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Beyond Financials: Five Great Uses for Data Analytics in Manufacturing


At times, any manufacturing enterprise can feel like a web of mysteries and riddles. Just keeping track of all the moving parts—from supplier relationships to compliance requirements, from inventory control to shipping—poses a major professional challenge for accountants.

Fortunately, data analytics allows you to break down the complexities of manufacturing and extract business intelligence across the enterprise. Yet, how many of us work with owners and senior managers who claim to rely on their gut instinct when making decisions? A study of California executives by Corvinus University of Budapest demonstrated that even the most rational leaders make up to 80 percent of their decisions based on intuition.

That makes our role all the more critical. By using data analytics intelligently across the enterprise, internal auditors can help management and stakeholders make decisions based on hard facts for timely risk assessment and business improvement.

CEOs may look first to auditors to ensure compliance, but our greatest value may come in the areas of operational effectiveness and efficiency. For example, most organizations have a working fire suppression system that passes regular inspections. But an operational audit may reveal issues such as frequent false alarms, pressure leaks that require costly service calls, and even anomalies such as frequent motherboard failure on equipment in rooms where the leaks occur. In reality, how much is that "compliant" system costing?

Data analytics can help identify potential areas where manufacturers can reduce costs, eliminate inefficiencies, and make better decisions. The possibilities are almost endless, but here are five top areas where you can set up IDEA to provide critical information for planning, forecasting and action.

#1 – Purchasing

IDEA can be used to set up dozens of tests to monitor critical data fields. For the process of creating a purchase order from a requisition, the following are some areas where IDEA can help you examine the data in different ways:

  • Were any items sourced to multiple vendors on multiple POs?
  • Can you track where they all originated?
  • Were POs created from older requisitions (say, over 90 days?) If so, why did that occur?
  • On the other end of the life cycle, were the goods ever actually received?
  • Did the quantity received match the quantity on the purchase order?
  • Did they all match the vendor’s invoice?

#2 – Sales

Are company sales skyrocketing? This may be an area to investigate further to ensure the numbers are verified. For example:

  • Do any commissions, advances, or sales bonuses look excessive?
  • Monitor for common sales schemes, such as:
  • Shipping out goods to customers without a sales order
  • Recording sales for duplicate or cancelled orders
  • Skimming from sales returns
  • Look for unusual or significant sales with month-by-month comparisons
  • Scan journal entries before the close of the year or a reporting period
  • Investigate credit memos and deferred revenue accounts

#3 – Warranties

Dubious return practices can make profit margins unreliable.

  • How many warranty claims are you getting for goods sold?
  • Are they coming more often from particular service providers than others?
  • Do the serial numbers match up?

#4 – Subcontracting

Fraud and waste in the supply chain can be a major Achilles heel for any manufacturer. Labor violations, shoddy workmanship requiring product recalls, and intellectual property infringement are just a few of the costly issues that have recently splashed across the headlines to embarrass major manufacturers.

While this complex issue cannot be resolved behind a desk, data analytics can help.

  • Track the labor and material costs you are being charged to match against the quality you are actually receiving.
  • When suspicions warrant, you can also set up more elaborate tests, such as checking shipment dates, cities, and time

#5 – Inventory

You can set up almost as many tests for this vital area as your imagination can generate.

  • When it comes to stock levels, do you keep excess inventory on hand?
  • If so, how long do the excess items stay around?
  • How many items do you have that are obsolete or have an expired shelf life?
  • When obsolete items are scrapped, how are they recorded?
  • Do you have items going out the door that cost less than the sum of their components?
  • Are you still purchasing components for items that have been deemed obsolete?

In addition to these five, there are many more areas in which using data analytics to the fullest can make a significant contribution to the bottom line, including pricing, cash management, and payroll, to name just three.

We Want to Hear From You

Do you have other ideas about how to use IDEA to help manufacturers implement smarter and more efficient processes, increase predictability, and get on top of costly exceptions and fraud early? Please share them—just send us an email and we’ll feature the best idea in an upcoming edition of the monthly IDEA Update!


Best Practices , CaseWare IDEA



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