Category Archives: Supply Chain

Are You Strange Enough? (Repost)

This post originally aired four years ago (on Nov 30, 2007) and is being reposted because it complements Monday’s post by Dalip Raheja on The Difficulty of Finding Qualified Supply Management Candidates very well. In Dalip’s post, he noted that you will never find a good candidate if you can’t define what qualified is. And, if you want a successful organization, qualified needs to capture the skills you want talent to possess — and these skills are highly dependent upon the outcomes that you want. In this classic Wharton article, which excerpts part of chapter four of Daniel M. Cable’s book, Change to Strange, we are told that to get the best results, companies have to build a workforce “that is extraordinary in a way that customers care about” and the only way to do this is to build your organization around measuring and gaming performance drivers . In particular, around metrics that define what you want to capture. These metrics will define the skills you want your candidates to possess, which will in turn define what qualified means, and, ultimately, help you find the right candidate. Plus, in today’s crazy economy, how can you possibly hope to win if you’re not a little strange?

Browsing through the Knowledge @ Wharton site, which is another one of those sites (like the Economist) that is just as important as the supply and spend management sites you visit every day, I stumbled upon an article published this summer that asked “If Your Workforce Is Strange Enough to Guarantee Competitive Advantage”. It’s a very good question.

The article excerpted part of Chapter four of Daniel M. Cable’s book, Change to Strange that notes what characterizes successful companies these days is a “strikingly different, obsessively focussed” workforce, one that — compared to competitors’ workforces — is “downright strange”. More specifically, to get the best results, companies have to build a workforce “that is extraordinary in a way that customers care about”.

In the excerpted chapter, the author argues that a successful organization is built around measuring and gaming performance drivers – and this is what results in a strange workforce. The development, measurement, and enactment of the performance drivers is what provides the required insight into what the organization is creating, and not creating, that is required to differentiate it from its competitors, attract customers, and, most importantly, win.

The process starts by identifying the outcome metrics that provide a valid reflection of what you think your organization exists to create. Then you find a way to make these metrics move in a way that your competitors are not willing or able to pursue. For example, if you’re a procurement outsourcing organization, you might decide that what customers value most is spend under management and spend put through the system. If this was the case, then you’d find a way to integrate best of breed on-demand SaaS technology into your offering so that not only could you put every purchase you make on behalf of the client through the system, your clients could also put every purchase they make against the contract through the system. Then, used meticulously, your customers would find over 95% of their spend against a contract you cut on their behalf would be in the system and that their spend under management goes up as a result. If your competitors think that the most important metric is total leverage-based purchasing power, you’re in a unique position if you’re right as to what customers want.

It’s also important to answer each of the following questions when you believe you have identified an outcome:

  • What produces the number – and what makes it go up or down?
  • What are the two or three most important beliefs our customers need to have about us relative to our competition to affect this outcome? How do we measure our progress toward our goal of having these beliefs accepted by the majority of our target market?
  • How can we influence the outcome in a way that is valuable, rare, and hard to imitate? What are we willing to do that the competition is not in order to drive this outcome?

For example, if you were a procurement outsourcing organization, you might come up with the following answers:

  • Spend through the system is calculated as total dollars on contracted items spent through the system divided by the total dollars spent on contracted items. It goes up when maverick spend is down, and down when maverick spend is up.
  • The two most important beliefs a customer has to have is that we mean what we say and we eat our own dog-food. We do all of our spend through the system. We measure our progress towards this goal by determining the percentage of outsourcing deals we are getting invited to bid on versus the total number of outsourcing deals that are currently happening in the marketplace.
  • We can adopt an open book policy on our own spend, and let prospective clients (under NDA) access the system and verify that our claims are valid – and this is something our competition might not be willing to do. We can also offer an on-demand spend analysis solution to our clients as part of our service offering so that they can calculate for themselves how much spend goes through the system, how much maverick spend is happening in their organization, and what commodities or categories we should be handling for them.

Thus, even though it might be a little too academic for your tastes (as the book was written by an academic who used a Business School as the example – ick!), the article had a very good point and asked some very good questions once you isolated the core of its message. If you want to be the best, it’s not enough to just work harder and more productively than everyone else … you have to be just a little bit different … and maybe even a little bit strange.

Can SaaS Solutions Improve Supply Chain Network Quality?

