Take a Lean Six Sigma Approach Using Data Analytics

Henry Ford once said that if he had asked people what they wanted, they would have said faster horses. Constant innovation keeps businesses thriving.

Regardless of your industry or role, there are plenty of opportunities to get creative and improve processes to increase your productivity. The Lean Six Sigma methodology paired with the use of data analytics has the potential to improve operational efficiency and facilitate innovation. The framework can be applied to Define, Measure, Analyze, Improve and Control (DMAIC) any business process or objective. It focuses on reducing and eliminating waste, lowering defects in products or methods, and improving customer satisfaction.

The Origin of Lean Six Sigma

Lean Six Sigma can be traced back to Motorola engineers who decided that the traditional methods for measuring defects in thousands of opportunities were insufficient. They set out to measure defects per million opportunities by:

1. developing a new standard
2. creating a new methodology
3. cultural change to achieve their goals

Their demand for higher standards and quality helped Motorola achieve more than $16 billion in savings. Tens of thousands of companies throughout the world have adopted Lean Six Sigma as a way of doing business.

How it Works

The fundamental objective of the Lean Six Sigma methodology is the implementation of a measurement-based strategy that focuses on process improvement and variation reduction. Lean Six Sigma seeks to improve outputs by identifying and removing the causes of defects (e.g., errors) and minimizing variability by using a set of quality management and statistical tools.

Applying Lean Six Sigma

When taking a Lean Six Sigma approach, most professionals begin with an assessment using checklists and questionnaires to determine which business activities stand to benefit the most. These are compared with predetermined standards or desired results and used to determine whether a particular process is being followed or not. Variations are recorded to find root causes and areas for improvement.

The numbers have a story to tell. Data analytics enables professionals to bring data from different sources and file types into a single platform where 100% of the data can be compared and analyzed. This delivers insights that were not previously attainable. Analytics can uncover opportunities for efficiency and quality control, in addition to fraud prevention.

CaseWare IDEA® data analysis software is the preferred tool of professionals who are not data scientists or programmers. It provides a centralized approach for capturing and analyzing data to help professionals assess risks, gather evidence, uncover trends and provide the intelligence needed to make informed decisions. Here are some ways IDEA users are applying the Lean Six Sigma methodology combined with IDEA to improve operations and processes including:

• Analysis of Obsolete Inventory Data:
  • Last date sold for products
  • Changes in quantity (look for over or under production)
  • Inventory turnover
  • Order dates vs. fulfillment and delivery dates – look for opportunities to reduce fulfillment times
  • Purchasing – Amount of inventory on hand (too much or not enough)
  • Returns – Which products are being regularly returned? Was there a change in the vendor or product quality?
• Revenue Analysis – Ratios and pricing: Review contractor jobs by type and gross profit to determine whether some jobs have higher profit margins. There may be opportunities to market those services and/or products to increase profitability.
• Expenses & Vendor Contracts – Explore purchasing power opportunities. Is the company ordering supplies from multiple vendors when they could be consolidated or negotiated?
• Purchasing Cards – Is AP cutting small reimbursement checks when it may be more efficient to implement a p-card program?
• Reporting – How long does it take staff to run and/or create monthly reports? Is it an area where IDEAScripts might be used to shorten the process and delivery time?
• Waste – Does a corporate fleet of vehicles have excessive repair or warranty expenses? Would it be more cost-effective to purchase hybrid vehicles to save on fuel costs?

Examples of IDEA in Action

Due Diligence

 
Mergers and acquisitions require verification of the value of inventory. Blending sales reports with inventory data, IDEA can be used to determine whether inventory is worth the stated asking price. In one case, IDEA helped identify $200,000 in products that had no sales in 18 months. The information helped the purchasing company reduce the seller’s asking price by $100,000.
 

Data Errors

 
Incomplete or inaccurate data can wreak havoc on an organization. IDEA was used to analyze four years of detailed reports to detect variations or errors between the detail ledgers and the general ledger. In a single day, 1.2 million records were analyzed using the summarization feature in IDEA to uncover a host of errors and mismatched invoice numbers. When accuracy is not an option, data analytics can be applied to quickly identify gaps and missing data that may indicate fraud or processes that require improvement.
 

System Implementation

 
Like many organizations, there comes a time when new systems are implemented. Transferring data from old to new systems is a daunting task. IDEA is frequently used to export vendor, client and employee data from legacy systems to clean and prepare it for upload into the new system. IDEA’s powerful data extraction and formatting capabilities save hours of effort and help with a smooth transition.
 

Cross-Charging

 
When departments cross-charge expenses, it can be difficult to evaluate group performance for budgeting purposes, especially when no report exists. IDEA’s summarization functionality helps determine where expenses originated, view historical trends, and estimate future cross-charging estimates for budgeting.
 

Regulatory Requirements

 
IDEA is effective for using keyword searches to identify un-allowed costs and generating reports that can be used for federal regulatory audits. It has become invaluable for identifying allowable and unallowable costs. Through keyword searches, accounts and transactions that are high risk for unallowable costs can be discovered and analyzed in minutes.

The Lean Six Sigma methodology challenges professionals to look across the business for opportunities to improve existing processes and identify new ways to achieve optimal levels of efficiency. There are valuable insights within the data, and IDEA can help you get answers to, track trends and patterns, and test controls that need adjusting.
Ready to boost your efficiency and innovation? Talk with one of our data analytics experts – contact [email protected] to get started.

Audimation Services is a data analytics company that combines deep industry experience and proven technology solutions to transform raw data into vital information.