How To Become a Data-Driven Organization

1. Which capabilities do organizations need to become data-driven organizations?

The data-driven organization is not a new concept. Put simply, any business that is making business decisions based on facts, rather than based on gut feelings, opinions, and emotions, is a data-driven company. In a data-driven organization not only senior management makes data-driven decisions, but all decisions at all levels are made based on facts. It is therefore about strategic decisions: “are we extending our services to another industry?”, Tactical decisions: “are we hiring this applicant?”, and operational decisions in the workplace: “are we giving this customer a discount?”

Data-driven organizations make sound decisions in a continuous data-driven business cycle. This cycle requires the following three capabilities:

1. Tech-savvy (Data creation & integration): Ability to create and collect all relevant digital data, and integrate and structure this data into information.
2. Data fluency (BI & Analytics): Ability to deduce intelligence & insights from data & information.
3. Data literacy (Decision management): Ability to make decisions & formulate actions based upon intelligence & insights.

Figure 1: data-driven business cycle with the required capabilities.

Most organizations face difficulties in meeting the technical and organizational requirements to become a data-driven entity. Gartner forecasted that 80% of companies would address their lack of proficiency in data literacy by 2020. Many organizations now recognize this and are starting to change their perspective towards data and analytics. They are beginning to understand that data and analytics can be a significant factor in creating value and shaping business strategies for data-driven businesses. One example is H&M Group’s data mesh journey, a domain-based approach to setting up data architecture within the company.

Tech-savvy capability

Without a big data & analytics platform, the organization is literally driving with blindfolds. Yet qualified people with expertise on the cloud, big data, and data science are scarce and hard to get. And it’s even harder to keep them because a high salary and job security are not enough to keep them satisfied. And even if they are staying with you, they need constant adaptation and learning.

Data fluency capability

Like being fluent in a language, data fluency enables people to express ideas about data in a shared language. In a business context, data fluency connects employees across roles through a set of standards, processes, tools, and terms. Data fluent employees can turn piles of big data into actionable insights because they understand how to interpret it, know the data that is and isn’t available, as well as how to use it appropriately.

Data literacy capability

Data literacy is the ability to read, work with, analyze, and argue with data. Much like literacy as a general concept, data literacy focuses on the competencies involved in working with data.

Every employee on all levels needs technical skills. But being tech-savvy is not enough, soft skills are far more important. Two kinds of soft skills, in particular, are essential:

1. critical thinking skills: agility, collaboration, creativity, and problem-solving
2. business skills: communication, negotiation, leadership, project management, planning, delegation, time management, privacy, and ethics.

But the most crucial success factor is the right mindset: Have an open-minded growth mindset (instead of a fixed mindset). Every employee must be accountable for his own success and learning journey. By far the biggest challenge and learning curve is for senior management. Data-driven businesses increase transparency, and transparency reduces power. If that isn’t threatening enough, the rise of Artificial intelligent driven automated decision making is potentially degrading managers from drivers behind the wheel to guiding passengers.

2. Strategic roadmap towards a data-driven enterprise

All three capabilities must be developed and maintained guided by an overarching strategic roadmap towards a data-driven culture. Building a data-driven enterprise is not just about encouraging the use of data in decision-making. Data and analytics leaders must lead the development of the correct competencies and rebalance work to be consistent with their enterprise’s ambitions for generating information value.

A common mistake that organizations make trying to develop a data analytics capability is to hire brilliant data engineers and scientists, let them experiment, and hope for the best. This will surely not lead to analytic solutions that are embedded in the organization and deliver sustainable business value. Don’t treat data and analytics as supportive and secondary to your business initiatives.

First, develop an Enterprise architecture, and let that be the blueprint for further development of the existing data analytics platform. This approach will ensure that the business strategy is aligned with the technical capabilities and actionable insights lead to actions that improve strategic objectives.

Digital transformation is a human transformation: it is not a technological program but a strategic roadmap towards a data-driven culture. Therefore you’ll need an Integral Data-Driven educational and onboarding program’ that is measurable, personalized, affordable and rapidly scalable. Bear in mind that talent is always the constraining factor. There are three crucial factors for every person to make a successful data-driven learning journey:

1) Ambition: The desire and will to change
2) Ability: the skills and knowledge to learn
3) Allowed: the perception that change is supported and permitted

Figure 2: Strategic roadmap towards a data-driven culture

The Strategic roadmap towards a data-driven enterprise consists of two phases:

1. ROADMAP PHASE
2. CHANGE PROGRAM PHASE

ROADMAP PHASE

Start with an organizational assessment that analyses the drivers and impacts of the transformation on the organization, assesses the preparedness of the organizational entities to adopt the transformation, and assess the “people and organizational” risks associated with the transformation. Align the business strategy with an integrated data-driven transformation strategy.

CHANGE PROGRAM PHASE

The change program consists of five iterative steps:

1. CHANGE PLAN
2. AWARENESS
3. EDUCATION
4. LEARNING & EMBEDDING INTO ORGANISATION
5. PEOPLE ANALYTICS & TRANSITION MONITORING

CHANGE PROGRAM

Develop an integral change program that is optimally tailored to the employee’s level of knowledge and business situation. Use the concept of ‘Education as a Service (EAAS)’ as a framework. Customize and personalize training courses, where possible and needed. Sometimes online learning works best, in other cases team learning is more effective.

AWARENESS

Creating awareness through storytelling and learning journeys. Active commitment and communication of higher management is a key success factor.

LEARNING & EMBEDDING IN ORGANISATIONAL CULTURE

Cultural reinforcement is created by training on the job, apply what’s learned in practice and a continuous feedback loop. Coaching should focus on the three personal success factors: Ambition, Ability and Allowed.

PEOPLE ANALYTICS & TRANSITION MONITORING

Control the learning transition by making the transition data-driven. Develop a BI & Analytics system to monitor the personal learning journey of every employee, as well as monitoring the crucial transition drivers.

CONCLUSIONS

The journey to become and thrive as a data-driven organization is a data-driven human transformation. This transformation is linked with business vision and strategy. Manage the cultural transition with an integral data-driven educational & onboarding program. Monitor the learning journey with people analytics. Focus on the sustainable learning of technical as well as soft skills. Allow room for experiments. Start today. Learning is fun!