“You’re the person to get this done, good luck!”, and with that, you leave the boardroom. You’ve just been appointed to lead the organization in its journey to become more data-driven. Fully motivated, you go back to your desk, get comfortable and re-open your laptop to start building a data-driven organization. Next, you open ChatGPT (or Google), as many journeys start today, and man it’s your lucky day! You’ve not only been appointed leader for the data transformation, but you just asked ChatGPT for assistance and they’ve provided tons of examples of critical success factors, frameworks and methodologies. These are all textbook answers on how to begin a data transformation so we won’t focus on these aspects. Instead, we will share some lessons that we’ve learned from our hands-on experience of helping build data-driven organizations.
Build a collaborative culture
The best ideas are exchanged during coffee breaks, right? We cannot underestimate the power of bringing people together. A key aspect of becoming more data-driven is creating a collaborative culture that encourages transversal teams and breaks down departmental silos, ensuring that everyone has easy access to the data they need to make informed decisions. Independent of the organization, we have learned from experience that collaboration happens best when people begin to understand what they can learn from each other. This is achieved best by organizing regular (less formal and enjoyable) get-togethers where people can talk about data-related initiatives they have taken and challenges they are facing. When the ultimate goal is to inspire each other and create a community feeling, data success follows naturally.
Middle management is the glue
Unless a plan of action is made by management, commitments to become more data-driven can only be hopes and dreams. Whilst senior management is inherently skilled at driving change and championing a data vision, we’ve noticed the challenge of actioning a commitment often lies in getting the necessary involvement of middle management. We have therefore shifted focus in our approach towards middle managers, since they play an essential, but often under-recognized, role in leading the data change and building a data culture. It is important for middle management to fully comprehend the added value of becoming more data-driven. One way to do this is by developing concrete initiatives that are of tangible and beneficial value to them. If you can get them onboard, they are likely to be the best evangelists to further build and spread a data-literate culture across the organization. Change is never easy, but overcoming the hesitations and worries of middle management will most likely result in the transformation being more easily embraced, which will accelerate the success in the long run.
Don’t be afraid to make a pit stop
As with any new initiative, it's important to continuously measure the effectiveness of data-driven decision-making. Agility is the buzzword that is currently taking the world by storm. In the journeys we’ve taken with clients to become more data-driven, we’ve found it is essential to adapt (when needed) and take a step back to assess the challenges faced along the way. It’s not necessary to have a perfectly defined target operating model in place pre-transformation. Having an initial guideline is enough to begin putting theory into practice. Believe it or not, dealing with the often rare challenges the moment they occur is more efficient than trying to anticipate them at the very beginning. If you do this, you will likely lose yourself and others in time consuming discussions about hypothetical futures. Practical learning and adaptation will always be more beneficial than theory and forecasting.
Don’t accelerate because everyone is moving fast
Life is a marathon not a sprint, so it’s important to pace yourself. Keep this in mind when trying to unlock the power of being data-driven. Don't rush into buying the most advanced data tools or trying to build complex artificial intelligence (AI) solutions when your organization is not ready. Starting with the basics is often the best approach. Reflect on your top use cases and what data products you really need to run and grow your business. Ensure that the data decisions you make are based on what the business really needs. Don’t go for predictive models or automated decisions if your employees are still adjusting to taking more data-driven decisions. Make sure you have a set of ‘engagement rules’, processes and clear governance. Invest in training and establish a solid but fit-for-purpose data architecture. If the foundation is solid, then the tower can be built higher.
Are you ready to embark on the often bumpy but very exciting journey of becoming data-driven? Then let’s go! Don’t forget to enjoy the journey, because it’s just as fun and rewarding as the end goal!
Authors: Julie Verheye and Gauthier Dejonckheere
