Business Processes Modeling – Another Responsibility of Data Stewards

By Anne Smith

Along with a deep understanding of the data and meta data, data stewards must thoroughly understand the business processes needed for optimum performance. An excellent way to gain this understanding is to carefully and completely model business processes and the relevant data.  Business processes represent the flow of data through a series of tasks that are designed to result in specific business outcomes.  They are an important component of a data steward’s responsibility, and stewards should understand the fundamentals of modeling processes as well as data.

 

What Is a Business Process?

A process is a coordinated set of activities designed to produce a specific outcome. There are processes for saving a file, constructing a building, and cooking a meal. In fact, there is a process for almost everything we do. A business process is a type of process designed to achieve a particular business objective.

Business processes consist of many components, including:

  • The data needed to accomplish the desired business objective 
  • Individual work tasks that manipulate, review, or act upon the data in some way
  • Decisions that affect the data in the process or the manner in which the process is conducted
  • The movement of data between tasks in the process 
  • Individuals and groups that perform tasks

Processes can be manual or automated, fully documented or simply knowledge in the minds of one or more people. They can be simple or complex. They can be formal, requiring exact adherence to all details; or flexible, provided the desired outcome is achieved.

 

Logical Process Modeling

Logical Process Modeling is the representation of a business process, detailing all the activities in the process from gathering the initial data to reaching the desired outcome. These are the kinds of activities described in a logical process model:

  • Gathering the data to be acted upon 
  • Controlling access to the data during the process execution
  • Determining which work task in the process should be accomplished next
  • Delivering the appropriate subset of the data to the corresponding work task
  • Assuring that all necessary data exists and all required actions have been performed for each task
  • Providing a mechanism to indicate acceptance of the results of the process, such as electronic “signatures”

 

All business processes are made up of these actions. The most complex of processes can be broken down into these concepts. The complexity comes in the manner in which the process activities are connected together. Some activities may occur in sequential order, while some may be performed in parallel. There may be circular paths in the process (a re-work loop, for example). It is likely there will be some combination of these.

The movement of data and the decisions made that determine the paths the data follow during the process comprise the process model. The logical process model contains only business activities, it uses business terminology (not software acronyms, technical jargon, etc.…), it completely describes the activities of the business area being modeled, and is independent of any individual or position working in the organization.   Like its sibling, Logical Data Modeling, Logical Process Modeling does not include redundant activities, technology dependent activities, physical or systems limitations or requirements.  The process model is a representation of the business view of a set of activities under analysis.

Heretofore, many applications and systems were built without a logical process model or a rigorous examination of the processes needed to accomplish the business goals.  This resulted in applications that did not meet the needs of the users and / or were difficult to maintain and enhance.  Stewards can participate in the development of logical process models to improve the understanding of the organization’s activities and relate those activities to the relevant data.

Problems with an unmodeled system include the following:

  • Not knowing who is in possession of the data at any point in time
  • Lack of control over access to the data at any point in the process 
  • Inability to determine quickly where in the process the data resides and how long it has been there
  • Difficulties in making adjustments to a specific execution of a business process
  • Inconsistent process execution

 

Logical Process Modeling

Logical process modeling methods provide a description of the logical flow of data through a business process. They do not necessarily provide details about how decisions are made or how tasks are chosen during the process execution. They may be either manual or electronic, or a combination of methods. Some of the logical modeling formats are:

  • Written process descriptions
  • Flow charts
  • Data flow diagrams
  • Function hierarchies
  • Real-time models or state machines
  • Functional dependency diagrams

 

A function is a high-level activity of an organization; a process is an activity of a business area; a sequential process is the lowest-level activity.  Therefore:

Functions consist of Processes.  Functions are usually identified at the planning stage of development, and can be decomposed into other functions or into processes.  Some examples of Functions would include: human resource management, marketing, and claims processing.

Processes consist of Sequential Processes.  Processes are activities that have a beginning and an end; they transform data and are more detailed than functions.  They can be decomposed into other processes or into Sequential Processes.  Some examples of Processes would be: make payment, produce statement of account, and verification of employment.

Sequential Processes are specific tasks performed by the business area, and, like a process, transform data.  They cannot be further decomposed.  Examples of Sequential Processes are: record customer information, validate Social Security Number, and calculate amount due.

