Optimize Your Supply Chain with EPM

Posted by Steve Berry

Dec 6, 2019 10:58:44 AM

When it comes to curing supply chain hiccups EPM is prescription medicine uniquely formulated to meet the supply chain’s diverse requirements and reduce financial risk.

Think about what you need to run your supply chain with maximum efficiency for maximum benefit. You need to capture a myriad of disparate data coming from a myriad of sources, such as:


·      Point of sale

·      Contractual commitments

·      Your capacity

·      Actual inventory

·      Other legal constraints

·      Suppliers’ constraints

·      in-transit inventory

·      Demand

·      Available capital

·      Delivery lead times

·      Demand variability

·      And a lot more . . .

You also need to operationalize the data you capture — meaning that you need to put it to work. The data has to extracted, cleansed, consolidated, and formatted. Potentially insightful correlations need to be postulated and tested. What/if forecasting models need to be built and analyzed based on various scenarios — not just for demand at particular points in time, but also for many of the other variables (including some just listed) that could impact your business. Finally, stakeholders need to communicate and collaborate around this data and analyses so they can effectively address questions like:

  • Where do supply chain bottlenecks exist that are holding back growth?
  • Where are we over- or underinvested in inventory?
  • Where do opportunities exist to free up working capital?
  • How or where can we be more agile in meeting demand?
  • What should we outsource and where?

Whether your answers are right or wrong will obviously have a huge impact on your business. For many companies, inventory is one of biggest items on their balance sheet. It is also obviously one of the items causing the greatest financial risk — such as when a retailer is out-of-stock on a popular item or a manufacturer fails to keep customer commitments because a key part is unavailable. Weighed against those risks are the risks of keeping items in inventory too long — such as holding costs, product obsolescence, and the simple cost of making or buying something you don’t need yet (and may never need).

Data Latency Issue

Unfortunately, the time available to get these answers is typically, and increasingly, short — so data latency is a big issue. The older the data, the more likely the organization’s situation could have changed before action is taken. That is why the functional and informational barriers that isolate supply chain silos (e.g., manufacturing, procurement channels, suppliers, logistics) from each other can no longer be tolerated. Stakeholders across the enterprise need to operate off a common set of facts if they are going to work together toward common objectives. That way the data that originates in one department (e.g., sales or procurement) will be available as needed to other departments (e.g., manufacturing) that rely on that data (e.g., to schedule production runs). Something else that can no longer be tolerated is linking together a convoluted array of spreadsheets for complex data analysis. Spreadsheet models are notoriously prone to break as data volumes, data disparity, and model complexity all increase. Time spent overcoming silo barriers and repairing spreadsheets increases data latency and financial risk.

Forecast Quality Issue

Another issue that increases financial risk is poor forecasting. Even if stakeholders can get the data they need in a timely way, it might not matter if the forecasts based on that data is inaccurate — for example, because stakeholders use weak analytical tools or because they cannot easily explore which tools turn out to offer the most insight in a given situation. This is another reason to use something more robust than spreadsheets. It’s one thing to build forecasts based trailing averages or simple regressions. It’s another to leverage more sophisticated methods like single, double, or triple exponential smoothing — or to weight data based on its volatility such as seasonal demand and market trends. Unless the more complex analytical methods are built into whatever tools stakeholders use, they will probably stick to simpler methods. That likely means less accurate forecasts, and — once again — greater financial risk.

Oracle EPM Cloud— Purpose Built for Supply Chains

If Oracle EPM Cloud were a prescription drug, the list of indicators printed on the back of the bottle would read like the list of supply chain requirements. Wide array of built-in analytical methods? Check. Easy to switch between analytical methods? Check. Near real-time data integration across supply chain silos? Check. Automation for fast data extraction, cleansing, consolidation, and formatting? Check. Powerful collaboration features? Check.

Indeed, the powerful multidimensional database engine at the heart of Oracle EPM Cloud — Essbase — is purpose built to support exactly the range of complex analytical methods, huge datasets, and cross-silo data exchange automation that modern supply chain management requires.

By having all these capabilities in a single platform, Oracle EPM Cloud provides a single point of control to optimize both the supply chain and what ultimately matters most: financial performance.

Topics: EPM Support, Technology Insights, Cloud EPM, Managed Services, Enterprise Performance Management (EPM), Oracle Products