How to create a data-led organisation

Most executives understand that having a data-driven organisation will increase revenue, improve customer satisfaction, deliver operating efficiencies and drive profitability. So, then, why have only 24% executives created a data-driven organisation? It comes down to not having a data-led culture. The good news is most executives – 76% according to a BARC study – are making the relevant investments to transform their organisations.

If you are like most executives I speak to, you are probably asking yourself what is a data-driven organisation. Being data-driven means employees rely on numbers even when it’s not easy or convenient to do so. If you have a data-driven organisation, you’ve developed a data culture that permeates the entire organisation – not just at the executive level or within certain functional areas, but everywhere.

Creating a data-led culture requires a vision and a plan.  To help you understand what is a data-led culture, let’s first look at the characteristics of organisations that are not data-driven.  The bad before the good, in a way. 

• Lack of executive support.  Changing the culture of a company requires executive leadership especially to overcome internal resistance when introducing new skills, people and ways of working. In fact, according to a survey conducted by NewVantage Partners, 91.9% of executives said cultural obstacles were the greatest barrier to becoming more data-driven. 
• Lack of strategic alignment.   Setting and aligning strategic business and technology strategies – and teams so they work together toward shared objectives – is a requirement for company success.  This is particularly true when data and the tools used for insights and analytics is a collaborative effort. 
• Lack of a single view of data.  The inability to have a single view of data, such as customers, product, inventory or sales, limits the ability of your colleagues to make informed decisions.   For example, not having data on customers makes it a challenge for marketing  professionals to understand and effectively engage customers required to improve satisfaction, sales and loyalty.   
• Lack of data quality. Poor data quality can be a serious barrier to business success, resulting in decision-makers questioning the accuracy of their organisation’s data.  It’s a big problem that is costly, too, with Gartner estimating that poor data quality costs companies $15 million per year in losses.
• Lack of data literacy. The ability to read, analyse, apply and communicate the value of data is a challenge for most people, though it’s a business critical skill today.  An Accenture study of 9,000 employees across industries and job roles revealed that just 21% of them felt confident in their digital literacy skills.
• Lack of tools. Creating a data-led culture requires providing colleagues with the tools they need to visualise and analyse data.  According to a Deloitte survey, 67% of mid to senior-level professionals struggle to access data because the analytics tools deployed in their organisations are too difficult to use.
• Lack of collaboration. Investing in data tools and processes without the involvement of the business will result in wasting precious money and time.  Therefore, ensure that your analytics and business teams are working together on real-world use cases that deliver tangible results – be it specific  insights and/or business outcomes. 
• Lack of change management. It’s important to prepare your colleagues for the transition to a more data-driven culture, and this requires investment in communications. A 2015 McKinsey study found executives that invested in a rigorous change management approach reported a 79% success rate – three times the average for all other initiatives.

Now that we have covered what not to do, let’s now look at what you should do if you’re starting off on the journey to creating a data-led culture.  Here are seven tips that will lower the time and cost to creating value from your data and, at the same time, start to introduce the characteristics of high performing data-led organisation:

1. Start with the question.   Start with what you’re trying to achieve from a business perspective and then source the data required to answer the question.  In doing so, you will start to create or reinforce a data-driven culture.  If you’re not sure where to commence, create a list of questions you and your colleagues seek to answer and then determine what data you have and don’t have available to answer the questions. This will help prioritise what value you can create in the short-term and what investment in data, people and technology you may need to make for the long-term. 
2. Get your hands on the data.  You’re sitting on a gold mine of data so start to use it.   A logical place to start is better understanding your customers in order to acquire or retain them.  Here are six suggestions to help you generate quick value from your data. 
3. Obtain the right tools.  Having easy-to-use tools that enable your colleagues to quickly access, understand and interpret  data is important to creating a data-led culture.  If they are confident in using tools, then they will start to apply the data to support them in making decisions.
4. Build data literacy. Making sense of data is a challenge for most people in an organisation. To address this, it is critical that you invest in training and coaching colleagues so they can:
   1. Ask the right business questions
   2. Understand what data is needed and how to test the validity of the data
   3. Interpret the data so the results are useful and meaningful
   4. Test hypotheses using A/B tests to see what results pan out
   5. Create easy-to-understand visualisations so colleagues understand the results
   6. Tell a story to help colleagues see the big picture and act on the results of analysis
5. Develop data strategy. The goal of a data strategy is to answer the question of how your entire organisation can leverage data in support of making business decisions, and to create a plan (with a clear data roadmap) that factors in the role of people, processes, and technology to make the plan a reality.  
6. Start to ask more questions.  After you have used data to answer foundational questions about your business, you’ll want to ask more far reaching questions such as how do you reduce the costs of returns, which my colleague, Peter Hanlon, Head of Analytics at Xiatech, answers for you.
7. Recruit data scientists. Once you have started to generate significant value from your data, and you have begun to ask more advanced questions of your data, you will want to bring in data science, either directly or through a partner. My colleague, Alberto Calzada, Xiatech’s Head of Data Science, has shared his tips to help you build a data science  team.