6 Bold and Creative Techniques for Supply Chains to Weather a Stormy Market

What would you have done with your supply chain in 2007 if you knew what was about to transpire in 2008/9?

The Institute of Supply Management (ISM) data shows that the US manufacturing index has been below the break-even level for three consecutive months after thirty nine months of growth. Will the trend continue? If so, how long and will it get worse? Is the slowdown in China going to have a significant impact on the rest of the world? It remains to be seen.

It’s déjà vu all over again and perhaps the third time since the turn of the century for the global economy to tread water and decline. How are companies dealing with this? The least mature organizations will wait and just react – it will be ugly. Leaders have begun to orchestrate their entire value chain and make changes now that will provide buffer during the downs and catapult them out when growth resumes. Existing Gartner clients can read: Gartner’s Demand-driven Value Network Maturity Model.

What role should the Chief Supply Chain Officer (CSCO) or head of supply chain undertake to stay ahead of the storm?

 

IBM

The Great Depression of the 1930s presented an “unprecedented economic challenge, and Thomas Watson, Chairman of IBM, met the challenge head on, continuing to invest in people, manufacturing, and technological innovation despite the difficult economic times. Rather than reduce staff, he hired additional employees … – not just salesmen … but engineers too.” (Wikipedia)

The trajectory that IBM had after World War II catapulted them ahead of the rest of the industry. It took many technology disruptions, including one that IBM created themselves, and nearly 50 years for IBM to relinquish its position as the world’s most dominant technology company.

What lesson does this provide for supply chain organizations today? Does the IBM approach to difficult economic times suggest an alternative universe of solutions? Was Thomas Watson the first Mode 2 Jedi?

At Gartner, we use the concept of a bimodal supply chain to distinguish between the daily operations of a business from the more strategic view of the future. “Mode 1” is defined as traditional state of supply chain and the everyday drill of cost reductions, delivery performance improvements, and the usual culprits of operational performance. “Mode 2” is an exploratory state, driven by innovative approaches, changes in the market, growth opportunities, and new models of business that impact supply chains. Watson was clearly in a Mode 2 conviction after the stock market crash. “Damn the torpedoes, full speed ahead!” (Admiral David Farragut). Existing Gartner clients can read: Gartner’s Disrupt or Be Disrupted – Defining the Bimodal Supply Chain.

 

Risk / Reward

Too often we’ve seen dramatically poor forecasts. While forecast accuracy is an interesting concept, when it comes to market dynamics, we have to consider whether we are inclined to bias ourselves more towards the positive and hit the gas pedal when it appears as the sky is the limit. And, do we tend to shrug off downward projections without understanding the real implications of such a laissez-faire attitude? In either case, betting wrong has impacts.

Usually, if we do not appropriately anticipate and prepare for a downward trend, the typical after-the-fact response is the venerable Mode 1 stereotype: cut people, stop all discretionary spending, and slam on the brakes. It’s a no holds-barred knee-jerk response. Who has not been there before?

How would we have dealt with the most recent market collapse in 2008-2009 if we knew in 2007 that it was coming? We only get one attempt at each challenge, what can we learn about the past that can be applied going forward?

 

Think Advanced Maturity and Mode 2! 6 Steps to Success

The typical supply chain response to a downturn is to shut down factories, layoff production workers, cut orders on all suppliers, shut down future-focused improvement activities, etc. This approach impacts the ability to grow in the future.

What if we approached this differently? Does the lesson of IBM in the 1930s offer us a window to view an alternative scheme? Proactive strategies fall into the realm of “an ounce of prevention is worth a pound of cure.”

  1. Let’s start with talent. Watson hired well ahead of the curve in the 1930s. While admirable in the 20-20 hindsight view it is not always possible. CSCO’s should approach a potential downturn as an opportunity to retool the organization and to acquire skills that the supply chain knows it will need in the future. Instead of purely reacting to the “cut 10% of the HC” directive from the CFO, have a plan in place to retool the organization.

Downturns usually unleash a wave of excellent talent available to the market. Be prepared to reduce your team by more than the 10% target and then begin the acquisition plan once the dust has settled. The CEO and CFO will applaud the forward-thinking. In their eyes, you will still achieve the cost reduction targets but be in a much better position to accelerate when the upward trajectory resumes.

