Welcome to the second post in our 5-part series on fostering a data-driven organisational culture. We’ve been helping organisations to create data-driven cultures for a few decades now so we’ve put together this series to help you to do the same.  Last week we examined the importance of getting business buy-in to the analytics process.  Once you’ve gotten that, you are ready to start your analytics journey following these four steps.  This week we are examining the first one:

  • Design a strong data and analytics strategy
  • Move from strategy to decision implementation
  • Embrace a questioning culture
  • Always be measuring (close the loop)

 

 Analytics First Needs a Business Strategy

The raison d’etre of analytics is to deliver insight to be actioned by the organisation.  The prerequisite to an analytics strategy is therefore a clear, well defined, well understood, actionable, business strategy.  Examining the business strategy will allow you to identify concrete opportunities where analytics can contribute to the organisation achieving its goals.  You can use these identified opportunities to provide structure for your analytics strategy.  This will mean that your analytics function is delivering measurable value to the organisation.

An analytics project without an aligned organisational objective will not be able to deliver value.  While it is possible that novel discoveries might be made, this will be down to luck – and not good decisioning processes.

Avoiding ‘Analytics for Fun’

When analytics is performed simply because it is fashionable, or with a vague objective such as ‘investigate the business’, then there are only two likely outcomes:

  1. Discovery of solutions to non-critical problems. While these insights may be interesting, they are not actually important – they are not of any tangible use to the business.
  2. No solutions will be discovered.

In both cases there are two costs.  An immediate opportunity cost arises, because the analytics project could have delivered tangible value, had it been business-aligned.  The second cost has longer-term ramifications – analytics projects may subsequently be viewed as expensive, tangential, flights of fancy.

The Analytics store has spent 15 years consulting with large organisations, and we have often seen this happen.  It can take years for an analytics team to recover from projects that did not have specific objectives, and could not, therefore, provide actionable, valuable insight to the organisation.  The organisation becomes disillusioned with the possibilities that analytics promised, and the team feel demoralised.

To avoid these pitfalls, weave your analytics strategy into the organisation’s strategy.  Over time, these two strategies will merge to become one.  For now though, you need to prepare your organisation for the changes that implementing that strategy will bring.

 

Change Management: Analytics Impacts Everyone

As the analytics champion, you’re going to need strong change-management skills.  The introduction of analytics into an organisation has wide-ranging effects: communicate them early to your colleagues within the management of your organisation, and keep them involved in the on-going strategic development of the analytics projects.

Be clear: a well implemented data driven strategy will result in a change in how decisions are being made – for everyone.  Your senior colleagues will need to have a sound understanding of the impact on them of implementing a data driven strategy.  Be clear from the start so that they can prepare.

Keep communicating: analytics is not something that can be developed in a silo within a technical team.  It requires active input from the organisation’s leaders who will be actioning the decisions based upon the derived insight.  Later in the series we will examine just how crucial pan-organisational data literacy and involvement is, but for now … just keep communicating.

Champion measurable improvement: your role may involve engendering a new acceptance of the existence and identification of areas within the business that need support, clarity or redirection.   Analytics can sometimes highlight areas where processes are not well-defined, or are not fully understood – and that can be painful for those areas. To counteract this, you can highlight in advance the likelihood of that happening and involve senior colleagues in developing a plan for dealing this type of new information.  Focus on the positive side-effect of bringing rigorous examination to bear on the decisions that are built upon these processes: it should be embraced.  To help you communicate this, you can present a framework such as measured improvement, and measured failure.

 

Failure Is an Option – Once We Learn How to Succeed

Along with your colleagues in the organisation’s management, you can work to change a reactive culture to a proactive one. Intrinsic to that is the acceptance that failure is part of a data-driven culture, and is imperative to its success. Valuable business decisions cannot be made without the risk of failure.  It is perfectly possible to make many decisions that avoid the risk of failure – by defining those decisions so that they result in as little change as possible.  This, “busy-work”, is to be avoided.  Instead, encourage decisions that are based on good data, answer good questions and identify solid business value.  Be prepared to take a measured risk.

By its nature, analytics involves testing possible decision pathways.  Tests may tell us it is the wrong decision pathway.  This type of measured failure is good – it provides us with the data to be able to take the correct decision in the future.

But be careful, failure is not an end in itself!  Failure is encouraged, but only

  1. as a necessary by-product of innovation,
  2. when the risk has been minimised before-hand
  3. when the failure was calculated to provide information as to the better pathway.

 

Conclusion

An analytics strategy exists in tandem with a business strategy.  Analytics should always be undertaken to deliver concrete value to the organisation. An analytics strategy, and function, can only be developed in tandem with your senior colleagues – keep the in the loop. Implementing an analytics strategy involves bringing rigor to bear on all existing processes, which may highlight areas for improvement. Develop a plan with senior colleagues as to how to deal with those new insights.  Share this plan with the wider organisation in order to encourage proactive decision making, investigation and testing of solutions.  This groundwork will serve to create a culture where analytics functions and their projects can be integrated, successful and valuable to the organisation.

Whether your organisation is fledgling, well-established, small or multinational, a good data and analytics strategy will enable you to make braver, better business decisions.

The Analytics Store is the leading consultancy and training firm in analytics in Ireland.  We work with business leaders to knit data and analytics into their business strategies, ensuring that analytics teams and projects deliver insight, that can be actioned and measured.  If you are curious about how we could facilitate your business, get in touch.

The next blog in our data-driven organisation series will examine how to move from designing your strategy to actually making decisions.  We will look at the data, people, systems and decision space that are necessary to do so.