Process intelligence for supply chains and manufacturing operations
Six tenets of intelligent process improvement
Today’s manufacturers face a dynamic, competitive environment characterized by disruptive technologies and increasingly complex supply chains which bring significant challenges as well as opportunities. Process improvement efforts can be deployed quickly and return results in the near term. However, companies that do this can also take a long-term view and recognize the need for continual process improvement efforts to address evolving market conditions.
- Think beyond what is currently “known”
- Challenge conventional wisdom
- Stretch beyond process mapping
- Follow the facts
- Buy runs, not players
- Carry it across the goal line
- Two heads are better than one
- Meet the authors
- Join the conversation
- Related topics
Think beyond what is currently “known”
People often “know” which process improvement methodologies work, and they approach those methodologies the same as they have for decades. Yet despite those decades of history to learn from, companies are still struggling to realize success from their process improvement efforts.1
Why do some process improvement efforts succeed and others do not? This paper outlines six tenets to help companies think beyond what is currently “known” and bring more “intelligence” to process improvement.
1 3rd Biennial PEX Network Report: State of the Industry, Trends and Success Factors in Business Process Excellence,” PEX Network, Fall 2013, http://www.processexcellencenetwork.com/downloadContent.cfm?ID=1697.
Challenge conventional wisdom
Manufacturing companies tend to approach the design and manufacturing process the same way they have for many years, often constrained by the geometries of traditional manufacturing processes (casting, machining, etc.). These “constraints” can limit the potential performance of products (heavier, weaker, quality defects, etc.).
One of the keys to the DMAIC process (Define, Measure, Analyze, Improve, and Control) is to sometimes think outside of the box when it comes to improving a process. One such way to think outside the box during the Improve phase is to use innovative technologies to remove traditional manufacturing constraints and thus improve the functionality of the end product.
Additive manufacturing, often referenced as 3D printing, is one such innovative manufacturing process that can change the conventional wisdom behind the design and manufacturing of a product. By using additive manufacturing, geometries that were once impossible to fabricate or just cost prohibitive are now feasible and can improve the functionality of a product.
Stretch beyond process mapping
Like many industries, manufacturing companies utilize numerous complex processes. Understanding how processes truly work is a key to identifying improvements. Mapping these processes step by step by shadowing people is a good start; unfortunately, how individuals think the process works and how it actually works can be very different. This approach can also be limited as it is difficult for a single person or group of individuals to fully understand all of the processes utilized at a manufacturing company due to the sheer number and size of all of the business processes.
A different approach involves purpose-built tools that follow the data in a company’s underlying technology to map the process. Deloitte’s proprietary tool called Process X-rayTM is designed to reconstruct what really happens and provides organizations with the capabilities to isolate root causes.
Advanced analytics is currently used by manufacturing companies to address a whole host of different questions using historical performance, such as: span compression, demand aggregation, predictive material availability, and network impact modeling.
Follow the facts
Manufacturing companies gather vast amounts of data, from customer demand to supplier and operational performance. There are many reasons why companies don't see these initiatives through, such as: competing priorities, organizational leadership changes, and lack of accountable leaders.
Many times, companies can be asking the right questions to improve the business but without fully utilizing the available data improvements, they can be limited or focus efforts in the wrong areas. Advanced analytics is one way that manufacturers can use the vast data available to more efficiently test hypotheses using fact-based analysis.
Advanced analytics is currently used by manufacturing companies to address a whole host of different questions using historical performance: span compression, demand aggregation, predictive material availability, network impact modeling, etc.
Buy runs, not players
In the movie Moneyball,2 a statistician suggests the following: “People who run ball clubs, they think in terms of buying players. Your goal shouldn’t be to buy players; your goal should be to buy wins. And in order to buy wins, you need to buy runs. Baseball thinking is medieval. They are asking all the wrong questions.” The same is true in process improvement.
Every day, manufacturers are forced to handle “random” events that are impacting their business. From threats of shutting down production lines due to parts not showing up on time to reworking parts due to poor quality, manufacturers are constantly firefighting to keep production lines up and running.
Many times, companies waste valuable time and money only addressing the symptoms that are impacting them (expedite, part rework, etc.). Unfortunately, by only addressing the symptom, the issues will continue to reappear, kicking off the firefighting process all over again.
To address this, companies should look to tackle the true root cause of the problem. One method is Root Cause Corrective Action (RCCA), a process that tackles the root cause of the problem and prevents issues from reappearing.
2 Moneyball. Dir. Bennett Miller. Perf. Brad Pitt and Jonah Hill. Columbia Pictures, 2011.
Carry it across the goal line
Like many other industries, manufacturing companies may have a hard time seeing process improvement initiatives through to completion and on through the sustainment phase. There are many reasons why companies don’t see these initiatives through: competing priorities, organizational leadership changes, lack of accountable leaders, etc. Many times companies lose interest in these initiatives because of this lack of ownership, focus, clear business impact, and rewards.
Another reason manufacturing companies may have a hard time pushing through to sustainment is the number of stakeholders required to make a change. Many times, to implement an improvement multiple processes must be changed, each with a different stakeholder in charge. If any single stakeholder does not buy in to the change and fulfill their commitment, the whole initiative can be at risk.
One thing, however, remains the same, no matter how much time and effort is put in to the improvement initiatives, without completion and a focus on sustainment, anticipated benefits will likely not come to fruition.
However, by developing a solution that focuses on implementation and sustainment, process improvement initiatives can be successful and benefits can be realized.
Two heads are better than one
Lean Six Sigma became widely adopted in the manufacturing industry in the 1990s and 2000s. Many companies developed entire organizations around the topic to educate employees, provide certification, and drive Lean Six Sigma projects.
Lean Six Sigma is an approach that can be used for maximizing benefit while minimizing effort. It can be further enhanced by educating others through an apprenticeship model where employees new to the concept can learn from the experience of those whom have been through it before. Such a mentorship model can keep teams motivated, foster continuous learning, and, most importantly, maintain improvement gains.
Download the PDF towards the top of the page for more on the six tenants, including several case studies, to help you on your journey in bringing more "intelligence" to process improvement.
Also, check out our other perspectives on Process Intelligence, which draws upon time-tested techniques like Lean Six Sigma that are enhanced with proprietary analytical tools and deep experience to help clients make breakthrough improvements.