In this blog, we will explore the Business Value Analysis capability of the SAP Information Steward 4.2 release.
Poor data quality can affect businesses in many ways. The impact can be financial, customer perception, operation efficiency, brand recognition, regulatory compliance, and so on. Here we see some examples of issues that arise due to bad data and how it affects various day-to-day aspects of the business.
| Issue | Impact |
|---|---|
| Difficult to determine the right recipients for marketing campaigns | Operational Efficiency |
| Inaccurate order information causes delayed or lost shipments and lower customer satisfaction | Financial Customer Satisfaction |
| Sales representatives are not able to identify relevant accounts | Operational Efficiency |
| Costs are high due to account duplication, while response rates are low | Financial Operational Efficiency Customer Acquisition |
| Potential customers are annoyed by redundant mail, emails, and phone calls | Customer Satisfaction |
| Total revenue and profitability of products and services is reduced | Financial |
| Reporting uses wrong data, which leads to wrong conclusions and decisions | Financial Operational Efficiency |
| Inaccurate statutory reporting | Legal |
| Carrier stop charges for incorrect or incomplete addresses | Financial Customer Satisfaction |
| Misalignment between vendors and defined terms due to system inaccuracies | Financial |
| Poor spend visibility due to unstandardized, duplicate data | Operational Efficiency |
| Unable to find the right product / material due to unstandardized, duplicate data | Financial Operational Efficiency |
| Items are purchased off contract at premium prices due to poor quality supplier data | Financial Operational Efficiency |
And, there can be many more such issues that arise from specific industries and business processes. For any organization, it is important to understand and quantify this impact. By assigning a dollar amount to poor data quality, the business awareness of the downstream and bottom line impact of bad data is increased. It puts value on clean, accurate data and can be used to justify additional funding of your information governance initiatives. Sure, an organization may know in theory there is a cost associated with bad data, but to be able to put actual numbers behind it - this can really give the information governance cause the credibility that it needs.
SAP Information Steward's Business Value Analysis enables business-orientated data stewards (or data stewards in collaboration with LOB representatives) to connect financial ROI to the organization's data quality and information governance initiatives.
Information Steward's Business Value Analysis features allows the organization to see the overall trend for the cost of poor data at various levels for root cause analysis. The business can also perform ‘what if’ analysis to identify potential savings / losses if they clean the bad data and accordingly focus their data quality / information governance efforts in the areas that will benefit them most.
With the Information Steward 4.2 release, the process of validation rule development now includes the ability to define itemized cost per failure. So as you add a new set of business rules, the financial impact associated with the data that failed against the rule is immediately taken in account within Data Quality Business Value Analysis.
There are two types of costs that can be considered when you calculate the cost per failure. Some costs are incurred in terms of a human resource spending time on addressing the issue or performing root cause analysis. These are called resource-dependent costs. Then there are costs that are resource-independent in nature. Here you can see a few examples of different cost types:
Resource-independent costs
- Cash flow: Additional costs incurred to the organization’s cash flow, such as delays in recognizing revenue or making supplier payments
- Fees: Costs associated with any additional expenses or direct fees, such as those resulting from regulatory compliance failures
- Fixed overhead: The fixed overhead cost distributed per failure, such as storage costs due to returned shipments
- Revenue: Loss of direct revenue, such as lost customers or new sales
- Sales: Additional costs associated with selling goods, such as sales organizations following erroneous leads
- Other: User-supplied costs
Resource-dependent costs
- Labor - Costs associated with the loss of productivity, for example, a resource or person will have to spend a specified amount of time to capture and remediate quality issues
- Other – Costs that are not covered by the existing types
This is by no means an exhaustive list. The idea is to provoke thinking about such costs when trying to understand impact.
If you would like to find out more about SAP Information Steward's Business Value Analysis feature, here are some additional resources available to you:
- SAP Managed Tags:
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