Let’s take the SCOR Upside Supply Chain Flexibility measure. This measure is described as, “the amount of time it takes a supply chain to respond to an unplanned 20 percent increase in demand without service or cost penalty.” This begins with knowing about the change, understanding the risk associated with the change, and then determining how best to respond to the change. Knowing sooner means having all of the right data along with the analytics that will not only highlight the risks, but also provide insight into your response alternatives.

Your ERP system may give you most of the data, but some customer and supplier data may still exist outside ERP. Getting all the data and then applying the analytics, can be difficult, especially if you want to run multiple what-if planning scenarios.

Of course, the other popular option is Excel. It may be easier to get data into Excel but it is unlikely you would have all of it. The analytic piece of the equation is the most difficult to replicate in Excel. The one advantage of Excel over ERP is that it tends to be easier to use. However the challenge becomes similar to using a heating pad to warm up at the rink, it is only good for one. As soon as the Excel file gets passed around, changes are made and then the “right data” question comes back into play. This is important because in most cases any response to the change, for example the unplanned 20 percent increase is not going to happen in isolation.

In order to increase the analytic side of your “Upside Supply Chain Flexibility” measure, the wish list begins to look like this;

• All of the right data in one place.
• Supply chain analytics in the same place as the data.
• Easy access to the data and the analytical tools for all required participants.

Look for these attributes to heat up your supply chain analytics capabilities. I guess only a frozen hockey player would come up with this analogy.

Keeping on the lighter and warmer side of flexibility, be sure to check out this week’s New Kinexions video on flexibility. Poor Ari Cole can’t bend like he needs to! Click here to watch Episode 2 and don’t forget to enter our “New Kinexions” contest! To learn how you can win an Xbox 360 with Kinect, visit https://community.kinaxis.com/thread/7369

Those top three challenges are:
Volatility—driven by global complexities and fluctuation in customer demand
Visibility—specifically the need for accurate, time-sensitive information
Value—continued corporate pressure for supply chain management and operations to create enterprise value

Those are indeed, significant obstacles. Fortunately, considerable progress can be made addressing them through the use of a supply chain management solution, and, more specifically, S&OP tools.

There’s been quite a bit of discussion about demand volatility here on this blog and in the Supply Chain Expert Community. For instance, Lora Cecere from the Altimeter Group addressed the subject in a webinar titled, “What S&OP capabilities matter most?” Trevor Miles has had some good posts on volatility too.

What Lora, Trevor and others have noted, is that in recent years, demand has not only fluctuated more significantly than in the past, but the frequency of change has also increased. The result is that forecasting by looking only at historic demand patterns is no longer sufficient. What’s needed instead, is the application of a robust what-if? capability to do range forecasting. That way, rather than a single number forecast, users can also test upside and downside scenarios to evaluate potential risks and mitigate against them.

It isn’t surprising that visibility—or, more accurately, lack of visibility—was cited as the second most prominent supply chain challenge by respondents in IBM’s survey. As today’s supply chains become more complex, visibility becomes more important. This is particularly true in industries such as high-tech electronics and consumer goods, where brand owners and contract manufacturers face high demand volatility and rapid product evolution. They also have increasingly complex operations where many critical activities take place outside the traditional four walls of the enterprise, and there are many geographically-dispersed sites and/or partners using disparate data systems.

I’ll argue, however, that the real challenge isn’t to simply gain visibility. It is a pre-requisite to the end-goal, not the goal itself.  Sure, visibility is vital but the larger business goal is to improve agility.

Many will promote “visibility” solutions and will tie that to statements like “sense and respond.” The problem is few, if any, are actually providing tools to enable the response process. They provide a limited level of visibility and leave users to determine how to benefit from it.  Visibility without the tools to drive action gives only minor advantages to the organization. One needs to be able to alter and analyze information, not just see it.

I’ll also add that collaboration plays a critical role. Having access to “actionable” supply chain information can set the stage for more meaningful and effective interactions between stakeholders based on informed decisions whereby the impact of decisions are understood and action plans are clearly defined.  To truly improve supply chain performance—and ultimately address that unrelenting pressure to add enterprise value—a company must first gain supply chain visibility, but then they must be able to collectively leverage that data to make rapid decisions and act accordingly. 

