A data-driven company is an organization that has integrated data analytics into the core of its business processes and uses the insights that gain from this data to transform its processes. Its key characteristics include a focus on automation, continuous improvement and optimization, the ability to anticipate internal and external changes, an adaptive mindset, and above all, a culture that fully embraces data and its potential.
Building data-driven businesses requires more than just integrating business intelligence and hiring data scientists on staff. Fortunately, there are common characteristics of a data-driven organization to be considered by business owners.
10 key steps to achieve a data-driven culture
Proper preparation, evaluation, planning, action, measurement and, above all, communication must be applied to each of the practices that we present below, as they will greatly improve your chances of success.
- Have a robust and mature data technology. A data integration platform is necessary, together with expert capacities in such technologies to support the process.
- Be open to the outside. Take advantage of alternative external data sources and combine them with internal data sources to enrich the data. It is key to learn what other organizations and industries are doing with the data, to broaden the focus and innovate.
- Achieve data fluency. It consists of gathering all the data in a single place, which allows employees and departments to connect and make use of it. Transparency, fluidity, and ease of connection will add value to all departments. All this is achieved by standardizing data, processes, tools and even terms. In this way, information will flow transparently more effectively, and employees will become familiar with the most fundamental part of the data: Where they are and how to use them appropriately.
- Don’t isolate data scientists. It is necessary to expand the functions of this department to the entire company. To do this, new business skills must be created in the organization and there must be a direct relationship between the different parties. The CDO (Chief Data Officer) must become a problem solver with both a business perspective and a data analytics perspective. One example is partnering the CDO with the CFO (Chief Financial Officer) to formally give value to the organization’s information assets to improve data management and benefits.
- Address the cultural change impacts of a data-driven approach. This needs to happen early on, so that the team understands that the change is necessary. Be explicit about how data influences different decision-making styles and communicate the benefits it will bring to employees. Benefits such as saving time, helping to avoid rework, or getting frequently needed information will motivate them and employees will be more proactive when dealing with it.
- Data literacy capacity. A necessary step is to establish specialized training at all levels of the company so that reading, working, analyzing, and discussing data is not a problem. All employees must be able to ‘converse’ with data. Leaders involved in decision making must go further, have coding knowledge, and be conceptually fluent in quantitative issues; especially leaders involved in strategy, who must internalize the expectation that data assets are there to be shared.
- Identify and communicate the business value of data. Information must be measurable to be valued. Metrics must be chosen carefully considering the nature of the data and the end goal of the data. The information must be treated as an asset, being necessary to have a strict control on the origin and the consumption of the data.
- Address the ethical implications of data and analysis. Both internally and externally, it is necessary a code of conduct that defines ethical guidelines for the use of data and analysis. Spend time balancing the benefits of data and analytics with the ethical and privacy risks it poses. Knowing the trust expectations of all parties involved will help not to upset the balance.
- Troubleshoot basic data access problems. It is by far the most common complaint from employees when it comes to obtaining even the most essential information. Don’t let this happen right now and make sure data access within your company works as it should. The democratization of data is the key for the different parties to make decisions based on tangible data, easy to understand and focused on the business.
- Traceability of uncertainty levels. Demand teams to be explicit and consistently report their levels of uncertainty quantitatively. In this way, managers will be able to directly face the possible sources of uncertainty and will be able to rigorously evaluate the reasons for acting in response to them.