Introducing SimpleData Management from GlueData

Introducing SimpleData Management from GlueData

Nov 22, 2018

In todays’ business, data drives processes and processes drive profitability.

The smooth running of any process is impacted by the system data that the process utilises. Research from Experian shows that inaccurate data has a direct impact on the bottom line of 88% of companies, with the average company losing 12% of its revenue as a result (https://econsultancy.com/the-cost-of-bad-data-stats/).

Poor quality data adds costs and slows down processes. For example, in the Order to Cash process, the incorrect unit of measure will create an incorrect sales order and an out of date customer address will result in delays in delivery. In the Procure to Pay process, too much is spent on purchasing and incorrect products being returned.

Increasingly important, with the introduction of GDPR and POPI, incorrect or out of date data will lead to lack of compliance and will become subject to fines.

Ultimately, poor data results in poor deliverables, poor information and poor decision making. Time, resources and opportunities are continually lost.

“The best way to ensure good quality data is to validate data when it is entered in the system whilst also retroactively fixing data already in the system. To do this, you need a clear set of rules as well as timely and accurate reporting.” States Brett Schreuder: Managing Director of GlueData.

GlueData’s SimpleData Management (SDM) does exactly this for data in your SAP system:
• New data is verified against rules and entry is simplified by highlighting, hiding and greying out fields.
• Existing data is highlighted through exception reports and cleansed systematically in sprints.
• Workflow is used to approve new data captured.
• Future plans will ensure duplicate master data is prevented and many other additional features.

“SDM will ultimately become a single solution for integrated data management and data governance. Data management with Point-of-Entry control, workflow, data exception reporting and sprint cleansing. Data governance will have tangible and measurable capabilities where the business has accurate role and KPI reporting that ties data governance into the organisation and does not operate as a top down and bottom up approach to data, but rather an integrated and single view of data management.” Concludes Brett.