A recent article over on Supply & Demand Chain Executive on a holistic view of quality described the four steps to applying a cloud-based solution to establish a quality supply network. In this post, we’ll review the four steps presented and then discuss whether or not SaaS (Software as a Service), because “cloud” is undefined and irrelevant, can really improve your network quality.

The author is correct in that a number of trends (including a greater reliance on component suppliers, outsourcing of subassemblies and offshore manufacturing) are dramatically changing the supply base and challenging the ability of brand owners to manage their supply chains and ensure quality. And the author is also correct when he states that access to data is unpredictable across the supply chain and this is a problem. If all you get is a number of reports that are incomplete, inconsistent formats after the fact, that’s just not good enough — especially if you need to interpret the data in real time to take effective, corrective, actions.

And he’s also right in that, when outsourcing (to far-flung locales), intermittent inspections are not enough. A quality trend analysis, built from the continuous monitoring of quality, is required. However, retesting after you get a delivery does nothing to insure quality of supply — it only prevents defects from reaching the consumer. And if this results in a stock out six weeks before Christmas, this could be devastating.

That’s why a quality supply network, which insures quality before product leaves the manufacturer, is required. According to the author, this is achieved by:

  1. Capturing the Data
    Extract as much data as you can from suppliers’ manufacturing execution systems and/or spreadsheets into a common format.
  2. Uploading the Data
    Aggregate, synchronize, and retain the data on common servers where the supplier and brand owner have secure access.
  3. Analyzing the Data
    to gain insight into quality issues and trends (in real-time)
  4. Gathering Insight from the Data
    by way of an intelligent, multidimensional pattern recognition tool that identifies the data clusters where anomalies and issues are

And, at least according to the author, the best way to do this is a cloud-based solution because manufacturers do not need to make significant IT investments to build a quality network and you can quickly bring alternate manufacturers online and monitor their product quality, ensuring the results you need and minimizing the impact to delivery schedules.

This is true, but he is making / implying a couple of incorrect assumptions.

  • Cloud offers no advantages over SaaS
    and, furthermore, you don’t even need to have a true SaaS application or have it externally hosted! You could have a traditional web-based solution in your data centre. As long as suppliers can easily upload their data or provide you web access to their data feeds, it doesn’t matter if it’s cloud, SaaS, or just web-enabled. As long as everyone who needs the data can get it when, and how, they need it, problem solved.
  • You don’t need a multidimensional pattern recognition tool.
    All you need is a good data analysis tool and a smart analyst — because no tool will ever be smarter than the analyst driving it. As long as she can build the cubes she needs, create the appropriate multi-dimensional reports, and capture trends — she’ll spot the issues.

In short, SaaS doesn’t improve supply network quality — real-time data sharing and analysis improves supply network quality. A SaaS solution can enable this, but it’s not always necessary and not a complete solution in and of itself (as you will always need a smart brand owner and smart analyst driving the solution).

Wanted: Talent-Driven Innovation

While we’re on the subject of talent and the importance thereof to a successful Supply Management organization, a topic that we will address further in the weeks to come, it is fruitful to point out a “recent article” over on Industry Week by Stephen Gold, the CEO of Manufacturers Alliance, who asks a very important question:

Can the United States meet the challenge of creating the skilled workforce needed for manufacturing leadership?

After all, if we are going to homeshore and bring jobs back, due to the rising transportation and labour costs in the developing world, as well as the considerable overhead imposed by various import and security laws, we need a workforce that can handle them. And considering that the manufacturing workforce has declined 40% over the last 20 years, it could be difficult to bump it back up quickly given the skills required for your average production line these days.

Given that the #1 driver of competitiveness is talent-driven innovation, if the US can’t step up its game, the emerging markets may take the lead. Especially given that countries such as Germany, China and India have done far more in recent years to encourage innovation (and in turn build vibrant manufacturing bases) in their own backyards than the US has done. And given that high-skill employment has risen 17% while low-skill employment has dropped 9%, there is a double challenge to be faced. Furthermore, with the recent de-emphasis of math and science in primary and secondary schools, and the corresponding decline in math, science, and engineering degrees from 11% to 7%, there is, in actuality, a triple challenge to be faced. (And that’s not considering the fact that a global assessment ranks US students 23rd in science and 30th in math!)