That is true value.

Of course this uncertainty is not restricted to the US economy, which is the point Tom Friedman makes by focusing on the German economy and how it relates to economic recovery in Europe.  In fact he points to three influences that will need to be reversed if the US and EU economies are to recover soon:

The first big structural problem is America’s. We’ve just ended more than a decade of debt-fueled growth during which we borrowed money from China to give ourselves a tax cut and more entitlements but did nothing to curtail spending or make long-term investments in new growth engines.

Second, America’s solvency inflection point is coinciding with a technological one. Thanks to Internet diffusion, the rise of cloud computing, social networking and the shift from laptops and desktops to hand-held iPads and iPhones, technology is destroying older, less skilled jobs that paid a decent wage at a faster pace than ever while spinning off more new skilled jobs that pay a decent wage but require more education than ever.

But the global economy needs a healthy Europe as well, and the third structural challenge we face is that the European Union, a huge market, is facing what the former U.S. ambassador to Germany, John Kornblum, calls its first “existential crisis.” For the first time, he noted, the E.U. “saw the possibility of collapse.” Germany has made clear that if the eurozone is to continue, it will be on the German work ethic not the Greek one. Will its euro-partners be able to raise their games? Uncertain.

Commenting on Bernacke’s statements, Jeannine Aversa of Associated Press writes that

Consumers have cut spending. Businesses, uncertain about the strength of their own sales or the economic recovery, are sitting on cash, reluctant to beef up hiring and expand operations. A stalled housing market, near double-digit unemployment and an edgy Wall Street shaken by Europe’s debt crisis are other factors playing into the economic slowdown.

OK, OK, so there is lots of economic uncertainty.  What do we do about it?  During my time as a management consultant I learned a fundamental truth: Analyzing a situation is fairly easy, defining a future state is a lot harder, but the really hard part is defining the path to achieve the future state. Not being an economist I can comment little on the efficacy of Tom Friedman’s suggestions for recovery, nor on Ben Bernacke’s for that matter.  My guess is that most of the readers of this blog fall into this category too.  Clearly we all want the same future state of a revived world economy and we are all too aware of the current state of the economy.  Of course we all have our opinions on the path to recovery, which we can express in elections, but for the most part actually pulling the levers of the economy is not something which is in our control.

Which leaves us all feeling “really unusually uncertain”.

While we may not be able to effect change to the national or global economy, we do have some level of control over the economic performance of the companies for which we work.  As I commented in a previous blog titled “Why S&OP? Why now?”, this is where I see sales and operations planning (S&OP) playing a big role.  But for S&OP to be effective it must provide ways for people to evaluate and understand uncertainty.  There are 4 fundamental capabilities that are required to achieve this:

1. Capture of assumptions made about the future state for knowledge sharing and control
2. Facilitated collaboration across functional boundaries to get buy-in and inputs from multiple parties
3. Super-fast “what-if” analytics that allow organizations to evaluate and compare multiple scenarios in order to maximize performance and to mitigate any identified risks
4. Continuous plan performance management so that deviations are detected early and course corrections can be made quickly

The last point about performance management is often overlooked.  The more uncertain the future, the less likely it is that your plans will be achieved.  It doesn’t help much if at the end of the month you determine that the plan wasn’t achieved.  In a more stable economy this might have been sufficient.  In today’s volatile economy (which is the root cause of our uncertainty) it is really important to monitor performance continuously and to course correct as quickly as possible when significant deviations are detected.

However, what makes this all possible is super-fast “what-if” analytics.  Uncertainty is risk.  Without a mechanism to evaluate many alternative scenarios, your ability to evaluate and understand risk is reduced greatly.  Do you think Excel is up to this?  Do you think this can be achieved without any technology?

First you have to decide where the concept can be applied.  This suggests that you examine your existing processes to determine where you can address a significant portion of the normal variation with a minimum of organizational effort.  That alone can be a major stumbling block and too often I’ve heard the comment “everything is an exception around here”.  So the challenge is identifying what constitutes a meaningful exception, and in my book, a sign of a good process is where something is an exception less than 10% of the time.  The next step is to identify who needs to act, how they will be notified, and what tools they will need to address the exception.  Not a trivial job, but well worth the effort.   

