Tamro looks into its master data

“Traditionally, the master data used to be contained in the ERP system, but over the years they came to be stored in separate systems. This may have led to internal inefficiencies with the result that the information was not always available to all,” explains Jukka Pesonen, Tamro’s IT Development Manager.

With the expansion of electronic services, stringent requirements are imposed on the accuracy of the data. For example, most of today’s orders are placed electronically and customers are able to view product assortments and prices on the Internet.

Tamro is currently building an automated logistics centre in Tampere. With automation, the importance of the master data’s accuracy is also highlighted. The centre, due for completion in 2012, will handle around 45 per cent of all pharmaceuticals used in Finland.

Customer data must be accurate

When the placement of orders for pharmaceuticals and the preparation of deliveries take place more or less automatically, it is of utmost importance that the customer data required for dispatch are free from errors.

As Tamro wanted to determine the current status of its data, it ordered a Master Data Management (MDM) pre-study from Affecto. Completed in spring 2011, the project took about three months.

The current state analysis looked into the type of processes used, how the data were processed and where they were maintained. Additionally, the owners of the systems were identified. The information was gathered through interviews by Affecto’s consultants with individuals representing the various business areas.

According to Pesonen, the use of an external consultant instead of in-house personnel provided sorely needed extra resources. Also, the support given by the top management for the project encouraged the interviewees to make a true commitment to it.

Ownership of data to be defined in great detail

While the pre-study was used to stake out a development path, no changes to the systems or processes were made during it. Pesonen says that one of the most valuable findings of the pre-study was that the ownership of data must be determined more accurately.

“Who is responsible for the data at any given time when customer data are spread across several systems from ERP to CRM? Often, the efficiency of master data management needs to be improved due to the fragmentation following mergers. In our case, it was a question of changes in business caused by new customer groups,” says Pesonen.

Another finding made in the course of the pre-study was that a life cycle needs to be defined for all data. It means, for example, that a specific item of data is effective, say, as of Wednesday next week or is available for a predetermined period of time.

A concept model required for data

“The pre-study also found that a concept model was required for the data. The existing models are based on the structure of the ERP system. A drawback we identified was that with the existing structure, it was hard to respond to new needs quickly enough.”

The key requirements specified by Tamro for the master data management system were availability, transparency and controllability. During the course of the pre-study, it was proposed that the management system be implemented as a centralised solution. The new system could be built in stages. Stage one would focus on data profiling to support subsequent centralisation.

As member of the German Phoenix Group, Tamro also operates in other Nordic countries and the Baltics. According to Pesonen, the results of the pre-study and the potential MDM project will be utilised in these countries where appropriate.

Solution

The Master Data Management pre-study completed for Tamro identified the systems in which master data were stored and explored ways of ensuring their efficient use.

Benefits

• Development path for master data management
• Greater focus on the ownership of the various categories of data
• Identification of the needs to update the concept model for the data structure
• The pre-study revealed the current status of the master data and highlighted the most critical areas where improvements were called for
• Greater awareness of the master data and the importance of sound data management