“Crawl-Walk-Run”: Improving Your Master Data Step by Step

By Israel Rosales on December 31, 2013

In the previous post, we discussed how to determine the current status of master data in your organization. We also introduced a progressive, three-step “crawl-walk-run” strategy to elevate your master data to the next level. Here, we will walk through this process using a real-life example from an apparel company. "Babies Sitting, Crawling, and Walking"

Mike is the Master Data Manager at this company. His team, established just a year and a half ago, has been tasked with the management of all material master data within the organization, as this was identified as a critical business area. Mike’s team has four data analysts, each of whom covers a different area.

Current Status
The company’s level of master data maturity is currently somewhere between the Developmental and Reactive stages. With each clothing season, the company requires input of multiple data elements related to material master data:

  • Finished goods, with all of the required views (basics, sales, manufacturing, accounting, etc.)
  • Raw materials, with their relevant views
  • Bill of materials that links the finished goods, raw materials and manufacturing process
  • Pricing conditions for the finished goods (base price, taxes, discounts, rebate conditions, etc.)

In addition to the changes required for each of the four seasons, the company’s Sales & Marketing Department wants to add sub-seasons, in order to meet the consumer demand in a more agile way. This would mean increasing the number of clothing seasons to eight per year (two per natural season)—a strategy that has already been put in place by some of the industry rivals.

In order to implement this, Mike’s team would have to generate in SAP:

  • 1,500 new finished goods
  • 3,000 new raw materials (thanks to process standardization for finished goods and seasons, they have reduced this to an average of two new raw materials per finished good)
  • 2,750 new bills of materials (taking the alternative manufacturing processes into account, this currently averages at one and a half BoMs per finished good)
  • 30,000 new condition records for the different pricing conditions and combinations of access sequences

Let’s consider this in the following context. (Note: For the purposes of this example, we will ignore objects like production orders, as we will consider this as transactional data.)

Each day, Mike’s team has to pursue the different departments involved in this process in order to gather all of the necessary information for the Excel templates they are using. Each department is in charge of specific fields for each object related to their area.

Once all of the information is gathered, the data analysts use custom loading programs (created some years ago for the initial data migration into SAP) to complete the creation of these objects in SAP. Since these programs are not always as updated as desired, the analysts frequently have to supplement this process with manual action. Both data gathering and manual manipulation have been identified as big sources of errors and subsequent dirty data.

In addition to the efforts described above, Mike’s team also has to accommodate frequent requests from Production and Sales & Marketing for ad-hoc mass changes to the system as a result of evolving business needs. These include changes in pricing and discounts to react to market tendencies, changes in bills of materials or alternative raw materials due to changes in manufacturing processes, changes in vendor prices, etc. These ad-hoc change requests are a permanent headache for Mike and his team: Each request is slightly different from the previous ones, and the few ABAP programs created for these tasks are expensive and become obsolete very quickly.

Plus, the team is bombarded with a constant influx of correction requests, as business detects mass errors in the data almost every day. As a result, Mike’s team is totally overwhelmed—in essence, they are just acting as “fire-fighters,” surviving each day with the hope that the next one won’t be as bad.

The emergence of each new clothing season brings endless days and long working nights, complete with the hiring of temporary employees to alleviate the inevitable bottlenecks and an ever-increasing expense of ABAP programs. Add to this all of the complaints from the business—as master data errors result in downstream delays, financial losses, and decreased levels of service and customer satisfaction—and Mike’s team is at its wits’ end.

Looking to the Future
Mike’s manager invites him to a meeting and communicates some of the future changes:

  • It has been confirmed that the number of clothing seasons will be increased from four to eight per year.
  • In addition to the material domain, the Master Data team will need to start managing other domains: customer, starting in three months, and vendor, starting in six months.
  • Only one new data analyst can be added to the team.
  • The subcontracting budget for the new season has been cancelled.
  • The budget for new ABAP programs has been restricted; a new ABAP program will be approved only if it guarantees a clear productivity improvement.

Discouraged and depressed, Mike returns to his desk. During the next few days, he spends hours after work searching for possible solutions (the daily data emergencies flooding his team don’t allow him any time to do this during normal business hours).

