Month: February 2016

Time and Inventory Strategy

I was in Poland recently looking out the hotel window at the town’s historic clock tower – still in operation after about 400 years – and started pondering how time shapes the modern supply chain.  Time is the lens that focuses all supply chain planning decisions.  Distance is time.  Inventory is time.  And Time is money.  For any consumer facing organization, our ability to make decisions in a ‘timely manner’ is nothing less than a matter of corporate survival.

Our planners hold the customer satisfaction in their hands.   As they balance the dynamics of demand against the constraints and limitations of supply, we need to recognize that the feasible, financially viable options available to planners have been dictated by earlier choices.  The decisions that limit their current choices were made days, weeks, or even months earlier.  But a planner’s life is pretty straight forward, right?  They only have to answer one question:   What customer demand can we meet today?

If the answer was, ‘All of it’, the job really would be easy.  Yes there would be questions about inventory, but we’ll talk about that later.  Very rarely is all demand being satisfied.  So more questions get asked:

  • If not today, then when?
  • When can we ship it?
  • When can we make it?
  • When can we receive it?

This is where the planner’s job get complicated.  As we drill down into each of these questions, we realize that they are interconnected:

  • The demand we can meet today depends on what’s in stock.
  • If it’s not is stock, it depends on what has shipped within a transportation lead time.
  • What we can ship depends on what we produced a manufacturing lead time before that.
  • What we can manufacture depends on what we scheduled a planning cycle before that.
  • What we can schedule depends on the available components that were ordered a procurement lead time before that.

Let’s go back to the first question as the place to start working our way back through the decision points that drive supply chain strategy and inventory policy.  “What customer demand can we meet today?” Before we start crunching numbers to come up with an answer, consider a more fundamental question and one that drives continuous supply chain improvement:  How long is the customer willing to wait to take possession of the product?   The duration the customer is willing to wait versus the time (and cost) it takes for us to ‘get’ more is the primordial equation of supply chain management.  ‘Demand Latency Potential’ (DLP) is the duration a customer will wait between selecting to procure a particular, fully specified item, and taking possession of that item, before selecting an alternate item or foregoing the procurement altogether.

DLP can range from less than a second to years.  From the chewing gum impulse buy while standing in line at the grocery store, to waiting for the ‘Back to the Future’ hover-board.  We normally think about this in terms of manufacturing Getting strategy.  The higher the DLP – the longer the customer is willing to wait – the longer we have to create the product and the further ‘upstream’ we can hold inventory.  We don’t craft our supply chain strategies on an empty whiteboard. Our customers have already decided on the boundaries within which we need to work.

The further upstream we can hold inventory, the shorter the ‘Commitment Horizon’.   Commitment Horizons are the durations between committing funds to procure, convert, or transport and the customer taking possession and paying for the product.  We want the shortest Commitment Horizons possible to collapse the time between spending and collecting money.  Most customers will not wait the full value stream lead time for most industries and products with which we work. Take the time to understand, differentiate, and segment customers and products based on DLP.  Once we clearly understand DLP, we can compare it to the cumulative value stream lead time.

The difference, along with accounting for variability, is the amount of time and money you need to invest in inventory to bridge the gap.  Before each shipment point and point of conversion, we can decide to hold inventory to close the DLP gap.  This is where factors relating to demand variability, risk pooling, and total cost analytics are leveraged in multi-echelon inventory optimization.

We are trying to minimize cost while at the same time maximizing feasible planning options.  Because of market imperatives, we employ postponement strategies, delaying customization by holding inventory at the component and sub-component level while waiting for a more accurate customer demand signal.   Investing in critical, hard to obtain and long lead time raw materials may be part of the strategy to shrink the time to fulfill – and react to changes – customer demand.

Following the DLP vs Strategy Curve in Figure 2 is like traveling back in time through the conversion points in the product structure illustrated in Figure 1.  Somewhere along the curve lies the right blend of manufacturing and inventory strategies that are appropriate from an order fulfillment and inventory investment standpoint, to support your business model.

Determining these strategies can quickly become overwhelming.  There are powerful Inventory optimization and Strategic Analysis software packages on the market to support this decision-making process.  They don’t however, fully take the place of deliberate, clear thinking when crafting a comprehensive supply chain strategy.

So as planners sit down each morning to make the decisions that are driving customer satisfaction, understand that they really make many, interrelated decision over different horizons.  When you design your supply chain, take the time to decompose these decisions.  Follow them back to the business drivers and create an integrated strategy that allows planners to take powerful actions.

Getting Inside Decision Cycles

“There is always a latent tension between what facilitates timely decision and what promotes thoroughness and accuracy in assessment.”

Many of the supply chain planning software implementations on which I’ve worked have felt like quests to cram more data into the solution to enable the planners to make ‘perfect’ decisions.   This idea that more data means better decisions – that somehow if we could just get a little more data, the software could calculate a near-perfect, optimized plan – can become distracting and lead implementations astray.

These conversations remind me of my experience in the US Marine Corps.  The art of warfighting came down to making imperfect decisions, with incomplete information, but executing them… well, let ’s just call it ‘vigorously’.  We talked about getting inside the enemy’s decision cycle.  That ability to interpret the environment, reassess, adjust, communicate, and press on more quickly than our foes was one of the keys to success on the modern battlefield.  The decisions did not need to be ‘perfect’, but they did need to be ‘good enough’ on a timely basis.

The military has talked about the O-O-D-A loop for decades.  It is in fact, the foundational concept behind the Marine Corps model of maneuver warfare.  The ideas have filtered throughout the business community, but as they were passed on, some of that original messaging was lost.

This is not a single loop.  There’s a crank on the side of this wheel that needs a strategic focus to turn.  The companies that turn this faster gain strategic advantage, but what’s the differentiator?  This comes down to one box on diagram: Orient.

Orient.  Understanding, interpreting, and synthesizing information is what good companies do well. They are very efficient at orienting in the OODA loop by filtering out noise and distractions. Organizations focus their view of information and streamline decision making by defining effective metrics.

Misalignment in the metrics strategy can cause an isolated, high visibility service failed to create the impression of broader problems, while an endemic weakness may not be apparent in the granularity of the data at specific nodes in the network.   ‘Correct’ metrics will depend on the supply chain strategy and the future state organizational model.

A fully realized Performance Measurement System is the underpinning of effective tactical and strategic decision making. It enables an organization to

  • Monitor (Observe):  Track performance for reporting
  • Control / Diagnose (Orient / Decide):  Highlight when the supply chain operations require modification or attention
  • Direct (Act):  Use of metrics to focus activities and as a foundation for personnel evaluation

The steps for implementing an effective Performance Measurement System are easy to list, yet deceptively difficult to carry out.

  • Metrics Definition
    • Select appropriate metrics to monitor supply chain performance
    • Establish clear goals
  • Data Management
    • Define data required to support metrics and operational statistics
    • Determine mechanisms for storing data and displaying metrics
  • Performance Tracking and Root Cause Analysis
    • Define process and organizational responsibility to track performance and identify points for further analysis
    • Define root cause analysis / corrective action process and mechanisms

Effective, efficient decision making.  Cranking that OODA faster than your competition; fast enough to keep ahead of the market.  These are critical factors for success when conducting operations with the Marines or guiding your supply chain organization.

Talk to MEBC today about creating this foundation for your supply chain operations.

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