connect to deliverable initiatives

  • A set of initiatives that will deliver value aligned to identified domains

  • Consideration of the impact of the above on pillars of culture, value, delivery, technology, governance.

But isn’t this a digital strategy?

No, although in my experience there can be significant overlap in objectives, energy and approach between the 2 areas. In general, a digital strategy focuses on activities to create new business models that are enabled by the ongoing digitisation of a company. Digital strategies have tended to focus heavily on technical platforms that would enable new functionality in a business – like a platform to support an omni-channel approach in retail.

A data strategy is more focused on the management and application of data and analytics to drive business outcomes. For example, ‘how we’ll use data to better understand our customers so we can have more relevant conversations through our omni-channel platform’.

So, whilst a data strategy has a separate focus to a digital strategy, there can be a symbiotic relationship between the two. They are also both aligned to your technical strategy (which governs the technology approach to create a unified, manageable technical estate) and your business strategy (which describes where the business wants to go and how it will deliver on its purpose).

When is a data strategy not a data strategy?

The word strategy is typically defined as a framework for behaviour – it provides the rules of engagement that govern a set of actions that drive towards a specific outcome, underpinned by a belief system.

However, in business the word strategy can be synonymous with an expensive experiment in inactivity. Too frequently I’ve seen companies pay – er - ‘reassuringly expensive’ consultants to create a beautiful 200-slide piece of shelfware that offers elegant theory but delivers no practical value. To be clear, a good (data) strategy should be:

  • Aligned – connected directly to business outcomes

  • Actionable – something that can be delivered with clear next steps

  • Practical – using language that aligns with internal culture

  • Appropriate – approaches are right-sized for your organisation and ambitions

  • Balanced – well-balanced across the different ‘pillars’ of transformation

  • Concise – as short as it can be to communicate the above, and no longer.

So do I need a data strategy?

Yes! And also, no.

I firmly believe an organisation needs a vision and a plan around its use of data, and a good understanding of how helps them better compete.  As more companies invest in data and analytics, there is no other option.  How will you fare if your competitors are able to fundamentally make better decisions than you?  Or if they’re able to cut 25% of their costs from a process to deliver a product or service?  There is a Darwinism effect happening right now, so the ‘stick your head in the sand’ approach to data is just no longer viable.

The question is: what is the right vehicle for talking about data?  When a leadership team is all strategied-out, the last thing they may want to hear about is a new and distinct additional paper.  For some, suggesting the need for a data strategy will be met with enthusiasm, but I’ve also seen the idea of a new strategy met with board-level eye-rolling (perhaps due to the issues outlined above).

So here’s the thing: we may or may not need or want a defined, isolated data strategy. What we most definitely DO need is to educate our leadership around 4 key points:

  • Data has the capacity to create significant market advantage

  • We’re already ‘doing data’ today, so this is about doing it better

  • Our competitors are already investing in data (I suggest looking up the latest company report for your competitors and searching for words like ‘data’ and ‘analytics’)

  • We need a plan of action around the role of data to drive our business outcomes

Whether you call this plan a data strategy or something else, I don’t think it matters too much.  The important thing is to have the conversation, and to create a clear narrative around the role of data in your future success.

Bringing data to the mid-market is a data conversation by Ascent’s Chief Data Scientist, Rich Pugh (DataIQ 100)and covers all you need to know about data strategy, objective setting and implementation.

Rich Pugh

Chief Data Scientist

Ascent

As Chief Data Scientist at Ascent, Rich is passionate about delivering pragmatic advice to leading organisations on data-driven transformation and building successful data science teams.

With more than 20 years’ experience helping companies create value from data, Rich has worked across a variety of industries, helping businesses around the world increase profit margins, solve operational challenges and delight their customers.

Rich is a strong believer that there is nothing analytics can’t do and strives to help organisations leverage the power of their data.

Rich Pugh

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