Blog - 30 Sep 2022
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Data Transformation
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Results of a KPMG report ‘The Data Imperative’ reveal that 57% of large enterprises do not have a defined data strategy. An actionable data strategy is a critical part of a data and digital transformation that aligns clearly to your business ambitions. It needs to be well balanced and ultimately identify a set of initiatives to invest in that will drive change.

data strategy, AI and analytics, data assets, data-driven, business objectives, datadrivenstrategy

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2022-09-29T23:00:00Z

How to build a data strategy to drive value.

Ascent Chief Data Scientist Rich Pugh explains why successful business transformations start with a well-defined data strategy.

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Data Transformation

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Results of a KPMG report ‘The Data Imperative’ reveal that 57% of large enterprises do not have a defined data strategy. An accessible, actionable data strategy is a core component of successful digital transformation, aligning your data assets and capabilities with your business ambitions and identifying the initiatives that will truly drive change.

The purpose of a data strategy.

The main driver for developing a data strategy is to create clarity around the role of data in a business’ future success. Many organisations have so much data they don’t know what to do with it. At the same time, thanks to the ongoing hype around AI and analytics, organisations know that there is potential or value in their data assets, but they simply don’t have access to the expertise that could help them identify the best opportunities for their business. This is where a data strategy can help – done well, it creates a clear narrative around an organisation’s opportunity and a roadmap to inform investment as part of a broader transformation.

Creating an effective data strategy that drives action can be a complex task.  Here’s some of the common questions we get about data strategies:

What should you consider before writing a data strategy?

If there’s one aspect you need to get right with a data strategy, it’s that it must align to (and help deliver on) your wider business goals and objectives. Without this, your data strategy will lack relevance – you won’t be able to engage your senior stakeholders – so inevitably it will become expensive shelf-ware.

We must also remember that delivering a data strategy is all about change – transforming and reframing your business by putting data at the core of your operations heart. If the organisation is not ready for change, then you may not be able to realise your data-driven potential, however well-described in a strategy.

Why might I need a data strategy?

Firstly it’s important to note that every organisation uses data – you can’t not in this increasingly digital landscape. If you hire a single employee, send a single invoice, or simply send an email, you are using or creating data.

However, the role of data has changed dramatically in the last 20 years – from a by-product of operations to a strategic asset that can be used to create a leaner, smarter, more relevant business.  Because of this, an organisation needs a vision and a plan around its use of data and the role that data will play in their future success.

It comes down to Darwinism: 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 processing costs to deliver a product or service?

What should go into a data strategy?

Fundamentally, your data strategy should create a clear narrative around:

  1. Your ambitions: An understanding of why you’re creating this data strategy, and what you hope it will achieve in the context of your business objectives - is it to become more smart or efficient for example? Since many people in the business won’t know what a data strategy is supposed to accomplished, we should describe why we’re creating it and what it will enable the business to do that it cannot do today.

  2. Your opportunity: A vision for the way in which data will deliver on your business ambition, including a set of specific activities and the impact these are expected to deliver. For example, consider the following:

  • What does a future data-driven version of our business look like?

  • What value could data deliver to our business?

  • What is the cost of transformation? What is the cost of not transforming (or not transforming now?)

  1. Your journey: A clear definition of your current maturity levels, and what will need to happen to support the value you are looking to deliver:
  • What is our current starting point in terms of maturity?

  • What does a practical and balanced roadmap look like?

  • What are the immediate next things we should do?

To describe your journey, the data strategy should present a summary of the current levels of data maturity across an agreed set of pillars which include People & Culture, Technology, Data Management & Governance, Skills & Change. This ensures your data strategy is well balanced (and not just a business case for tech investment, or a suggested data management process).

How should we communicate our Data Strategy?

When your data strategy is created, you will likely find that you will need to create alternative versions to communicate key aspects to a variety of stakeholder groups. For example, you may want to create a version for the board to support an investment case, aversion for broader internal stakeholder engagement and even a public version for external stakeholders.

It is important to remember that a data strategy is a live working document, so establishing a clear plan for ownership, and an approach to communication is vital - forming a dedicated project team from all represented areas of the business is essential, rather than being conducted in siloes.

In summary, an effective data strategy can create alignment in the business about the role data will play in meeting your ambitions, helping everyone understand the reason for your journey and the steps you will take towards becoming a more data-driven organisation.

By Rich Pugh, Chief Data Scientist, Ascent.

#datadrivencompany #datastrategy #digitalstrategy

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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