Let’s use a common administrative process as an example, committing to a sales order delivery date.  For this example, your business uses either a traditional ATP process, or perhaps product lead time to automatically establish a proposed commit date.  If in 90% of the cases this results in a date that is in alignment with the customer need date, then you have the basis for implementing an exception based process.  In this case, only those orders that do not meet the customer requested date would be identified as an exception and flagged for special consideration.  All other orders would be automatically committed and confirmed with the customer.  This might be refined further to establish tolerances where the exception is only in cases where the delivery date is more than 3 days later than the customer request.

Once the exception condition is defined, an effective process for dealing with them requires timely notification (alerts) to the people who must collaborate to establish an acceptable outcome.  In today’s largely outsourced supply chain, that can be both technologically and logistically challenging.  Not only do they need to be notified of the business condition requiring their attention, but given access to the tools and information that can lead to a rapid and reliable decision.  Using the order commit process as a further example, the ability to meet the customer request date might take one of several paths;

1. Product substitution (if availability exists)
2. Production acceleration (if capacity and material availability exist)
3. Order split (if a partial order can be delivered when the customer needs it)
4. Order prioritization

A well defined exception management process would consider options in a logical sequence and within a time frame that meets customer expectations for responsiveness.

Applying the concepts of exception management to ERP action messages is an area ripe with opportunity.  I’ve known organizations that get 30,000 or more action messages following an ERP regeneration.  In those organizations it is readily acknowledged that planners will never get through the action list.  Therefore, the real question is, “Are they working on the right actions?”  In one organization, a second level analysis was performed on the action queue to evaluate the messages and prioritize them with regards to their importance and impact.  This had a huge impact on planner productivity and overall business performance.  A well designed exception management system should have that effect where ever it is applied. 

The bottom line is that I strongly recommend examining if your organization has the tools to effectively implement exception management processes.  This requires the ability to generate alerts, identify the right participants, provide the right views of information, and facilitate collaboration where needed.  The investment to put this in place will typically yield returns that are often 10X within the first year.  With the economy now on the rebound, the time is right to better leverage your organizations human capital through the implementation of effective exception management processes.

It begins with what he believes defines the customer experience value chain:

“Network of internal and partner processes, people and capabilities that translate innovation into customer value while delivering an unrivaled customer experience”

While closely formulated from Forrester’s definition, loosely defined as “activities through which companies create value, competitive advantage, and superior customer experiences”, what I find unique and interesting about Cisco’s definition is the specific attention and promotion of “people” and their “capabilities”. Perhaps this resonates so much with me because I have long believed that collaboration is the next supply chain “optimizer”, and collaboration is decisively a purpose-driven human activity. To be more precise, it is the unifying of actions taken by uniquely capable people for a common good (more on this later).

Angel identified four legs required to support the creation of strategic advantage; Customer Focus, Agility, Collaboration and Sustainability. At first glance, you might find these to be obvious and perhaps not so unique – and indeed, many companies are talking about these elements in one form or another. What is different about Angel’s message, for one, is the maturity and execution of the model. For example, I’ve never met a company who would say they are “not customer focused”; however, most continue to govern themselves according to traditional, and very operationally focused, metrics (e.g. cost, quality, delivery and speed). Cisco, on the other hand, measures their customer focus by focusing on perfect product launch, perfect order, order-to-invoice cycle time and last but not least “moment of truth customer satisfaction measurements” – thus, redefining their balanced scorecard to align with its customer focus.

A significant portion of Angel’s presentation was spent on the Flexibility/Agility leg. What caught my eye most is a theme I am seeing across multiple manufacturing segments, and is becoming a key requirement for many looking to improve their supply chain management and S&OP processes: the growing gap between Demand Chain and Supply Chain. Today, it is not uncommon to see completely disjoint demand side planning (S&OP) and detailed supply chain planning solutions, and yet, it is in between the two where a significant amount of efficiency and performance can be lost. I believe the gap is widening at a steady rate, and this is what is driving the need for new and innovative solutions to “collaborate and effect change in real time”.

