The other day, I was eager to come across a report on "how to measure your supply chain" from a well-known research firm—only to find out that it was largely a discussion on selecting business intelligence technology products. It was like asking for directions and then being told to go buy a car with a navigation system. Supply chain performance management is bigger than one technology. Process, methods, and technology all play a vital role in getting improvements in performance.
Better late than never
In all fairness, performance management has taken a back seat, because progress for many in the supply chain journey has not come easily (in which case, just moving forward could be satisfying enough for some). Part of the challenge is that there isn't consensus around a sound methodology to date. A few popular frameworks like balanced scorecards, SCOR, etc. have been available for some time, but these have yet to be widely adopted. There are challenges in trying to align these with the accounting practice of the firm. And in cases where they have been adopted, it's been piecemeal, because the sheer scope and complexity of the total supply chain can be overwhelming. There is no consistent method to capture data across the end to end chain. And there is not much agreement on data and other standards to create a cohesive and consistent picture that everyone agrees to.
The other challenge with measuring is that you can get a lot of data, and not have any real insight. In fact, there is never a shortage of "numbers" within any organization, because people are always being asked to quantify their contribution, and it's common to find situations where everyone is working harder than ever, but the organization as a whole is failing. Similarly, within the supply chain, you can find a lot of metrics at the functional silos, but the real challenge lies with aligning these different metrics to provide a cross-functional view—first across the enterprise and now across multiple enterprises. This brings me to the focus of this month's article
Finding measures that really matter
Since supply chains, by definition, are about the end-to-end inter-enterprise process (be sure to read Dr. Rajamani's article where he outlines a simple process framework to understand the broader perspective), we highlight the growing importance of looking outside your four walls when thinking about supply chain performance management.
When taking a systemic view of the supply chain, a key principle of effective management is about reducing variability. And with more of the supply chain being outsourced these days, the sources of variability have also shifted outside the enterprise. (This month, we'll focus on measuring the right things, and in next month's article, we'll talk about the right way to measure them.)
Students of systemic thinking are also familiar with the constraint management mantra: "An improvement on the constraint is an improvement throughout the entire system." So if you are overwhelmed by the number of supply chain measures you are tracking, it's better to focus your energies on a few that can have a significant impact. And don't forget that these will evolve over time as the constraints and priorities shift.
Supply side insights
On the supply side, just in the last few years, we've seen performance metrics evolve from a procurement mindset toward a total cost of supply perspective that encourages companies to look beyond their immediate suppliers and shift towards a holistic approach that includes the supply base several tiers upstream. Consider the following examples:
Brand manufacturers of digital cameras (and imaging products) have come to realize that their ability to profitably meet demand had a lot to do with how they manage the procurement of the CCDs (the chips that capture the images), which are often under allocation from (a very small group of) manufacturers three tiers upstream. This is a complex challenge that creates the classic bullwhip effect for two reasons: first, given the degree of outsourcing in the electronics industry, in many cases the total lead time can stretch over 25 weeks (or 6 months) across the entire supply chain. Second, short product life cycles (constantly improving mega-pixel capability) meant that CCD procurement decisions cascaded downstream and had a significant impact on product mix decisions and promotion campaigns. (Try guessing 6 months before Christmas which camera model spec is going to be hot and how many will sell.)
This elevates the importance of processes like integrated sales & operations planning to better understand not only the purchasing risk around making "strategic buy" decisions, but how it impacts the new product introduction (NPI) schedules and promotions downstream.
Many consumer goods and food companies whose products require chicken have learned that cost drivers such as corn, processing, etc. can form a large portion of the cost of the end item. Without the flexibility to pass along the price variability (due to fixed menu prices), they had to develop a strategy for better managing the source of that variability (i.e., the corn producers who are three tiers upstream).
Companies like Mindflow Technologies, who have in-depth domain expertise in such categories, go further by incorporating supplier capacities within their analysis. By modeling the suppliers' abilities to better understand production volume and profitability, they help the buyer and supplier enter into a collaborative relationship and agree on certain volume levels at the correct volume discount.