  1. Do you know where your supply and demand is? If you are a mature organization with strong supply chain analytics capability, you clearly do. If not, you are driving somewhat blind, looking back at what has been accomplished but with no sense of what is coming. Don’t wait to start because it will be too late.

Why not partner up with the IT team immediately and seek out some critical target areas for better information and analytics to support your supply decisions. Regardless of your areas of strength or weakness, diving in now before you are asked to change will put the CSCO in the driver’s seat in advance of any challenges for the typical Mode 1 “cut headcount, shut down factories, etc.” request later on.

  1. Don’t wait until there is no choice and be forced to shut down factories and lay off employees. With a strong S&OP process in hand, CSCO’s can begin to evaluate how to reset manufacturing earlier as signals begin to drop. Instead of all-in reductions in work force after the fact, production shifts can be slowly reduced ahead of time without impacting key performance metrics, especially customer service and cost – as they lead to major exposures in revenue and margin. Existing Gartner clients can read: Gartner’s Hierarchy of Supply Chain Metrics.
  2. What downturn has not been met without asking your supply base to do something? The usual suspects come to mind: take back inventory, delay and cancel purchase orders, extend payment terms, cut prices, and compromise well-nurtured supplier relationships. These are all so typical in their Mode 1 demeanor. We can be much better than that. Key suppliers should be viewed as partners – this changes the entire dynamic when challenges arise.

The CSCO or CPO knows that the suppliers see the same avalanche coming their way. There is no better time to dust off the supplier relationship program and evaluate the entire supply base than beforehand. Who is performing very well (cost, quality, delivery, innovation)? Is it possible to shift more supply to these top-performers, especially in multi-sourced categories now? Have we lived with 3 or more suppliers in certain categories when, in reality, 2 is sufficient? It is very important to consider the myriad options ahead of time than to be stuck with a limited, mode 1 playbook later on.

  1. Risky Business! Yes, there is always the issue of risk with a more consolidated supply base, but what is more important now – cost optimization or overall risk? When we talk about risk-making and decisions, the CSCO must know what she is getting into. By understanding what data and intelligence exist about past downturns, the CSCO and CPO can make informed, low-risk decisions today instead executing a reactive response tomorrow.

Engaging top suppliers early demonstrates the trust and confidence the supply team has and creates enduring goodwill. Mutually advantageous strategies can be developed and called into action at the right time. We may be wrong about the projected situation but one might argue you’ll be better off by taking a Mode 2 approach. It’s only bad risk when you have no data or experience to judge with.

  1. You’re not alone in this – what opportunities are lurking? Take advantage of this and realize there are a number of ways for you to do so. First, you have colleagues in the same impending mess as you. Sharing experience and issues allows you to test ideas and find out from others what is or isn’t working for them. Gartner’s exclusive network of diverse and experienced supply chain executives provides an excellent opportunity to talk to someone who understands. Peer networking continues to be the most sought-after element of a CSCO’s repertoire with Gartner.

Next, look ahead of you in your value chain – you will see are customers in the same predicament. A truly orchestrated supply and value chain means that these upstream conversations already occur naturally and are an important facet of everyday supply chain engagement. Ask them about what they see, what they are considering and, you’ll find ideas to help key parts of your supply chain be ready in a holistic manner.

 

Check your mode, now.

Are you thinking ahead and considering innovative and unique ways to persevere through difficult times working out scenarios of what might be? How will you be prepared to respond? Will you wait before you plan on a response tactic? Or, will you lead the charge and start now – ready to pounce on the opportunities that will present themselves while the rest of the pack gets washed ashore? What knowledge assets do you have at your disposal to test ideas against?

 If you are interested in learning more, please go to Gartner’s Supply Chain page or contact me via LinkedIn.

 

If we don’t learn from our past, we are bound to repeat the same mistakes over again.

Michael Massetti is an Executive Partner with Gartner who really does enjoy being a supply chain professional! Seriously. All opinions are my own.

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Dealing with Big Data: From Quants to Smarts

For those tracking the world of Big Data and Analytics, you’ve probably heard of “Quants.” Just to be sure, a quant is the epithet of a person who is an expert in analytics and “quant”-itative analysis – thus the moniker “quant.” Quants are the people who businesses rely upon to illuminate the gnarliest analytical, mathematical, and numerical problems.

