Lean Business Intelligence helps Manufacturers
Manufacturing is filled with variables. Variables in the workforce, in supplier delivery & quality, logistics and in processes. Unbridled variability is the same as chaos. Lean Six Sigma, APICS (APICS is the premier professional association for supply chain and operations management) and ASQ (American Society for Quality) provide tools and techniques for addressing variation. Lean Business Intelligence helps eliminate management variation by getting the entire team's priorities aligned.
- Existing improvement approaches fail to systematically minimize management variation. This variation has an enormous impact on the effectiveness of an organization. Lean Business Intelligence helps remove this variation.
- Many teams, dealing with excessive variation, have the "what do we fix first?" issue. In Lean BI, data points the way. The largest opportunity becomes the focus for improvement and it's the responsibility of those running the process (not outside improvement experts) to drive that improvement. When employee turnover occurs the focus remains on the largest opportunity. It doesn't change because someone new thinks "we need to do this." The data creates a roadmap to results. The prioritization that Lean BI provides minimizes a major source of management variation.
- Meaningful performance expectations are established with Lean Business Intelligence. Expectations that reflect process knowledge. Realistic expectations garner the respect of process owners, even those who in the past, have scoffed at arbitrary goals. Realistic expectations creates accountability. Arbitrary goals increase process variation because actions taken to hit arbitrary goals will probably have a whack a mole effect.
- Lean Business Intelligence helps eliminate siloed departments, acting against one another to achieve siloed objectives. Lean BI gets teams pulling the same direction.
High Inventory Levels
- Excess & obsolete inventory builds to oversized levels. There is no systematic approach to keeping it visible and managed
- Overall inventory exceeds expectations significantly
- Appropriate, planned inventory levels (goals) are arbitrary, data is not used to determine those levels. (Inventory goals are inflated because underlying material's data is not factored into them)
- Monthly stratification of inventory is limited to inventory aging, not planning categories (hint: the horse is already out of the barn)
- Inventory reporting fails to compare “Actual to Plan” in inventory planning categories
How Lean BI Maintains Optimum Inventory Levels
- Using your major inventory categories, (i.e. Finished Goods, Purchased, Raw, etc.) we'll help define the actionable sub categories in each (i.e. Allocated to Scheduled Work, Safety Stock, Excess, etc.)
- We use usage data, MRP forecasting or other data to define meaningful benchmarks for each sub-category of inventory
- We create monthly visuals of “actual to plan” for each category and have planner/buyers identify specific items that cause excess to plan. The team identifies specific actions to address these items
- Largest excess materials are visible online to the team, along with the actions planned to eliminate them.
Low Inventory accuracy can interrupt production plans and increase production costs (some are obvious costs, some are hidden.) Not to mention causing inflated inventories and high excess and obsolete levels
- Physical inventory counts typically fail to correct the problem. With a high likelihood of mistakes during a physical count, especially in unorganized areas typical of a low accuracy area, any improvement won’t last.
- Though everyone wants a quick, easy fix, there are none. However, once you know where you want to be, and define a deliberate course to get there, improvement starts. Stay the course and you’ll soon be wondering how the business ran in its previous state.
How Lean BI Improves Inventory Accuracy
- We help identify layout and parts storage issues contributing to the problem. We review and recommend the implementation of warehouse upgrades to eliminate inherent causes of low accuracy as well as lead Kaizen events focused on organization and Lean's 5S.
- We analyze your entire parts flow, from receiving to shipment, and identify improvement opportunities
- We create meaningful, easy to understand, inventory metrics the entire team sees and understands, from management to warehouse
- We assist in the implementation of proactive warehouse cycle counting to obtain unbiased inventory accuracy data to track improvement
- Ongoing Lean BI performance measures ensure transparency and accountability, to maintain and build upon improvements till objectives are achieved
- Detailed scrap data is often collected but no tactics are employed to maximize understanding of the data, it's distributed as a list or simple pareto. Team members can’t easily see trends or other important aspects of the data.
- The variety of scrap sources in manufacturing operations (i.e. set-up, test, trim, quality and engineering change scrap) make it difficult to identify the largest opportunities for improvement
- The real information is buried in the data, which allows people to ignore it, even those who should be acting on it. It allows them “to do things the way we’ve always done it
How Lean BI Minimizes Scrap Levels
- We turn your scarp data into simple, but meaningful visuals the teams can quickly interpret. The visual will create accountability for performance in specific categories, and team ownership will be assigned to categories
- We create meaningful performance benchmarks for each scrap category to ensure focus on the largest opportunities.
- We ensure teams define improvement actions and maintain follow-up till real performance improvements occurs and the results fall to the bottom line.
- As organizations change to adjust to the competitive environment, customer requirements sometimes get neglected. In the back of your mind, you’re hoping the customers won’t notice, eventually they do and they start to express dissatisfaction.
- At this point you realize neither you or the rest of team have visibility to your delivery performance details. You know your customer’s rating, but there is not much actionable information in it. Your internal tracking of delivery performance is opaque, no one really knows what’s driving the poor results.
- When a review meeting is called it takes a day or two for the team to create the detailed data for the review
- In reviewing the data, you realize there is no process for defining the categories late deliveries can be grouped by, i.e. engineering issues, customer issues, etc. Short term improvement with increased focus occurs but it doesn’t last because the process hasn’t changed
How Lean BI Improves Delivery Performance
- A root cause analysis of late deliveries will lead to a variety of issues including scheduling, engineering or quality, none of which can be quickly resolved. In the meantime, your customer is only concerned about getting deliveries back on-track. Lean BI will help get quick attention on the customer specific items while root cause issues are resolved.
- We create customer delivery transparency by obtaining the detailed data and converting into visual displays so everyone understands the trends and largest issues.
- We will define a process for reviewing delivery data on a regular basis. The process will be streamlined and data manipulations will be automated to minimize nonvalue added efforts from the team. The focus will be on the facts and solutions for meeting customer delivery requirements.
- We will define categories for missed deliveries and assign one to each. This will allow subgrouping to look for the largest common threads and get those addressed first.
- The recovery effort will include action item assignment and routine follow-ups. As repetitive issues are identified and addressed, future deliveries start improving
Other Areas of Performance
- Purchasing & Planning
How Lean BI Helps
- Any process that generates data can be improved with Lean BI’s transparency.
- Whack-a-mole management is eliminated with Lean BI, the transparency it creates allows for the detection of small problems before they become big.