So we’re back to Collaboration – the third leg. In my humble opinion, it will be in this area where excellence will be won or lost. You might look at collaboration as the combination of people + processes + technology/tools, but I was very impressed to see a slight variant of this long standing equation. In Angel’s vision, it is “culture” + process + technology/tools. I admit never having thought about it as a cultural challenge, but having worked with many large organizations on this problem, I’ve come to realize how unique a problem this is… collaboration amongst peers and employees is often challenging enough across departments. The type of collaboration Angel is talking about is inter-enterprise – which means that on a given day, you may very well be collaborating with a complete stranger living on a different continent. Indeed, there are cultural implications to achieving this level of maturity.

Again, I might say there is nothing new about promoting collaboration as a key to success; however, it is what Cisco is doing about it that distinguishes them from the rest. They are leveraging many of their own technologies to produce what they call an “Integrated Workforce Experience” (IWE) platform capable of bringing teams together to collaborate and solve ‘moment of truth’ problems that occur in the gap between demand chain and supply chain planning. Unlike social networking platforms, such as Facebook, MySpace and the like, which use friends, family and fun as a hook, I believe platforms like IWE will motivate productive usage and involvement through content, context, and consequence.

Finally, we have Sustainability, which is extremely topical these days as we watch in horror the catastrophe still hemorrhaging under the Gulf of Mexico. Here, we heard some common themes on creating efficiencies and innovations in product design, educating and increasing employee involvement, and a particularly catchy tag line: “Don’t just ‘comply’, lead, innovate, differentiate”. The one resonating message around sustainability, more of a lesson really, is the reminder that sustainability should not be viewed as a factor for competitive advantage, but rather, the one common flag around which everyone can unite and learn from one another. Industry collaboration will be the key to effecting a meaningful and lasting change.

Does Angel’s vision align with yours? Do you see effective collaboration as an emerging competency that will distinguish your company’s performance?

By the way, if you missed the presentation, grab a soda and sandwich and watch the replay of this presentation by registering here.

We are delighted to be sponsoring an upcoming webinar that will explore key issues for the global Pharmaceutical Industry and discuss the impact of these trends on supply chain development, response and go forward strategy.

Part 1: Pharma 2020 – Maintaining competitiveness and operational advantage in a rapidly changing environment
Tuesday May 25th 2010,  11:00am ET
Live Webinar

Speakers:

• Hans Engels, CEO, DSM Pharmaceuticals Inc.
• Thomas Panzer, Vice President Global Supply Chain, Bayer Biotech
• Nari Viswanathan, Vice President, Aberdeen Group

Key topics will include:

• Is the era of blockbuster new products over, and has the balance shifted to a new paradigm of competition on process and efficiency?
• Optimization of inventory and manufacturing capacity across multi-tiered global pharmaceutical operations
• Driving working capital efficiencies
• Enhancing supply chain agility and flexibility to integrate and align supply and demand

Registration is complementary.

Here’s the big question:  Will companies think differently after suffering the consequences of this natural disaster?  What will they do different?

I don’t think the answer is building more just in case inventory. In order to stay competitive supply chains have to be lean. (In fact, they are becoming even leaner with late stage postponement to satisfy increasing levels of customization on consumer goods.)

Here are some questions for consideration:

1. Can you proactively analyze and understand the risk of unplanned events?  This may be the upside or downside in demand or supply disruptions. This also includes the identification of sole sourced material.
2. Do you have the visibility and access to information in your supply network that you need? More and more companies are looking for a global view of all of their inventory with the need to rebalance as the demand and supply fluctuate
3. Do you know what to do when you have a problem that you just can’t solve?  When a volcano happens there is not much you can do about it. The question is are you making the best use of the supply that you have? How do you want to prioritize demand and allocate your supply? How quickly are you able to make these decisions?

While there may never be another volcano that disrupts the supply chain, there are daily disruptions that affect companies every day, and that taken in sum can have a material impact to the business. How do you deal with them?  Send in your stories!

