Mutual Friends: Aligning business strategy and data strategy
10 Jun 2020 by Nigel Turner, Global Data Strategy
Charles Dickens published his novel, “Our Mutual Friend,” in 1864. It’s safe to say he was probably not thinking of data strategy and its relationship to business strategy when he wrote it. But it is a simple fact that in our digital, data-driven world, business and data strategies can only succeed if they are closely interlocked and nurtured as mutual friends.
Before the rise of the data-driven business, the relationship between business and data strategies was linear. The business would set out its strategic goals and aspirations. Once these were determined, a data strategy could then be built to plan the data capabilities needed to underpin the business strategy and plan. This also implied that IT departments were often the primary drivers of a data strategy.
The idea that data is a subservient enabler is outmoded.
Today, things have changed. The idea that data is a subservient enabler of the business, useful only to support business operations and processes, is becoming increasingly outmoded. On the contrary, in a growing number of organisations data is becoming the business.
This has radical implications for the relationship between business and data strategies. In this new paradigm, the development of business and data strategies has to be done in parallel and interdependencies between them locked in. Any data-driven organisation (and what organisation isn’t these days?) which fails to recognise this mutuality is doomed to fail. This also means that any aspiring data-driven, digital organisation must create and implement a data strategy, something surprisingly many have still failed to do.
For example, take a manufacturing business producing a range of consumer goods. Traditionally it focused on selling its products to wholesalers such as supermarkets and other third-party channels. As such, its knowledge of its end buyers was at best sketchy and for the most part non-existent.
But it decides to create new digital channels to sell its products direct to its end customers, surmising that cutting out the wholesalers will increase its profit margins and enable it to gain a better understanding of and build relationships with its end customers. None of this is possible unless this new business strategy is developed alongside the data strategy needed to deliver it. Key questions would include:
- What new data would the organisation need to generate and capture to support the new business processes that need to be developed?
- What data platforms would need to be created to store the data?
- How will sales be made - through direct online channels, social media platforms and so on?
Business strategy without data foundations is a folly.
The point here is that setting the aspiration in stone in the business strategy without being first being sure the data foundation exists to realise it is folly. So data must become a pre-eminent consideration when developing the business rationale and case for direct sales. Moreover, it’s also possible that, as the required direct selling data strategy is developed, it can help to suggest other opportunities that the business had not considered, for example, how analysing data on online consumer purchases can help to highlight purchasing trends and so help generate new product propositions.
So, if you are tasked with developing a data strategy, how do you ensure that this close mutuality and interdependency happens? Here are some suggestions:
- Let the CDO, not the CTO define it: First and foremost, a data strategy should not be owned and developed by the IT department. IT might legitimately lead the technology strategy which will be needed to deliver the data capabilities required, but a data strategy must be owned by the business, working in close collaboration with IT. A chief data officer (CDO) is the logical lead if one exists in your organisation.
- Understand the business drivers: As a data management specialist, ensure you understand your organisation and its business goals, strategies and aspirations. The current formal business strategy is, of course, the ideal starting place, but you can supplement this with annual reports, external and internal websites, social media feedback and so on.
- Engage with stakeholders: When developing the data strategy, engage with a wide spectrum of business and IT stakeholders. These should range from senior executives through to people who actually run the day-to-day business. They will all have a different perspective on data problems and opportunities, so you gain a much richer and holistic picture of the current data landscape and the drivers for change.
- Speak the language of business: After drafting the data strategy, expect to create several initial iterations after presenting it back to the stakeholders. Use business language and not data management jargon to ensure it’s readily understandable to all. In particular, wherever possible, try to mirror the language of the business strategy to help people make the direct connection between them.
- Be agile: Finally, a data strategy is not set in stone. It needs to change and evolve as business goals and strategy change, so ensure there is a process in place to maintain alignment with the business strategy, review it at regular intervals with key stakeholders, and update it accordingly.
More organisations are recognising the need for a dynamic and flexible data strategy as a keystone to help them achieve their business goals. In a poll of Data Management Association UK (DAMA UK) members in May 2020, 69% of respondents stated that developing a data strategy was one of their two top data management priorities (with the other being data governance at 77%).
We are living in hard times, but only by making business strategy and data strategy mutual friends can it hope to meet the great expectations placed on them by so many organisations. Charles Dickens would have understood that.
Nigel Turner is principal information management consultant at Global Data Strategy and a committee member of DAMA UK.