Developing a data strategy is a three-step process. We start by assessing your organization’s current data maturity, or the degree to which your organization makes effective use of its data. Together with decision-makers in your organization, we then determine your desired data maturity, or how you would want to use data in the ideal case. Finally, we develop a data strategy that outlines which investments are required to bridge the gap between your current and your desired data maturity. In addition, we offer the services for executing this data strategy.
Assessing your current data maturity
The first step in developing a data strategy is assessing your organization’s current data maturity. Data maturity is the extent to which an organization effectively uses its data to support decision-making. Here are some examples of questions we would seek to answer in a data maturity assessment, in collaboration with stakeholders and data professionals from your organization:
- Which use-cases are you working on? How do they advance your business strategy? Do you have adequate data for these use-cases?
- Which technology do you rely on to collect and process data and make them available to your analysts?
Determining your desired data maturity
The second step in developing a data strategy is determining your desired data maturity. We think it’s important to spell out this vision in high-ROI business problems that advance your business strategy. Drawing on more than 16 years of experience working on data projects, we will collaborate with stakeholders in your organization to generate and estimate the business value of potential use-cases for the different domains you operate in.
Bridging the gap between your current and your desired data maturity
The next step consists of creating a roadmap that prescribes specific investments for bridging the gap between the way you currently use your data and your vision of how you want to work with data. Some examples of recommendations are the following:
- You may want to be able to react quicker to events. This may require a data platform that automatically collects data and processes them fast, such that they are available on-demand to your analysts. This will probably also require increased storage capacity. It will often make sense to run your data operations on the cloud, as this removes the need for investment in physical servers and reduces operational costs. It’s also the most future-proof strategy, as extra computing power and storage capacity are only a few mouse-clicks away. An additional advantage is that it will likely reduce your ecological footprint.
- You may already employ people who can extract insights from data, but it will still be worth the investment to raise the data literacy of other employees through trainings. This can be accompanied by change management to nurture a habit of relying on data for making decisions. Read about trainings we have delivered for, among others, Voka, Solvay, and NCOI.
Making the transition to a data-driven organization
Embarking on a journey to become more data-driven will result in faster and better decisions. Your starting point should be a data strategy. We can develop this data strategy, but also execute it.
Read about how we helped Unigro become an Intelligent Data-driven Organisation.
Our data strategists know how to make an organization data-driven, appreciate the needs of data engineers, data scientists, business analysts, and higher management, and prioritize your organization’s business objectives. We can staff your organization with:
- Data project managers who deliver a data product.
- Data team leads who manage people who work with data or data strategists in interim coaching roles. Read about how we organized people and stakeholder management at Argenta.
- Data Tribe leads or Chief Data Officers