Let us look outside of supply chain for examples where the data quality is good enough to make sensible decisions.  We know that child mortality is higher in poor countries than in rich countries.  The UNICEF mission is “To reduce child mortality by two-thirds, from 93 children of every 1,000 dying before age five in 1990 to 31 of every 1,000 in 2015.”  I’m good with the first part of the UNICEF mission (reduce child mortality by two-thirds) and will continue to donate to them on this basis.  It’s the second part that confuses me.  Does is really matter that in poor countries child mortality is 93 per 1000 births or 100 per 1000 births?  I would just go with “more than 90 per 1000 births”.  I just don’t see how the precision of the statistics improves the quality of UNICEF’s decisions.  And I think too often we confuse the 2 issues of quality of decision and quality of data.

Before I am misunderstood, let me state quite clearly that data quality can always be improved.  There is no question in my mind that all enterprises should have “data police” that ensure that the data is of reasonably good quality.  But let’s all recognize that data quality is like a sales forecast.  We all need to get better at it, but we will NEVER get it absolutely right, as in complete, correct, and there when we need it.  What we want to avoid is getting it absolutely wrong.

In addition, I think that data latency is a key element of data quality. So I don’t agree with Tom Wailgum. The speed with which you receive data is a big part of its quality. I would much rather have partially correct data quickly than precise data slowly. One of the most important insights that can be gained from data is trend. Trend is often more important than the actual value, and trend is totally absent from Tom Wailgum’s discussion. In other words, data should have 3 major measures of quality:

• Completeness
• Correctness
• Timeliness

In case we forget, people are operating supply chains right now with the quality of the data they have right now. They are making multi-million dollar decisions in the long term based upon the current data. They are making 1000’s of decisions on a daily basis – expedite this PO, cancel that PO, promise this date to a customer, … – based upon the current data.  In many cases they are using paper and pencils and gut-instinct to make these decisions, and more often than not they are the right decisions. Maybe not precisely correct, but still correct. I am sure many of you have horror stories of when bad decisions were made using bad data. I am equally sure that you have horror stories of bad decisions have been made on good data.  And, by the way, I am sure you have many stories of good decisions having been made on bad data.  Above all, I am sure that many of your horror stories will revolve around having known about something too late, and many of your good stories will revolve around having known about something quickly.  The value of knowing sooner is the central lesson to be learned from the famous Beer Game that illustrates the Bull-Whip Effect.

Also, let us not confuse the quality of the decision with the quality of the data. In other words, the decision might be directionally correct without being precise, and infinitely better than doing nothing. For example, it may be correct to split a purchase order (PO) for 1000 units and expedite part of the quantity in order to meet unexpected customer demand. We may chose to expedite 500 when it would have been better to expedite 600, but expediting 500 would be a lot better than not expediting any of the PO.  The decision to split the order and expedite part of it is 100% correct.  The quality of the data may mean the difference between expediting 500 and not 600.  I can accept that imprecision better than the inaction caused by waiting for “better” data before making a decision.

Naturally, we all want to avoid the situation where it would have been better not to split the order, but because of poor data quality a decision is made to split the order. In general I think the quality of supply chain data is a lot better than that.  The reason to have “data police” is that of course no-one knows which incorrect data will lead to disastrous decisions.

If the current data says “go North East” that is good enough for me. Leave it to the “accountants” to decide to “go 47 degrees 28 seconds”, especially if it takes 2 minutes to decide to “go North East” and 2 days to decide to “go 47 degrees 28 seconds”.  By the time the “accountants” have reached their conclusion, the entire demand and supply picture will have changed anyway.

In closing, I think we should all take a word of advice from Warren Buffet when he wrote in the Washington Post that “… it is better to be approximately right than precisely wrong.” I argue that most of the time waiting for precise data is precisely wrong, and that acting quickly based upon the existing data is approximately right.

1. Supply chain planning works best as a high-level, enterprise-wide discipline.
2. Adaptability is key.
3. Speed matters.

Would you add or change anything?

One line from the article caught my eye –

“… by its very nature, forecasting is more or less imprecise—too many supply chain disruptions cannot be predicted. Instead, the business world’s increasing volatility means that companies should strive for highly flexible operating models, processes, and plans that help them respond rapidly to economic, political, and market-driven changes.”   

