The [BEBR] Approach

Although in many cases a lot of data is already collected, most companies struggle to find value in it. BEBR has an extensive track record in helping companies starting using data-driven insights, and in our experience it helps to start small. We start with a specific use case and together with the involved people we make sure that the new data insights can be directly used in practice by defining the key performance indicators together with the end-users.

Choose your starting point:

I am new to data

I have a specific use-case

In 3 steps towards working data driven

1. IT & Data Architecture analysis

By mapping the complete IT architecture and the corresponding data we can determine the current status of the data infrastructure and discover the right opportunities:

• What are the opportunities when it comes to working data driven?
• Which business processes are now supported by sufficient data?
• What are suitable data driven use cases?
• What are the red flags? Which software is outdated or has security risks?
• What are recommendations for data driven working for the future?

2. Inventarisation of the business processes & use case selection

Combining the knowledge of your business and our knowledge of data we select a use case with a high business potential. We involve the actual users of the insights in your company so that we create maximum value. Together we define the KPIs to verify the outcomes of the next phase:

• Use case: better plan your personnel for the coming year.
  What was the average sick leave over the past years and what will be the sick leave for next year?
• Use case: turn the right knobs to improve your margin.
  What are the current drivers of your profit and what are the underlying (possibly still to discover) drivers?
• Use case: always have the right stock and reduce the costs on inventory.
  What's the upcoming prediction for demand based on historical data combined with the relevant external sources?

3. Data Selection & Proof Of Concept

We annotate the right data for the use case and develop a Proof of Concept. We work using an Agile process where we check the value of our findings with you and adapt if needed. Without investing in building a complete data architecture we first check if the Proof of Concept indeed works by verifying the outcomes in practice together. Example questions that (if relevant for specific case) could be answered:

• Can we indeed determine the average sick leave?
• Can we indeed determine the past demand of a product?

Continue with Data Driven Insights

When your organization benefits from the insights of the Proof of Concept we can continue with further integrating data driven insights. Based on the results of step 1 to 3 we have a clear view on how to continue improving your business with data:

• Which steps can be taken to integrate and automate data driven insights?
• How can AI support your business?
• What external sources could enhance your data?
• Roadmap & future recommendations

In 3 steps towards validating your use case

1. IT & Data Architecture analysis

Based on the specific use case we analyse the corresponding IT & Data Architecture:

• Which data is needed for this use case and what external sources might be relevant?
• Is the available data from the current IT & Data Architecture sufficient?
• What are the red flags? Which software is outdated or has security risks?
• What are recommendations for data driven working for the future?

2. Inventarisation of the business processes & use case definition

By combining the knowledge of your business processes and our knowledge of data we investigate the corresponding business process. We involve the actual users of the insights in your company so that we create maximum value. Together we define the KPIs to verify the outcomes of the next phase.

3. Data Selection & Proof of Concept

Together we select and annotate the right data for the use case and develop a Proof of Concept. We work using an Agile process where we check the value of our findings with you and adapt if needed. Without investing in building a complete data architecture we first check if the Proof of Concept indeed works by verifying the outcomes in practice together.

Continue with Data Driven Insights

As soon as your organization benefits from the insights of the Proof of Concept we can continue further with integrating data driven insights. Based on the results of step 1 to 3 we have a clear view on how to continue improving your business with data:

• Which steps can be taken to integrate and automate data driven insights?
• How can AI support your business?
• Roadmap & future recommendations