Supply chain management tips: Clean up dirty data


If there were one word to define what drives success in modern supply chain management, it would be collaboration. Of course, the finer details are infinitely more complicated than any single word can convey, but the supply chain is ultimately about multiple companies coming together to deliver products and services while meeting customer demands.

Challenges of the modern supply chain
As we detailed earlier this month, one of the many forces influencing the supply chain these days is the demand for omnichannel order management. Developing an effective multi-channel strategy requires a great deal of internal collaboration as well as solutions that provide visibility across multiple channels. Orders made through one channel must be accounted for in conjunction with every other avenue an organization manages. However, while it is important to enhance visibility on internal processes, no amount of interdepartmental collaboration will provide results in today's supply chain. Why? Because many organizations are forgetting to include their partners in their quest for greater visibility.

CaseStack CEO Dan Sanker recently wrote a LinkedIn blog in which he noted that achieving visibility over internal processes was a competitive action item in the supply chains of 1999.

"In the coming years, companies' process orientation will increasingly shift from an internal to a shared one that is connected, multi-enterprise and supported by enabling applications and integration technologies," Sanker wrote. "The new platforms that enable an end-to-end holistic view of the supply chain and provide right-time information to support the execution and decision-making processes will be powerful competitive advantages."

The problem with many existing strategies is that they are too narrow in focus. Yes, organizations must ensure that they have visibility over their own order management and other supply chain processes. However, the solutions they adopt to achieve this visibility should also be capable of expanding as business partnerships grow. This means keeping updated partner profiles and allowing for knowledge sharing so that every link in the supply chain is accounted for.

One potential issue Sanker identified in moving toward multi-organization visibility is that this high level of collaboration is bound to create massive volumes of data. This can place more pressure on organizations, as they need a system for quickly classifying any new data and for tracking customer profiles, new orders and inventories. Additional data can be highly beneficial if there are processes in place to handle it. However, it can turn into a big headache without effective data management strategies.

A new wave of supply chain management data
If Sanker's prediction holds true, then organizations will likely see a large influx of information from their supply chains. This can be problematic without tools such as data cleansing software and standardized practices to ensure that all new information is properly categorized. For instance, a white paper from Novation explored the costs of "dirty data" in the healthcare supply chain. Researchers identified the following issues in particular:

  • Increased labor costs
  • Stagnant product inventories
  • Excessive logistic expenses
  • Inefficient contract management
  • Delayed accounts payable processes

supply chain and order management system dataThere are a number of reasons that supply chain data quality can suffer. A lack of standardization, for instance, may mean that inconsistent information is collected when orders are processed. This in turn can lead to a high error rate or just lower overall visibility. However, it is important to remember that dirty data can also impact the completeness and accuracy of customer and partner profiles. As Novation suggested, this can ultimately lead to misinformed decisions regarding pricing, supply procurement and overall supply chain management strategies.

"Dirty source data can inhibit a healthcare organization's effectiveness in actively identifying and efficiently acting upon supply chain savings opportunities," the paper stated. "Enriched and accurate source data allows users to leverage valuable product information, supporting the processes necessary to identify cost savings opportunities."

Done with dirty data
These comments focused on the healthcare sector, but every industry can face data quality problems as their information stores expand. This makes it important to start preparing now. Novation outlined several action items that are likely to be valuable moving forward:

  • Treat data cleansing as an organization-wide effort
  • Implement data management strategies throughout the entire supply chain
  • Implement controls at every supply chain data entry point

One area in which many organizations falter is in implementing a comprehensive data management system. Many business and IT leaders do not know how many duplicate or inaccurate records they have. Furthermore, many still rely on manual processes to improve data quality, which makes data management an unnecessarily cumbersome task. Focusing on automation and improving data management practices throughout the entire supply chain will enable faster and more accurate information sharing while saving money on the operational expenses that would normally go toward manual processes.

"Many of today's item master maintenance processes are reactive in addressing new product request enrichment and validation, due to limited staffing and a lack of the necessary skill set needed to validate, standardize and enrich product information," the paper stated. "For true value and savings to be realized quickly, this process must be proactive in approach and must begin channeling clean, accurate and enriched product information at the origination of the request."

Of course, shifting toward a more proactive approach is easier said than done, particularly when there is no existing framework for improving data management. While achieving true effectiveness will require changes from a policy perspective as well as a technical one, the technology solutions that are chosen to orchestrate supply chain management processes can have a significant impact on the effectiveness of the processes used to handle data. For instance, IBM Sterling Data Synchronization Manager includes cleansing functionality that detects invoice inaccuracies and facilitates the adoption of standardized data formats.

The important element to keep in mind is collaboration. Internal and external stakeholders must be aligned regardless of which strategies are ultimately implemented. Just as internal processes such as data management must be part of an organization-wide effort, these strategies will ultimately need improvement across the entire supply chain. In this case, it may be best to lead by example and craft processes for exchanging knowledge so that all partners can move toward a unified strategy.

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