One day, someone in his local SAP user group suggests that he try Winshuttle.

Winshuttle to the Rescue
Mike reviews the Winshuttle website and analyzes the solution with Winshuttle Sales. After several meetings and demos (online and on-site), he decides to use the allotted ABAP budget to acquire some Winshuttle Desktop licenses for his team members. With the help of Winshuttle Sales, he builds a strong case of value proposition, which convinces his boss to authorize the purchase.

After that, progress happens very quickly:

Step 1 – Desktop (Crawl): With Winshuttle desktop tools, Mike and his team can generate Excel templates for mass updates to SAP quickly and without programming. They can also handle the changes required for next season, as well as unexpected changes from the business, in record time.

Ad-hoc requests that previously required a lot of time are now easily completed. Mike’s team can rapidly put out fires, while still having the time to plan preventative measures. Combining the querying and mass updating tools between Excel and SAP has allowed the team to clean up existing data in the system, eliminating errors and their downstream impact on other areas.

Departments across the organization are enjoying the benefits of this change, experiencing much fewer delays, better data quality, and faster response to mass change requests.
And all of this has happened in less than three months…

Pondering further process improvement, Mike’s team has another bold idea: “Why don’t we get some Winshuttle licenses for the business and let them do some of the tasks?” This brings us to Step 2.

Step 2 – Workgroup (Walk): Due to the imminent increase in the number of Winshuttle users, Mike decides to jump from a pure desktop implementation to a workgroup one, which adds a Winshuttle tool for document management and governance to his arsenal of value-added resources.

Key business users are identified as second-level authors, enabling them to create Winshuttle Excel templates. As first-level authors, Mike’s team reviews these templates, as well as each mass action before it’s performed against SAP.

The team also starts managing customer master data, as was scheduled six months prior, and to everyone’s delight, this has no impact on preparing for the next clothing season. Customer master data is handled in the same way as the material domain, ensuring consistency across the organization.

With the prospect of also having to manage vendor master data in one month’s time, Mike decides to forego hiring another employee, using that budget instead to acquire the Winshuttle Enterprise platform in order to facilitate continuous process improvement.

Following a natural progression, this step has evolved in less than two months…

Step 3 – Enterprise (Run): With the upgrade to the Winshuttle Enterprise platform, Mike’s team plans to implement a number of different workflows in order to have better control of master data processes. These include:

  • Several Excel-based workflows for gathering information related to each data object for each new season
  • A form-based workflow for the creation of and changes in customers
  • A form-based workflow for the creation of and changes in vendors
  • A form-based workflow for the creation of and changes in materials

With no programming required, Winshuttle tools allow Mike and one of his guys to build these workflows in only four months. Compared to the old ABAP invoices, the cost involved is just peanuts for the company.

Then vs. Now
Pausing to reflect upon the evolution of master data management since acquiring the Winshuttle tool kit, Mike is amazed at the progress achieved in only nine months:

Before:
– His team was putting out fires on a daily basis.
– They had no control of the processes, nor any time to think about how to improve them.
– Each new season was a nightmare to implement, with poor data quality and associated delays affecting all aspects of the business.
– Mike’s restless, sleepless nights were filled with worry about adding customers and vendor master data.

Now:
– Data emergencies are largely non-existent, as issues are prevented in a proactive manner. Even if a problem arises, it is resolved quickly.
– Seasons and sub-seasons are being managed with agility, with processes easily adapting to the business changes.
– There are no delays to business operations, as data is accurate and up to date.
– Without adding any new members, the team is able to manage customer and vendor master data, in addition to the material domain.
– All of the departments are actively involved in the master data governance processes, facilitating collaboration and efficiency across the organization.

With the Winshuttle out-of-the-box dashboard tool, Mike can analyze workflow processes and detect bottlenecks, as well as apply changes and improvements and measure their impact. He now has the time to focus on continuous improvement.

Mike gets comfortable in his chair and puts his feet up on his desk—big smile spreading across his face. He is now free to dream up improvements for the future.


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