If your organization aims to gain greater insights into its business activities, leverage data to create more value, make data and analytics a critical part of your business strategy and decision-making processes, and provide more personalized services to customers, then you’re likely aspiring to become a more data-driven enterprise. However, the question remains, are you ready to take the necessary steps to achieve this goal? This blog post aims to provide you with a solution to this question.
It is no secret that companies who see data as a valuable asset and fully leverage its potential will remain relevant in the coming years. Despite the growing importance of data-driven approaches, many companies struggle to implement them effectively. A few of the obstacles that we have encountered recently include businesses expressing their desire to incorporate data into their decision-making processes but are uncertain on how to begin or which areas to prioritize. Additionally, some companies want to speed up the delivery time of their reports, but are unsure about where to find qualitative data.
The cost of failing to adopt a data-driven approach
There is a lot at stake for companies that decide to not take on a data-driven approach. Can your organization afford to miss the data-driven revolution?
- Being outperformed by competition: With more and more organizations embracing data-driven decision-making and using data as an asset, those who choose not to risk being outperformed by competition and falling behind in terms of innovation.
- Out of control data overload: The volume from all types of data (such as sensory, structured, unstructured, images and voice) increases with the growth and digitalization of your business and its services. Ignoring this growth can result in data being inaccurately used, a limited overview of available data and decision-making opportunities and insights being missed. This becomes more costly to control every year.
- Not meeting customer expectations: Customers expect organizations to use data for more personalized services, to offer real-time insights and drive innovation and sustainability. Choosing to not be data-driven can result in lower customer satisfaction and loyalty.
- Mistrust and inaccurate insights: Without a data-driven approach, organizations risk drawing incorrect conclusions and making poor decisions based on incomplete or inaccurate information.
In general, the consequences of not embracing data-driven decision-making leads to decreased competitiveness, missed opportunities, and lower customer satisfaction.
What does the road look like?
Not every organization needs to start from scratch. The road to becoming more data-driven is different for every organization since it is also about the people, their readiness to change and the data culture. Do you know where your organization stands today and the next steps you should take?
On the road to becoming data-driven the why, how and what are essential. An important step is defining your organization’s data ambition and its related goals. Data ambitions need to be aligned with the current strategy and based on the current state and maturity of the organization. To achieve these ambitions, they need to be translated into a clear way of working using the Target Operating Model (TOM) which contains roles, processes, tools and more. This should be supported by a roadmap of projects that will deploy step-by-step the necessary parts to achieve the ambition. All this needs to be supported by change management to accompany the cultural change and build a data-driven culture. Every step in this road has its own challenges:
- Why: The difficulty here lies in understanding and supporting of the organization. It is not easy to communicate a data ambition and get the right people on board. To support the why, a clearly defined data-driven strategy that includes objectives, metrics and KPIs, and continuously monitoring and improving your data strategy is imperative.
- Where: A data ambition and its potential benefits are often not perceived as a concrete rational by different stakeholders in the organization. Use cases and quick wins are necessary to demonstrate concrete examples and the added value that is created. Performing a pilot enables you to evaluate the TOM in practice and customize and enhance it based on lessons learned.
- Who, what, and how: The responsibilities of delivering understandable and qualitative data are often not well defined. Many employees currently perform data-related tasks without clear roles, processes, and governance. It is important to clearly define which data roles are necessary in the organization and the responsibilities of these roles.
- Data-driven culture: Almost everyone in an organization uses data daily, but often the lack of data literacy and culture obstructs people’s trust and confidence in working with data.
If you find your organization experiencing any of these or other related challenges, it is safe to say that you are not alone.
Ready to follow the road?
When you have a better understanding of the data-driven road ahead, it becomes clear that it is more than just making data more qualitative, implementing tools, and developing a few algorithms. To become more data-driven, several other aspects need to be considered such as the culture of the organization, sponsorship from top leadership and readiness to change. In short, it’s about the people. The road ensures that they understand why, what, and how data-related activities are performed in the organization.
4 lessons learned along the road to data-driven success
Authors: Lucie Delporte and Hanne Gielen