What is worth noting about this example is that while the enabling technology is important to the analytical exercise, it was the vendor's domain expertise in specific categories that helped guide the thinking towards policy changes, including the realization that what was thought to be a commodity was, in fact, strategic.
Examples on the demand side
There is a lot written on the subject of collaborative demand management between immediate partners, but far fewer examples when focusing on the customer's customer. While the opportunity and hurdles are significant, continued fragmentation of the supply chain will force companies to deal with the broader end-to-end perspective.
In the manufacturer-retailer tug-of-war, some brand manufacturers have successfully used their market intelligence to take over the category management responsibility from the retailer. While this approach has its critics, there is no denying the advantage for these category captains (like Whirlpool at Best Buy, or Colgate at Carrefour) who have earned this right through a relentless focus on understanding the end consumer needs. In many cases, implementing the right policies and performance goals can ensure that all parties, even the competing non-captain brands can benefit from such an arrangement.
But then what about after the sale?
Given the potential opportunity, the "service supply chain" is deservedly getting much of the spotlight these days, since most brand name manufacturers don't pay enough attention here. And post-sales service is an especially acute problem in consumer electronics. From personal experience, I can tell you that while I have high loyalty to a premium brand of consumer electronics, I have hated every moment when dealing with their after-sales services (which happens to be outsourced). Being fully aware of their supply chain challenges (such as the effect of returns on margins), I can understand the motivation for making this someone else's problem. But from a brand equity perspective, it's just plain dumb. If you are going to outsource it, at the very least, you need to diligently measure and monitor how this affects your brand. Bottom line: If you TRULY want to earn customer loyalty, you need to manage all aspects—the good, the bad, and the ugly—because that is EXACTLY what your customers are experiencing.
In some industries like semiconductor, systems suppliers like KLA-Tencor monitor and manage throughout the product life cycle. While fill rate is one of the primary measures of customer service, KLA-Tencor discovered that was not a good enough indicator for ensuring part availability for their semiconductor customers. What the customer really cared about was to minimize unscheduled downtime attributable to parts. Instead, KLA-Tencor looked at mean down awaiting part (MDAP), which measures average lost production time across all equipment as a percentage of total available machine time, as a baseline.
Using technology from MCA Solutions, the MDAP baseline metric was then translated into a meaningful fill rate across multiple echelons, including local, regional, and global levels.
(When it comes to customer information, perhaps the single biggest hurdle comes down to attitudes towards data sharing. For a great discussion on this, read Bill McBeath's article, "A Matter of Trust: What to Share with Partners." Again, if you take a systemic view towards managing variability and look for the source of it, it will lead you to the appropriate supply chain strategy.)
There are a couple of takeaways from this as it relates to performance.
First, the end-to-end supply chain perspective begins to expose the variables that are outside the enterprise. So once these are identified, working with supply chain partners to mitigate that variability has to become the focus. And this gets into the next big area for supply chain—risk management—which is all about managing uncertainty.
Second, aligning metrics between enterprises is in the realm of policy (within ChainLink's 3Pe model). More than a decade ago, when most enterprises were vertically integrated, we created an executive position (typically at the VP level) to align demand, distribution, and manufacturing in the enterprise-centric supply chain. With outsourcing, coordination of the supply chain has now moved to a higher order—and that means the ultimate responsibility for alignment now rests with the CEO. If there is no higher "czar" to coordinate the end-to-end supply chain, then CEOs must work together to ensure that their scorecards are properly aligned through policy decisions that break down the "us versus them" mentality.
Your CEO has the power to break internal organization barriers as well as to change metrics, and therefore behavior, then, ultimately, results. However, supply chain professionals have not explained with clarity the supply chain vocabulary, aligned with the CEO's financial language and decision making.
In next month's article on performance, we'll examine the different approach to measuring, and discuss their pros and cons.
This article is from Parallax View, ChainLink Research's on-line magazine, read by over 150,000 supply chain and IT professionals each month. Thought-provoking and actionable articles from ChainLink's analysts, top industry executives, researchers, and fellow practitioners. To view the entire magazine, click here.
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