We believe that data lies in the center of all the business activities.

In any company, every department deals with data on a daily basis. It is being produced, analyzed, exchanged, and in the end delivered to the stakeholders. Thus all decisions made within your company are based on data. Knowing its potential, and using it in a correct way is the key to an effective business.

In your quest to take control over its data and information resources you need to first answer 3 key questions:

WHY?

Data management empowers the effective operation of the data and information value chain.

In order to survive in the long run, a business needs to ensure a steady profit and proper asset management. Information and data are the resources that can empower decision-making and help measure the company’s performance. Delivery of required data and its transformation into meaningful information forms the data and information value chain.

WHAT?

The definition and the scope of data management can vary. It depends on the company’s culture, needs, and resources. Each company needs to specify their understanding and the scope of data management.

We have developed a new (meta)model of data management: the “Orange” model. This model delivers a collection of techniques and templates for practical establishment of the data management through design and implementation of data and information value chain, enabled by a set of data management capabilities.

The “Orange” Model of Data Management

DATA & INFORMATION VALUE CHAIN

CORE DATA MANAGEMENT CAPABILITIES

Data management framework

Data management modelling

Information architecture

Data quality

SUPPORTING IT CAPABILITIES

Application architecture

Technology architecture

Data lifecycle management

Infrastructure management

OTHER SUPPORTING CAPABILITIES

Security

Project management

Change management

Audit

Business architecture

Business process management

The “Orange” model can be applied for:

  • maturity assessment of data management

  • design and implementation of a data management strategy and/or roadmap

  • design and implementation or optimization of a data management function

  • design and implementation or optimization of the value chain and core data management capabilities

  • design and implementation of data management/governance roles

  • performance assessment of data management

You can read more about our model in The “Orange” Model of Data Management. Click HERE to learn more about this book.

HOW?

We have developed a practical methodology that we call “the Data Management Star”. It provides a universal solution for successful implementation of data management function in any company, regardless of its industry, size or resources.

  • PREPARATION. DEFINE THE MAIN BUSINESS DRIVERS FOR SETTING UP DATA MANAGEMENT.

    The key success factor of each data management implementation is to make it feasible. The specification of key business drivers allows narrowing the scope of a data management initiative.

     

  • STEP 1. DEFINING NEEDS AND REQUIREMENTS.

    Specific to data management, each of the business drivers deals with a particular set of data. Most companies would start with customer data as it is the most critical one.

     

  • STEP 2. DIVIDING TASKS AND RESPONSIBILITIES.

    In this step, data governance comes to the scene. You will set up a data management framework by:

    • specifying the place of data management function in the organizational structure
    • designing policies, processes, tasks, and roles, etc.

     

  • STEP 3. BUILDING THE DATA MANAGEMENT FUNCTION

    There are several questions you will need to answer as a result of implementation of the data management function:

    • What information do data stakeholders need and why do they need that information?
    • What is your data?
    • Where is your data located?
    • Which transformations does the data undergo on its way from the original source to the end-user?
    • What is the required quality of your data?

    The design of the function strongly depends on the business drivers. During this step, you deliver all required data management sub-capabilities specified in Step 1.

     

  • STEP 4. INTERMEDIATE ASSESSMENT AND GAP ANALYSIS.

    At a certain point in your implementation, you need to perform an intermediate audit. Its purpose is to ensure that the work you have already completed complies with the original plan.

     

  • STEP 5. SETTING UP NEW GOALS AND PLANNING NEW ACTIONS.

    The data management star method is iterative by its nature. You can perform iterations

    • within each step
    • between steps
    • of all steps when you focus on a different business driver.

     

    If you’ve reached this step, it means that you are ready to extend your data management function to meet the requirements of new business drivers.

Our methodology is described in full detail in The Data Management Toolkit . Click HERE to learn more about this book.