Data Maturity Scan

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Strategy and control

1. Data strategy

Is there a data & analytics strategy within the organization?*

That is, a document outlining the vision for data & analytics and how it can/should create value for the organization?

No, there is no data & analytics strategy

No, there is no central data & analytics strategy, but some departments or teams do have their own data & analytics strategy.

Yes! There is a data & analytics strategy, but it is still largely isolated and not integrated with the business strategy

Yes! There is a data & analytics strategy and it plays a guiding role in the business strategy

2. Responsibility

How is responsibility for realizing the data & analytics strategy invested?*

This responsibility is not specifically invested

This responsibility is vested in specific individuals at the operational level

Responsibility is invested at the management level

Responsibility is invested at the board level

3. Steering

To what extent is the organization governed by data?*

Our organization (manages) primarily by gut feeling and experience

Our organization (manages) based on predefined KPIs

Our organization (manages) based on data in tactical and operational decisions

Our organization (manages) based on data in strategic, tactical and operational decisions

4. Value of data

In general, how does the organization consider the value of data?*

We are not convinced of the value of data

We are convinced of the value of data, but cannot always demonstrate it

We are regularly able to demonstrate the value of data

Data is seen by us as a strategic asset and is on the balance sheet

Man

5. Analysis skills

What type of analysis work do employees in analysis roles perform?*

Mainly descriptive analysis and reporting (what do we see happening)

Descriptive and predictive analyses (what do we anticipate will happen)

Descriptive predictive and prescriptive analyses (how can we anticipate what may happen)

Descriptive, predictive, prescriptive analyses and optimizations (what is the best scenario for upcoming events at that time)

6. Soft skills

What role do analysts play within the organization?*

One-stop shop for information and insights

They question or substantiate decisions or ideas of others

Are an equal advisor and sparring partner to others in the company with their knowledge and expertise

They direct (and thus help determine) operational, tactical and strategic choices of the organization

Business

7. Data & analysis knowledge

What is the level of knowledge within the organization regarding data & analytics?*

People do not know what data & analytics can do for the organization

People see added value, but there is insufficient knowledge to capitalize on it

One sees the added value and one has sufficient knowledge and expertise to deploy it regularly

Data & analytics is in our organizational DNA and there is sufficient knowledge and expertise to leverage the added value

8. Data & analysis application

How is the organization using data & analytics?*

People use available reports

People have access to dashboard from which they can extract their own information

People have access to dashboards from which they extract their own information and they are closely involved in creating analyses

People have access to dashboards from which they extract information and make their own analyses

Organization

Structure

9. Suspension in organization

In what way are the data & analytics activities organized?*

There are loose data & analytics activities, not invested in specific teams or departments, with no central direction or direction

There are decentralized data & analytics departments or activities

There is a central data & analytics department

There is a combination of central and decentralized data & analytics departments and there is central control or direction

10. Roles, tasks and responsibilities

How is responsibility for realizing the data & analytics strategy invested?*

This responsibility is not specifically invested

This responsibility is vested in specific individuals at the operational level

Responsibility is invested at the management level

Responsibility is invested at the board level

Culture

11. Innovation

What role does data & analytics play in innovation?*

Data & analytics is used only to improve, not to innovate

Data & analytics is used on an ad hoc basis for the purpose of innovation

Data & analytics are a structural part of innovation projects

Data & analytics are the drivers of new business models

12. Data-driven work

Is data-driven work encouraged within the organization?*

Data-driven work is not actively encouraged by management and board

Data-driven work is sometimes encouraged by management and board of directors

Data-driven work is (almost) always encouraged by management and board of directors

There is no need to drive data-driven work; it is automatic and in our DNA

Processes

Workflow

13. Analysis Process

Is there an established process and roadmap for setting up (or having set up) an analysis?*

No, there is no established process

There is an informal process

There is a formal, established process to which everyone adheres

There is an established process that is continuously optimized

14. Data accessibility

How accessible is data for analysis purposes?*

Data is hardly accessible, if at all

The most relevant structured data is available in analysis environment

Unstructured data is also available for analysis purposes, only in a different environment than the structured data

Both structured and unstructured data are accessible in one environment for analysis purposes

