Principles of BDM
Why Business Data Management?
Within larger companies, regular data management is organized by the ICT department in order to manage the data stored. Complexity accelerated when data had to be shared among different applications and platforms. Does everyone know the meaning of the data? Do they use it properly? Is data maintained in different places? Do we still have a single source of truth? By focusing on managing the data, there may be a lack of focus on the business itself. Despite the efforts to model the data on a conceptual and/or logical level which can be considered a reverse engineering attempt to model the Business. Lack of focus on and understanding of the business, becomes clear especially when data needs integration on a more corporate business level.
Too often we see that the business semantics are not or insufficiently clear and that IT specialists (business analysts, data analysts, BI experts, etc.) have to do an “educated” guess on availability and meaning of data, resulting in dashboards and other information products of which the quality of the information provided is doubtful and hard to falsify by the business, with great risks for decisions taken based on these information products.
Business Data Management is developed to define and model the business in order to get the semantics of the business clear. Business terms are the centre point of the study, they are discussed by business representatives, named, defined and classified into Business concepts, Business characteristics and in some cases Business characteristic values.
This will result in what sometimes is called a glossary or dictionary, within Business Data Management the term lexicon is preferred. This way a single language for the business is created, that will contribute to and (that is the goal) finally result into:
- A consistent use of terms by business representatives
- Clarity on what the business terms mean and stand for
- Consistency in terms used in policies, documents, folders, website, etc.
- Better understanding of (management) information delivered.
Within a company, the business people are the experts on their business. So Business Data Management really is by the business, for the business. Business has the knowledge and also the ownership and decision making power to set standards in naming and definitions. To get it organised and modelled there may be a (temporary) need for Business Data Managers to support the business. Creating and maintaining the lexicon and the Business Data Model will be a lot of work and will need permanent attention, adjustments and improvements. Because the world does not stand still. Even a bigger job will be to make all people speak the same business language, using this language in a consistent way in documents, folders, website, etc. And of course, the accounting systems used should talk this language too. First in terms of the human interface when entering data and getting the information out. Secondly also the inner world of the accounting systems: the metadata and data maintained should be aligned with the lexicon as far as it is not purely technical. For those Business terms that are used in accounting systems, they are:
- A perfect guideline for naming of data fields in user interface design
- A starting point in developing technical data structures to be used in accounting systems
- The basis for creation of technical names of tables and their data fields, by adding technical abbreviations for business terms to the lexicon.
So that if business looks into the data itself, they recognise what they see and can specify their requirements and specifications (stories) based on the business language. And yes, it is a long way to go for many organisations but the benefits will be enormous.
Conclusions:
- Business in charge
- From the business, for the business
- The lexicon will support a single language for the business
- Lexicon as basis for the Business Data Model
- Implementation within the organisation
- Implementation within accounting systems.
Responsibility of Business
Business Data Management promotes that the business itself is responsible for putting Business Data Management in place and executing it. Data is used all around the company and sometimes even outside the company, so the business should be able to explain what they are doing. Because they:
- have the best knowledge of the business the company is in
- know best if business is changing
- own and know the data
- own and know the metadata, that is: all that is documented on the business.
In RACI terms, the business will have the accountability role. Preferably they also take the responsibility in executing Business Data Management. The IT-department and if there is: a regular Data Management department should at least be consulted.
On data ownership of the business, a side note should be made. A business party may be called “owner” but sometimes that should be considered to be the delegated owner for the company. Like customer data, it is more and more regulated that customers (people) own their own data as administrated for within organisations. The business owner of this data within an organisation will the point of contact for that information for other business parties but will have to comply to regulations to protect the customer data. This may also apply to other data bought for a certain purpose for which an internal business party may be the (delegated) owner.
Normally there is not one single business within a company. One department may be responsible for Sales & Marketing , another one for production, physical distribution, etc. Supportive functions have their own “business” that could be modelled for example HR, Finance, IT, Facility Management, etc. All these businesses are identified and choices will have to be made how and where Business Data Management will be organised.
IT will have a special role. They will have to model their own “business” world in terms of the application landscape, architecture, incidents, etc. Also, they will have to monitor the development of the other Business Data Models within the company (and for that: the business itself) to determine the impact on IT.
Areas of Business Data Management
Business Data Management comprises the following areas:
- Business Data Administration
- Business Data Modelling
- Business Data Process Management
- Business Data Governance
Business Data Management as a method, will give guidelines on these 4 areas. Because all organisations are different, not at the least because people are different, it should be adjusted to the needs and policies of that organisation.
Business Data Administration
Business Data Administration concerns documenting and controlling the Business Data Model.
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Business Data Modelling
Business Data Modelling concerns modelling the “real world” of the business.
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Business Data Process Management
Business Data Process Management concerns setting and maintaining procedures and guidelines for Business Data Management.
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Business Data Governance
Business Data Governance concerns putting the BDM organisation, management and control cycles in place.
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Data Management versus Business Data Management
See the table below for the main differences between regular and Business Data Management.
IT – Data Management
Business Data Management
Focus on managing data
Focus on managing business
Creating models out of data
Creating models from business terms
Based on implementation, the technical world
Based on business itself
Data management to get IT in control
Data management to get business, the enterprise in control
Bottum up approach
Top down approach
Not-automated concepts and data out of focus
Focus on all business terms
Modelling as “finding a solution”
Modelling by analyses of the real world of business
Questions like: “will the data fit in”, “easy to source”, “easy to consume”
Questions like: “is it business language”, “do we all use the same business terms when speaking, in folders, on website, in systems”?
IT trying to make business data clear
Business defining their own business terms as a framework for the data itself
Focus on elementary, atomic data
All business terms relevant and modelled