The US may be able to rise to the challenge, but, like Rocky, they’ll have to have the eye of the tiger to do it. What do you think?

Why Are Fuel Prices So Volatile?

This recent article over on the Supply & Demand Chain Executive Site by Barry Hochfelder on a volatile problem does a great job of sketching out the fuel supply chain and explaining why prices will sometimes change five to ten times a day!

At a high level, this is how a fuel supply chain works.

  1. The refiner receives oil and produces gas, diesel, and petroleum fuel products.
  2. Traders then buy and sell the fuel.
  3. Fuel is moved via pipelines, barges, and tankers to supplier storage tanks.
  4. Distributors transport the fuel to retailers or consumers.

So where’s the volatility?

  1. There are buyers, sellers and intermediaries between the pipelines.
    Furthermore, there are many suppliers at different terminals in the geographic locations where pipelines terminate into bulk storage. These suppliers advertise prices at their terminals. If they see a change, they will often move prices to their advantage.
  2. Then there are contracts.
    Buyers will procure fuel based on midday close and other complex calculations.
  3. And suppliers offer multiple price feeds to try and win contracts.
    With prices that change based on time of day, contracting terms, and calculation methodologies.
  4. Taxes are constantly changing.
    There have been over 1,800 changes in tax rates at the local, state, and federal levels.

And this volatility is not going away. Time to start preparing.

JDA and Oliver Wight’s Myths and Realities of S&OP – The Verdict Part II (IV of IV)

In Monday’s post, we presented JDA and Oliver Wight’s 10 myths of S&OP planning, as laid out in recent white paper. Tuesday, we presented their 10 realities of S&OP planning. Yesterday we reviewed the first five myths and realities and offered our own verdict. Today we tackle the final five.

  1. Myth: S&OP is just another executive meeting.

    Reality: When executives take control of the process, they define the information that they need. Graphical views of aggregate information (both qualitative and quantitative) are crucial to an effective S&OP process.

    Verdict: Yes and no. Graphical views of aggregate information are crucial to identify overall trends, historical and projected future, and to quickly identify where reality is diverging from prediction, but hard numbers are going to be needed when it comes time to determine how much a plan is off and how much it needs to be corrected. And executives will define what they want to see, not necessarily what they need to make a good decision. That’s why supply chain needs to lead the process, and why supply chain analysts need to dive in and figure out how to present the executives not only with what they want, but the critical information that is needed to make a good decision.

  2. Myth: S&OP relies on a fixed demand plan or statistical forecast.

    Reality: Demand-shaping strategies and scenarios are evaluated through the monthly S&OP cycle. Executives need to evaluate different scenarios to identify and compare
    the effects on Key Performance Indicators (KPIs).

    Verdict: This is dead-on. Good S&OP uses good modelling and analysis tools to come up with good projections and good plans for presentation, discussion, nudging, and acceptance.

  3. Myth: S&OP processes are too complex and difficult to manage.

    Reality: Winning companies are collaborating with their trading partners.

    Verdict: Yes, but it’s not trading partner data, but POS data that is the most critical. This gives the most accurate view of historical and current demand that can be used to analyze the current plan. It’s only relevant that your supplier can only supply 30,000 units if you actually need 50,000. If you only need 20,000, your need can be met, and how many more units your supplier can supply is irrelevant.

  4. Myth: The finance team is just going to override any S&OP plan that we create.

    Reality: The new paradigm for S&OP incorporates financial analysis into each key step.

    Verdict: Not sure where this myth came from, as it’s usually marketing, sales or manufacturing that tries to override the number. Finance just wants a seat at the table. They will accept whatever plan is accurate, as that will allow cash flow to be optimized in such a way that the greatest benefit to the company is achieved.

  5. Myth: S&OP can be solved with the implementation of a tool.

    Reality: S&OP must have a combination of people, processes and tools working collectively.

    Verdict: Correctemundo.

So what’s the final verdict? Three realities were dead-on. Two were completely whacked. SI couldn’t make sense of one. Three more were only half right. And the last one was ok. SI gives it a C-. While there was obviously some thought and effort put into this paper, and it is worth a read, it would appear that it fails to remember that supply chain is central to successful S&OP (execution), data- and numbers-based analysis is critical to success, and one-size does not fit all, especially for certain categories of fast-moving consumer goods.