Quants play a crucial role in many industries and functional areas from health care and manufacturing to banking and retail supporting supply chain, finance, marketing, and more. As long as there are streams of data to understand, quants are here to stay. As the streams of flow into larger data lakes, especially with the Internet of Things (IoT) promising to generate gazillions of bytes more of data, quants have unparalleled job security. My former CEO at AMD, Rory Read, used to say that management’s role is to “torture data until the truth surfaces.” This role is relegated to data savants, a.k.a. The Quants!

“Torture data until the truth surfaces!”  Rory Read

One important area of focus for a company’s Business Intelligence (BI) activity is to identify the areas where more quantitative data analysis is needed. Many companies find themselves using high-performing employees mired in the laborious and unproductive practice of aggregating, rationalizing, cleaning, and reporting on data. BI and analytics programs drive to reduce the time needed to get information while allowing additional time for employees to dig deeper for fundamental, root-cause analysis capability, develop data models, simulate scenarios, and provide decision support.

Once the business achieves data cleanliness and stability, the focus changes from reporting and informing about past performance to anticipating and predicting future potential outcomes. Driving the business by looking exclusively through the rear-view mirror does not allow companies to avoid dangers lurking ahead. Once the ability to anticipate is in place, business discussions move from “what happened” to “what may happen” – scenario planning and modeling.

The migration to a forward-looking analytics model compels organizations to ask, “Are we ready for the ramifications that these BI development programs have on individual skills, management expectations, organization structure, and communications across the enterprise?” As the company evolves toward more anticipation-oriented and proactive decision-making based on data, the skills and disciplines required on the teams change. The questions management should be asking change, too. How will this actually work?

Teams must frame the decision scope and ensure clarity of the business problem(s) or opportunity(ies) being addressed. The quantitative analysis that follows will include reviewing historical data, establishing a hypothesis, gathering data, and performing the analysis. At the back-end of the process, decision makers must evaluate the results from the story that the data analysis conveys.

Trust is vitally important in both the data and the individual/teams doing the quantitative work. Verification never ceases. Critical statistical validation and thorough inquiry should always be the norm. Transparency of the analytical approach and assumptions is central to successful decision-making. If the models are used by upper management to guide and inform decisions, the underlying assumptions and algorithms used to provide the core information must be visible and understood by all involved.

“In the end, the science of analysis must be married with the art of intuition and experience to make BI programs bring the anticipated results.”

Thomas H. Davenport highlighted a number of key questions that everyone involved in the process should be asking in a Harvard Business Review article from the July-August, 2013 edition “Keep Up with Your Quants.” These questions included:

  • What was/were the source(s) of the data?
  • How well does the sample represent the population?
  • Were there outliers and did they affect the results?
  • What assumptions are in your analysis and models? Do any conditions render this invalid?
  • Why did you choose the specific analytical approach? What options did you consider?
  • How are you certain of causality vs. coincidental correlation of the outcomes with the variables used?

This type of inquiry has not been common or pervasive until recently. Management must understand the fundamentals and assumptions used to establish institutional confidence in the information and guidance that comes out of the analytics and decision support models.

In the end, the science of analysis must be married with the art of intuition and experience to make BI programs bring the anticipated results. Artificial Intelligence (AI) will play a more significant role in the future. In the meantime, the behaviors identified above are fundamental to the success of any analytics and BI program. It is necessary to keep strong and open relationships between the quants and the decision makers.

Do you want to be a quant? There are myriad opportunities across all industries and functional areas for individuals to delve into the world of quantitative analysis. As the data streams continue to grow exponentially with IoT to become tsunamis, the need will increase further. Quants will no longer be a luxury for business success, they will be necessary. The future will bring more AI into play – people working on data and models now are likely to grow and evolve to develop new AI algorithms.  Their role will expand to not only help evaluate data with known models, but also to create and maintain models that are intelligent and adaptive to update themselves. It’s an exciting future in Big Data, BI, Analytics, and AI!

Who’s your quant?

 

“I never guess. It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.” Sir Arthur Conan Doyle (Sherlock Holmes author)

 

Michael Massetti is an Executive Partner with Gartner who really does enjoy being a supply chain professional! Seriously.

All opinions are my own.