Companies across industries are making more day-to-day decisions and unlocking value with the help of data. From sensor data to website data to sales data, more and more aspects of business are being quantified and analysed. One side effect has been an increased focus on data scientists, their skills and their roles within companies.

But in most organisations, data scientists are but a small subset. Truly fostering a data-driven, analytic culture must go beyond that piece of the puzzle and consider the management of data scientists and beyond, plus training, tools, hiring processes and more, across departments. These are all crucial aspects of transitioning to a true analytic culture. In most cases, the kind of change that needs to take place must start at the top and that change begins with:

Empowering every individual Fostering an analytic culture from the top begins with empowerment. A successful analytic culture must be top-down in a very free-flowing and democratic way. ‘Fostering’ as opposed to implementing or forcing is key. It means empowering and trusting the workforce to explore and answer their own questions with data. In the earlier days, analytics were managed solely by one centralised team. The way forward, however, needs top leadership to decentralise the process so that every team member may ask their own questions by offering them accessible tools, the right training and giving data access (except for the most sensitive information) to the entire company.

Yet, all of this empowerment and fostering may not be for anything without the implementation of self-service analytics. Keep in mind that tools aren’t truly enterprise-ready if all members of the enterprise can’t use them. Having a tool with a subset of people who can use it, use it well and build great things isn’t enough.

Training your human resource Getting all users to be data-driven will, more often than not, require additional training. This training will happen in the form of tool training – through the use of the actual tool, use cases, online videos, and more. Such training tends to focus on features and functionality.

What is also important to address through training is the wider aspect of critical thinking, analytical curiosity, and a foundation in the relevant fields such as data visualisation. Bringing in outside experts can help to this end and keep things exciting. With this academic background and general foundation, specific tool training begins to make far more sense.

Accepting the change in culture One thing that’s important to note is that, for a lot of organisations (especially ones with very sensitive data), this empowerment can feel extremely uncomfortable at first – which brings us back to top leadership. Top leadership plays a key role in moving the company beyond a need-to-know mentality and truly practising what is being preached. By being unable to do this, you will undermine the entire transition. Acknowledging that empowerment can feel uncomfortable is the important first step, followed by taking steps to make it begin to feel like the norm.

Demanding data literacy It then becomes necessary for the leadership to demand data literacy from employees at every level. Instead of asking for opinions, management at every level must require data in their answers from their teams. Answers shouldn’t begin with the words “I think.” Instead, data literacy should be a part of all conversations. Of course, this will only stick if top leadership sets a visible example. All executives should use data every day and must model the analytic process and culture they want.

One small but important step to this end is to actually make data a part of all job descriptions so employees across the organisation are measured on it. This will make it easier to reward data-driven behaviour on a personal level. Another tangible step is to hold a company-wide competition with data. These are a great supplement, as they allow for leadership to reward data-driven behaviour more globally. Run an internal competition where folks can show off their skills, and make it executive-sponsored and judged. This gets a lot of people involved, puts the tools and training into action and really puts data at the forefront of the company.

Hiring fresh data-literate members While all these initiatives are taking place, leadership must also communicate a focus on the hiring process. Building an analytic culture with existing employees should be supplemented by an ongoing attempt to bring in the culture your organisation wants. Data should, of course, play a role in this process … but keep in mind the ideal candidates are not usually those with the most knowledge of the latest technology. Technical skills are important for some roles, but there is one non-negotiable trait that every team member must have: critical thinking.

The simplest way to look for critical thinking is to give all candidates – not just data scientist or data analysts – a data-driven test. The results are almost always quite revealing. The answers show whether the candidate can form questions to ask of their data, whether they are skilled at answering them and whether they ask follow-up questions.

Curiosity is another intangible that really underscores self-reliance and an analytic culture. One great shortcut to measure a candidate’s curiosity is to ask them how a toilet works. While this may seem like it’s out of left field, it’s a very telling question! People spend lots of time in toilets. How many people have actually taken the time to wonder and figure out how it works, though? This is also a great question because it’s fair and level for all candidates and can often get them to come out of their shell.

Most job-seekers come with plenty of canned answers … but few have a canned answer about toilets! This will allow interviewers to get a sense of curiosity and personality – two important facets of any hire and company culture.

All in all, implementing an analytic culture is a long-term process – not something that will happen overnight. But trust me when I say that a year from now, your company will have wished that top leadership got started today. Implementing the right technology, teaching everyone in the company how to use it and making data a baseline of all conversations are just a few ways your organisation can begin pushing the ball forward with regards to an analytic culture – and it all begins at the top.

Deepak Ghodke is Country Manager, India, Tableau Software

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Published on February 18, 2016