Artificial Intelligence is an enabler for digitization and data culture within companies.
In the context of digitalization, we often talk about artificial intelligence, and optimizing data-driven decision making. AI has broken into our lives faster on the back of three technological trends, as explained by Future Trends Forum expert Reinier Van Den Biggelaar, managing partner at BastaGroup and data science and AI manager at ORTEC in his remarks during the FTF meeting about the Future of Work:
- Cloud -Edge- Computing: It provides massive data storage and all the computational and processing power needed.
- Open source or open code. This goes beyond programming language, it also includes library and solution building environments, where big tech are promoting their machine learning frameworks, such as Google’s TensorFlow, Amazon’s SageMaker Neo or Microsoft’s Azure AI.
- Speed of telecommunications. Optic fiber and 5G today enable AI executed remotely with basically no wait time and very low latency.
Many companies want to leverage AI solutions, but don’t know where to start. “We must digitalize, we must digitalize” has become a mantra out of a Dilbert cartoon one would say. Reinier explains that changing the corporate mindset is essential: data are essential assets, and we should treat them as such.
Identifying data, knowing where to source them from, clean them, design algorithms to use them, having a clear goal and knowledge to interpret the responses, being capable of creating a virtuous learning circle in the process. Easy to say and tremendously complex to execute successfully. Therefore, data governance is a new discipline, still in its infant stages, but definitely critical in a few years. It must adapt and improve over time, to be effective.
In order to assess a company’s degree of maturity in digitalization, Reiner proposes the framework The 5X10 Data-Driven Maturity Model & Assessment, to check our bearings, are we having analytical problems or are we a data-driven, innovative organization. Digital maturity is defined based on 10 dimensions—all together cover all aspects of digitalization: both technical and organizational capabilities.
Once the digitalization maturity is defined, we can start creating a prosperous data culture where you can:
- understand and
- trust data.
What is a data culture?
A culture is the mix of customs, habits, unwritten rules and symbols that govern behavioral patterns in a company. It guides the thinking, feeling and actions of employees, and therefore, it has impact on each and every decision. A data culture is the set of collective behaviors and beliefs held by people who value, practice and encourage the use of data for better decision-making. As a result, data intertwine with corporate operations, mindset and identity.
How is a data culture developed?
Reinier proposes the 9 E method:
- Engage: explain why and what for is a shift in mindset needed to engage employees.
- Educate: develop employee training, reinforce with specialist profiles. In short, increase data literacy.
- Empower: offer work tools to create dashboards, insights and solutions.
- Enable: create support and learning environments and communities.
- Experiment: start with small projects (learn by doing) with grassroots initiatives. Test, test, test, fail and test again.
- Encourage: create safe learning environments, encourage learning and experimenting.
- Embed: Data are considered essential values, they become a priority.
- Energize: Celebrate and share success.
- Emphasize: keep up the momentum with bootcamps, hackathons, newsletters, etc.
In short, there are a few basics a company must do to truly be digital: first, assess digital maturity, then, define and act based on a data culture appropriate for their activity. Everything starts with the vision and business alignment because Artificial Intelligence is not an end in and of itself, it is an enabler.