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Don’t Use Data Integrity Issues As A Crutch

By Richard Sharpe | 12/11/2018 | 9:47 AM | Categories: Web/Tech

: “Our data has significant challenges and this is a real handicap for us.”  It is rare to talk to a company that believes they have very little challenges with their data.  In fact, the recent Supply Chain Quarterly Big Data Analytics Survey found that data quality and access issues were one of the main frustrations that business users have in getting true business value from their analytical initiatives. Unfortunately, many companies use their data liability issues as a crutch to justify why they are not getting true value of business analytics.

Case In Point: Several years back, a meeting was being held with the CFO, COO and SVP of Supply Chain for a well-known apparel company.  They knew that they needed to build the analytical capabilities of their organization but were skeptical because of their perception of the current state of their data. Fortunately, the SVP of Supply Chain had previous experience in tackling this issue.  He convinced the others to take a first step that would demonstrate that their data could be turned from a liability to an asset to produce meaningful insights on opportunities to reduce costs and increase profit margins.

Action: A Project Team was assembled and all sources for their transactional data associated with their supply chain and sales operations were identified. Data Subject Matter Experts were involved to address any data issues. Consensus was reached by the Team on how the data should be intentionally transformed to build a foundation for SKU and customer specific cost and profit performance information. Cloud-based technology was then used to further validate the data and to create specific and actionable financial performance insights that could be refreshed periodically. By benchmarking performance of similar customers and products, significant financial opportunities were identified. The Project team also found an unexpected bonus associated with potential inventory working capital reductions in excess of $10 million dollars.

Takeaway:  Competitive Insights presented at the CSCMP Global Conference in November of this year.  As part of that presentation, recommendations were made on basic building blocks to address data issues. You can receive a copy of this presentation at this website.

Data integrity issues can be proactively handled to ensure that operating data becomes a valuable asset.  An asset that allows for visibility into actionable insights that drive trusted, fact based decisions. The companies that take this seriously will consistently move ahead of their competition and drive additional profitable performance.

I would love to know your thoughts on this.  Please comment on this posting or email me at [email protected] .


All the best,

Richard Sharpe



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The opinions expressed herein are those solely of the participants, and do not necessarily represent the views of Agile Business Media, LLC., its properties or its employees.

About Richard Sharpe

Richard Sharpe

Richard Sharpe is CEO of Competitive Insights, LLC (CI), a founding officer of the American Logistics Aid Network (ALAN) and designated by DC Velocity as a Rainmaker in the industry. For the last 25 years, Richard has been passionate about driving business value through the adoption of process and technology innovations. His current focus is to support CI's mission to enable companies to gain maximum value through specific, precise and actionable insights across the organization for smarter growth. CI delivers Enterprise Profit Insights (EPI) solutions that enable cross-functional users to increase and protect profitability. Prior to his current role, Richard was President of CAPS Logistics, the forerunner of supply chain optimization. Richard is a frequent speaker at national conferences and leading academic institutions. His current focus is to challenge executives to improve their company's competitive position by turning enterprise wide data from a liability to an asset through the use of applied business analytics.


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