Each business activity in a logical process model is included in a decomposition diagram, given a meaningful name and described in detail with text.  As in Logical Data Modeling, naming conventions are quite important in process modeling.  Names for processes begin with a verb and should be as unique as possible while retaining meaning to the business users.  Nouns used in the activity name should be defined and used consistently. In a decomposition diagram, each level completely describes the level above it and should be understandable to all appropriate business users.

 

Data-Driven Approach to Process Definition

This approach, most commonly used in relational and object-oriented analysis efforts, analyzes the life cycle of each major data entity type.  The approach defines a process for each phase or change the data undergoes, the method by which the data is created, the reasons for the change and the event that causes the data to achieve its terminal state.  This method assures that all data actions are accounted for and that there are meaningful associations between the data and its processes.  However, in a data-driven method, the logical data model must be completed before the process modeling and analysis can begin.

Major points of interest in constructing a Logical Process Model are:

  • The purpose of the process: Writing the purpose and referring to it frequently enables the analyst to recognize a step in the process that does not make sense in the context of the process. 
  • Who will participate in the process: The participants may be people, groups of people, or electronic applications.
  • The order in which the steps of the process are done: Order in a process model is essential, and is one of the main ways a process model differs from a data model.
  • The data you expect to be included in the process: There is an initial set of expected data, plus you should know what data you expect to be modified or added during the process. Part of this step is deciding which subset of the data is appropriate at each task in the process. 
  • Decisions that will be made during the execution of the process: These include decisions about which path the process should take, and whether all the required data is present at any given point in the process.
  • The rules you will use to define the various parts of the process: Also, note any naming conventions that are important for the business.
  • The disposition of the data at the end of the process: That is, will the data be retained or deleted? If you plan to store the data, where and in what form will the data be kept? Do future process-related reports need to access the data?

 

The more complete the model, the easier it will be to implement an accurate representation of the business area responsibility for the stewards, and the more successful the organization will be in achieving its goals.

Process definition also helps an analyst or steward know when a process should be broken into smaller, sequential processes (tasks). If the definition of a process is ambiguous or lengthy, it is usually a candidate for decomposing into sequential processes.  All functions are decomposed to processes, and all processes are ultimately decomposed into sequential processes/tasks.

A good check of the accuracy of any model is to simulate it by walking through the process manually. This allows the analyst and steward to locate any points in the processes that are not valid before system construction.

Once the process has been successfully simulated, review the results with the appropriate data stewardship team and leaders who understand the expected results from each function and process. This verification step allows the business representatives to understand the process and to confirm the validity of the process and data.

 

Summary

Like Logical Data Modeling, Logical Process Modeling is one of the primary techniques for analyzing and managing the information needed to achieve business goals.  It is important that data stewards understand the concepts of Process Modeling, the methods used in process discovery and definition, and participate by relating and explaining the data and processes used by a business area.  Properly performed, logical process modeling can greatly assist the organization in their efforts, producing functional business processes and appropriate data for use across the enterprise.

About the Author

Anne Marie Smith is a leading consultant in Information Management and is a frequent contributor to various IS publications. Anne Marie has over 20 years experience in information management for several corporate entities and has successfully led the development of data resource management departments within corporations and consulting organizations. Anne Marie is active in the local chapter of DAMA and serves on the board of directors of DAMA International, and is an advisor to the DM Forum. She has been an instructor of Management Information Systems (MIS) with Philadelphia, PA area colleges and universities. Anne Marie has taught topics such as: data stewardship and governance, data warehousing, business requirements gathering and analysis, metadata management and metadata strategy, information systems and data warehouse project management. Anne Marie’s areas of consulting expertise include metadata management including data stewardship and governance, information systems planning, systems analysis and design, project management, data warehouse systems assessment and development, information systems process improvement and information resource management/data resource management. Anne Marie holds the degrees Bachelor of Arts and a Master's of Business Administration in Management Information Systems from La Salle University; she has earned a PhD in MIS at Northcentral University. She is a certified logical data and process modeler and holds project management certification. Anne Marie can be reached at amsmith@ewsolutions.com

 
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