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.
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:
Are company sales skyrocketing? This may be an area to investigate further to ensure the numbers are verified. For example:
Dubious return practices can make profit margins unreliable.
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.
You can set up almost as many tests for this vital area as your imagination can generate.
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.
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!