Implementation

15. Application of analysis results.

How easily can the analysis results and advice be used/applied?*

The applicability is limited, much work is afterwards for nothing

We find this difficult: a lot of precious time is lost, we often lose momentum

We think carefully about implementation in advance and often succeed in applying analytics

There is a functioning process to implement analysis results

16. Insight-based decisions

What role does data & analytics play in decision-making processes?*

Data & analytics plays no role

Data & analytics are used in retrospective evaluation

Data & analytics are used in underpinning ex-ante and ex-post evaluation

Data & analytics are primary drivers of decisions

Resources

Data

17. Data availability and quality

Is there enough data available of good quality?*

We do not yet have enough data of sufficient quality

We have (a lot of) data, but usability is limited and quality is low

We have sufficient qualitative, usable data within our organization

We have sufficient qualitative, usable data within our organization, and in addition to internal data, we also have access to relevant, qualitative external data sources

18. Data governance & privacy

How do you describe the state of Data Governance in the organization?*

We do not yet have developed policies and guidelines on data governance

There are some procedures in the areas of data storage, quality, security and use, but the scope and procedures are not yet complete

There are clear rules and agreements on data storage, quality, security and use, and the scope is virtually complete

Data governance is integral, contributing to the value of data & analytics to the organization

Engineering/Infra

Data architecture 19.

What does the data architecture look like?*

In particular, the data architecture is designed for primary processes

The data architecture supports the ability to do analysis

Data architecture covers both structured and unstructured data

Data architecture facilitates the possibility of an integrated customer view

20. Analysis tooling

To what extent does the analysis tooling meet the need ?*

Bad: We work primarily with excel-like tools

Moderate: we have a limited set of traditional analysis tools that we have to work with

Good: We have a wide palette of traditional and/or modern -open source- analysis tools that serve our current needs well

Excellent: We have a wide palette of traditional and/or modern -open source- analysis tools that serve our current needs well and are also flexible in deploying analysis tools to meet future needs as well

Overall Score Strategy & Steering

Total score Human

Total score Organization

Total score Processes

Total Score Resources

Overall score Overall

You are at the beginning of data-driven work. The road to an organization that can achieve its goals through data is complex and challenging, and we recommend building this route step by step, with attention to people, organization, processes and resources.

You (re)recognize the potential of data for your organization and you have taken the first steps to start working data-driven. However, the necessary development in all 5 pillars is still lagging behind. It is our experience that at this stage of the process a clear goal and focus are especially important, as well as doing relevant pilot cases to demonstrate the value of the activities.

Your organization is well on its way to successfully becoming data driven. Experience shows that it is now especially important: 1. to balance the development in all 5 categories, 2. to continue to demonstrate the value of data in general by means of (pilot) cases, and 3. to keep stakeholders involved across the organization. Continued development of data-driven activities is now key to success.

You organization already works at a relatively high level data-driven. The main thing now is to ensure that all the pillars of data-driven work further reinforce each other. Data and analytics guide your organization.

Strategy and control.

This pillar is the starting point for success. Working on the strategy and governance pillar means thinking about and working towards an organization-wide conviction about the value of data, a clear and supported picture of how to get there, a clear responsibility for this and a concrete interpretation of how to manage this. It is important that the entire organization is convinced of the value of data, knows why data has value to the organization, how it can be accessed, and what behaviors or applications go with it.

Human.

People are our most important capital. The right people in the right place ensure the realization of organizational goals, as well as employee motivation and happiness. Also, people with the right knowledge and competencies know how to ask the right questions and can be a catalyst for data-driven work.

Organization.

Organizational structure must facilitate and facilitate data-driven work. Data-driven culture is determining driver for success. After all, the workforce is the most important capital.

Processes.

Processes are important agreements about proven or desired effectiveness and efficiency of collaboration within your organization. A good process (Way of Working) ensures that data and analytics within the organization deliver the desired quality and results.

Resources.

Availability of proper and sufficient resources (tools, data, systems, etc.) is necessary to deliver the desired quality and can motivate and inspire innovation. Lack of proper resources is an impediment to achieving organizational goals.

All questions have been answered. The results give you insight into the data maturity of your organization and the first recommendations for making steps in this area. Of course we are happy to help. Leave your contact details below and you will receive an email with a link to the results. Fields marked with an asterisk * are required.

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Industry (old)

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Industry (SBI).

Company size*

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