Data Management Optimisation – Reengineering master data processes using lean techniques

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Master Data Process Reengineering using VSM Some of the greatest challenges that have daunted digital organizations since time immemorial are: optimization of processes & optimization of IT capacity. As the organizations grow more and more complex, another challenge has been added to the list: optimizing data.  Typically, the IT landscape of an organization these days […]

Master Data Process Reengineering using VSM

Some of the greatest challenges that have daunted digital organizations since time immemorial are: optimization of processes & optimization of IT capacity. As the organizations grow more and more complex, another challenge has been added to the list: optimizing data. 

Typically, the IT landscape of an organization these days consists of complex set of disparate systems and technologies, including CRM, ERP, SCM etc. This complex, fragmented environment of disparate systems and applications creates proliferating islands of information. These islands result in duplicate, incomplete and inaccurate data that leads to inappropriate analytics and, ultimately, inaccurate business decisions. Achieving a ‘data lean’ organization is hence the need of the hour. For this purpose, companies now take special care of their master data. Implementing master data management or governance is now as essential as any other ERP system. Processes for creating, reading, updating and deleting (CRUD) master data often require special attention due to the critical nature of the data. However, despite best efforts, it is not uncommon for inefficiencies, often termed as ‘wastes’, to creep into any process. Elimination of such digital waste is crucial for improving quality and efficiency within the organization.
 

Value Stream Mapping (VSM)

Value Stream Mapping (VSM) is one of the ways of identifying the wastes, in accordance with the lean principles. It graphically displays the process steps and the flow of work items and information involved in an end-to-end process, starting with a requestor raising a demand and finishing with the demand being fulfilled.  It helps organization to clearly differentiate between the value-add and non-value-add activities in the process, hence enabling them to cut back on, or club, the non-value-add activities. In data management context, VSM can be used to ensure smooth flow of information between various sub-processes of an end to end master data process. Master data processes often contain subprocesses through which, when viewed as a whole, data ends up getting keyed into the system several times. Such scenarios can be easily identified and eliminated via VSM. It can even be used to identify the source of incorrect information creeping into the system which might pose a risk to the efficiency of the process.
 
VSM can be applied to any business process – manufacturing or non manufacturing. Capgemini recently implemented master data management for a client in manufacturing industry. Let us have a look at a typical end to end master data process for a player in this industry. Given below is the as-is flow diagram of the material creation master data process:

 


 

VSM diagram (as-is process):

The above process translates into a VSM as given below. The lead times and cycle times mentioned per sub-process are for illustrational purposes and do not confer to the client under consideration. These are the intuitively estimated lead/cycle times, and would have several other dependencies like the experience/proficiency of the employee (c/t collect material data, completeness verification), availability of the employee (l/t management approval) etc.

For process number 5, 6 and 7, there would be an unrelated process running in parallel. It has not been shown in the VSM as it would entail lower lead time.
This diagram makes it easier to identify the bottlenecks.
As shown above, entering data for a single material comprises capturing information from several departments which might require involvement of multiple employees. This could lead to keying in the same data multiple times, and also increase lead time depending on the availability of system users from different departments. This end to end process involves 8 serial steps, with a total cycle time of 1hr 40 minutes. However, the lead time or turn around time (TAT) in this scenario can be as much as 62 hours – For a staggering 97% of this time, no work is being performed. Another KPI that could be considered here is the number of workers required. Clearly, in the worst case scenario, the number of workers will shoot up to 9. 

VSM diagram (to-be process):

As clearly highlighted in the as-is VSM diagram of the material creation process, the major contributor to the high TAT is the waiting time between data entry sub-processes from different departments. The fact that similar data is keyed in multiple times intensifies the need to club or completely eliminate these sub-processes.
Based on the insights generated, the VSM diagram of the to-be process is given below:

In this process, the two sequential steps of data entry – accounting and pricing data – have been clubbed. Additionally, plant, forecasting and operations data are being fetched at an earlier stage, eliminating the need to get it entered by people from corresponding departments at later stage. The idea, at a higher level, is that, there can be templates of similar materials which can be fetched and checked for accuracy during completeness verification / approval stage. This would not only reduce the time taken due to keying in of duplicate/similar data but also reduce the workforce required. This process requires 6 steps, and 4 workers. TAT or lead time has also been reduced to 38 hours. In case data template for a particular material is not available, regular process can be followed, but the accounting and pricing entry stages would still be clubbed, resulting in a lead time reduction of 12 hrs and 10 minutes as compared to the as-is state.

Hence, there could be several possible variants of the solution, depending on the available/to-be-implemented technology; VSM as a tool simply helps in identifying the waste processes and enables the firms to clearly visualize how value addition can be maximized.

Similarly, other master data CRUD processes can be Value Stream Mapped, and checked for scope of optimization by eliminating or fusing the sub-processes that do not add much value. As master data processes keep evolving with time as per the requirements of the organization, it is advisable to create VSM for the processes periodically to keep the waste in check. 

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