By our guestblogger Nelly Chatue-Diop

While data creation accelerates today at a rate never reached before, companies are facing challenges ranging from what to do with their existing data and what to do with new data. To illustrate this statement, did you know that there are almost 3 quintillion bytes of data created each day at our current pace?

Data has always been used in diffferent parts of companies. Finance, for example, is one department that has always relied on data in order to provide an overview of the companies’ performances and other budget purposes. As of today, the combination of more data availability, power and affordability computational capabilities and enhanced models, can give companies a strong competitive power. But unfortunately not all companies know how to deal with this data driven transformation. Data culture is not and should not be only for companies like GAFA or BATX. Moreover, it is a significant feature for future companies. Find here some easy recommendations on how to start.


Every transformation starts with people. I would suggest auditing all departments within the company to understand their current challenges: it could range from wasted time on manual repetitive tasks to deeper interrogations on how to achieve the department objectives in a more analytical way. Those precious feedbacks from your employees will give you the perfect opportunity to change the company’s culture. It will also introduce the imperative of transforming the organization culture into a data-driven one. Besides, it is highly recommended to use examples provided by your employees and thus show why it is relevant to your company. This will show how data could help them overcome some of their challenges.

Next to that, you will need to identify your data champion who will be empowered to embody this data transformation and follow up on all data initiatives. This leader should have strong interpersonal skills to collaborate efficiently with others as well technical skills to translate data findings into business insights. He or she must also be business savvy in order to adapt to your particular market industry therefor quickly prioritize projects that will be valuable for your company.

Besides, it is important to have this Data Champion reporting directly to the CEO. This will avoid dampening a major asset of Data Analysis – being neutral, completely objective with the sole goal of optimizing the bottom line of the company. This point is critical and it is where I see many initiatives failing.Let’s take some examples how to avoid data from getting subjective

– Your Data champion reports to marketing. Are you sure your Marketing leader, given data insights showing poor ROI of marketing campaigns, would willingly stop these campaigns at the risk of significantly downsizing his department budget?

– Your Data champion reports to Finance. Are you sure your Finance leader will agree to follow through on data insights recommending a double down on short term costs for great potential return on long term?

– Your Data champion reports to IT. Are you sure valuable models won’t be diluted down for the sake of simpler Architecture and/or lesser calls to the Database? And the list goes on and on.

Hopefully, it is now more clear for you to understand that introducing an intermediary between the CEO and the Data champion might prevent some highly valuable data insights to never get implemented across the organisation

Finally, you need to create an A-rated team of data professionals. Various skills that will include a good data team are : data engineering, data analysis, data scientists, etc. This unique combination of skills within a common team will ensure a shorter time to fulfill your data initiatives. The A-rated team will then help you choose the most appropriate tools to increase their efficiency.


As a transformative initiative, you want to make sure you choose the first projects to tackle, carefully. They need to be short, understandable by most and provide unquestionable value to the company. These early successes also need to be widely celebrated. However, not under the light of what the data team has accomplished but rather how much value it has generated when collaboration between data and business expertise happen. These projects are your stepstones to more complex ones but also more valuable ones and the map from these pilot initiatives to your ultimate data projects should always be clear for your company leaders.


Did I already mention that such initiatives start with people? Well, they also end with people. You have to give training in analytical thinking to everybody.
Your training should reach all employees, adapted to their levels and most important to their needs. Vice versa, this will allow your organization to leverage in-house talents as outside recruitment of data talents can be hard and expensive, given their rareness. Your main KPIs should be shared with all employees, so it can be the common language of the company. For some, the training might stop at knowing the main KPIs, for others it might expand to gaining knowledge on basic statistics or even switch to a data career. It is beneficial to regularly gather feedback from people on this data journey in order to early identify and address any misunderstanding that might grip the whole process at a later stage. Make sure you support your Data champion and data team, because it is not an easy feat to lead such a transformation. Last but not least, show empathy to everyone, especially to those who seem the most reluctant to change. Find out why they are afraid, reassure them by showing how analytics could add value to their everyday tasks.

Building a data-driven culture however daunting as it might seem at first sight is really as simple as placing your PEOPLE front, center and back. It is a journey for the whole company to embark on, with clear milestones and the ultimate goal always in mind. Start today, take baby-steps, listen to your PEOPLE, hire your DATA Champion, COMMUNICATE broadly and enjoy the ride. Finally, communicate, communicate, communicate.