So is this a supply chain planning mantra, or a supply chain response mantra?  The lines are blurring aren’t they?

It is this re-emergence of e-commerce that has given the consumer the buying power.  Of course, the recession has had a role to play by making price a key buying criterion, possibly the key criterion.  But e-commerce allows the consumer to compare several alternatives, in terms of both brand and price, in a fraction of the time and with greatly reduced effort.  While mall shopping isn’t going away any time soon, there is no doubt that e-commerce has shifted the buying power to the consumer through ease of use and ease of choice.  For example, my daughter went to the mall with a friend and came home excited about a skirt she had seen in a store but couldn’t afford it.  My wife called her friend to get a few more details and then spent about 20 minutes on the internet finding the best deal, which was 30% less than the store price, including shipping.  It would have taken her at least 20 minutes to drive to the mall and the 30% reduction does not include the cost of driving to the mall.  And it arrived in time for Christmas.  What’s not to like about this story?

So how does this relate to our market, which is much more in the low volume, high mix and build-to-order category, rather than the high volume, low mix and make-to-stock environment typical of CPG?  As has been commented by many people before me, retail-like behaviour is being adopted in more industrial environments.  I visited a fab-less semiconductor manufacturer in late December that is wrestling with increasing demands for a much wider choice of product capabilities coupled with expectations of greatly reduced order to delivery lead times.  The lead time expectation is a lot less than the manufacturing lead time so the semiconductor manufacturer is looking at postponement strategies including, very importantly, die reservations in the foundry, which of course they do not own.  Because of a greater product portfolio they cannot afford to keep the same levels of inventory because of the associated risks of price reduction and obsolescence.  As I stated in the opening paragraph, the adoption of consumer behaviour in a business-to-business environment has been increasing over the past few years, and will only accelerate.

Perhaps it is Lora’s point about the effect Wal-Mart is having on the supply chain that best captures the impact consumer and retail behaviour is having on the larger manufacturing sector.  Because Wal-Mart is such a dominant player, initiatives enforced by Wal-Mart soon trickle down the supply chain through multiple tiers of supply and affect other industries too.  Lora selects 3 initiatives: “sustainability scorecards, rethinking inventory strategies, and the initiation of the Supplier Alliance Program.”

Let’s start with inventory.  For centuries, inventory has been used as a buffer between demand and supply, starting with grain silo’s and other food stores.  The fab-less semiconductor manufacturer I mentioned above is, like many other manufacturers, adopting postponement strategies including reducing inventories to preserve cash, while at the same time being faced by the need for shorter order to delivery times.  Obviously there is a lot that can be done to improve manufacturing flexibility and shorten change-overs, but the biggest gains are to be had in reducing the order processing times, especially the time it takes to determine if the order can be delivered on time and in full.  Given the reduction in inventory, the issue has gone from available-to-promise (promising from finished goods inventories) to capable-to-promise (determining if the products can be manufactured in time), blurring the distinction between execution and planning.

The sustainability scorecard will perhaps have the biggest and widest long term effect on the supply chain.  As stated in a New York Times article, “In the future they may also have information about the product’s carbon footprint, the gallons of water used to create it, and the air pollution left in its wake.” With the impact of environmental legislation also trickling through the supply chain, particularly the electronics supply chain, it will only be a short time before a full product sustainability scorecard will be required including “carbon” accounting.  I think it is only some time before we will have a “carbon cost of goods sold.” And, as commented on in the NYT article by Tim Marrin, associate director of external relations for Procter & Gamble, “The last thing a supplier really wants is when you’re doing a separate index for every retailer.”  Wal-Mart has the market “muscle” to see this through and to ensure a standard is adopted across the industry.  For assembled products, such as consumer electronics, this means that the suppliers to the brand owners will also have to conform.  Which is how we will see the “trickle down” effect influence the adoption of a sustainability index on labels permeate other industries.  To be fair to high tech, particularly computing, they have had a start rating in effect for some years.  But the Wal-Mart initiative will take this to a whole new level of detail and accountability.

Am I just still too full of Christmas “cheer”?