Agile Demand-Supply Alignment – Part 1A

Responding to Demand Volatility and Supply Disruptions After Plans are Set and Orders Placed.


The capability to effectively realign supply and demand, during execution, in the face of demand volatility and supply disruptions, has become critical for survival and success. The global pandemic has simply put a giant exclamation point on the uncertainty that retailers, distributors, and manufacturers have always had to contend with.”


This article is an excerpt from the report Agile Demand-Supply Alignment — Part One: ADSA Elements and Examples.
A copy of the full report can be downloaded here.

This is the First in a series of articles on Agile Demand Supply Alignment.

Aligning Demand and Supply When ‘Stuff Happens’

The Need for Agile Demand-Supply Alignment

The global pandemic put a giant exclamation point on the uncertainty that retailers, distributors, and manufacturers have always had to contend with. A tremendous amount of effort and expertise is put into forecasting, supply planning, supplier vetting and selection, contract negotiations, ensuring the right purchase orders are placed at the right time, and that shipments are destined for the right destinations in the right mix and quantities. Yet, regardless of how good companies get at planning, ‘stuff happens’ and companies then need to be able to rapidly adjust to the evolving actual situation on the ground.

Between the time orders are placed with suppliers and the time those goods arrive at the factory, DC, or store, lots of things can change: actual demand deviates from the plan (sometimes dramatically) and supply/logistical disruptions and delays occur (sometimes catastrophically).

Now, more than ever, companies need the ability to rapidly adjust and change inbound flows at each stage in the process, to deal with unplanned changes. That includes slowing down, speeding up, or altogether changing production plans before orders are shipped, as well as the ability and agility to make post-shipment logistical and executional adjustments, such as changes to shipment destination, changing modes, consolidation and deconsolidation, merge- or split-in-transit, hold at intermediate locations, expedite, transship, and so forth. We refer to this capability for extreme flexibility in post-order execution as Agile Demand-Supply Alignment (ADSA).

Phases of Planning and Execution

As illustrated in Figure 1 below, the activities involved in planning and execution can be viewed as having three phases:

  1. Preparation phase: An enormous amount of capability-building, relationship-building, planning, negotiation, and preparation activities happen well before an order is placed with a supplier. This is the most consequential phase, as agility in execution is all about preparation before execution. Using the analogies of a sporting match or a military campaign, the team or army that wins is generally the one that has the best recruiting, training, equipment, motivation/discipline, and preparation. Below we discuss Examples of Specific ADSA Capabilities , all of which involve considerable pre-order capability-building.
  2. Production phase: In a make-to-stock model, production usually starts before orders are received. In a make- or assemble-to-order2 model, production or assembly starts after an order is received. From the perspective of the buyer, there are a specific set of ‘levers’ they can pull if demand starts deviating from plan. These can include requesting expedited or delayed production, leveraging alternate sources of supply, helping the supplier resolve material shortages or production or quality issues, reallocating existing supply or capacity, and using demand shaping to redirect, accelerate, or slow down demand. The availability and effectiveness of those levers depends in large part on actions taken before the order was placed.
  3. Logistics Phase: This overlaps somewhat with the production phase, because loads are tendered, shipments booked, and containers requested before the order/shipment is actually picked up and shipped. The levers available to make adjustments in this phase are different from the production phase, but with some overlap. Shipments may be expedited, rerouted, or merged-in-transit. In addition, alternate sources of inventory might be leveraged, existing supply reallocated, and demand shaping used.
Figure 1 – Demand-Supply Alignment Enablers During Different Phases of Planning and Execution

Early Awareness of Issues Enables Broader Choice of Resolutions, Lowering Costs

The sooner that deviations from plan are known, the wider the range of options available to deal with the issues. If a shortage is known early enough, then alternate sources of supply might be leveraged, whereas after a certain point it is too late for that. Similarly, when leveraging existing inventory from another location, expediting fees may be avoided if the issue is known on time. Furthermore, when customers are warned of impeding shortages or schedule slippages early enough, it gives them more opportunities for making adjustments. Customers would much rather know sooner, than finding out at the last minute that their order will be short or late.

Demand shaping is one lever that can sometimes be done with very little lead time, such as changing the price on a website. However, demand-shaping often cannot be done instantly, such as when promotional campaigns need to be planned and executed, partners and employees notified, physical goods moved (e.g. for more prominent placement), price stickers changed, and so forth.

Figure 2 – Different Demand-Supply Alignment Actions Require Different Lead Times for Completion

Accelerated Planning Cycles — Evolving to Continuous Planning

For the past three decades, planning cycles have gotten shorter and shorter across virtually all types of supply chain-related planning including forecasting, sales and operations planning, supply planning, and logistics planning. These have gone from monthly to weekly to in some case daily. In fact, we are moving to an incremental, continuous planning model, where inventory, demand, and orders are being constantly monitored. These algorithms are typically designed to avoid nervousness in the system — i.e. they don’t keep making changes to plans, but rather make changes only when the benefits of changing the current course of action outweigh the costs of changing course by some threshold amount.

These same trends have blurred the lines between planning and execution. The planning process is now embedded within execution processes. Furthermore, much of the same technology that has enabled faster compute cycles3 has also enabled much more granular/detailed, rich, timely planning models.

Tactical vs. Strategic Adjustments

Typically, ADSA involves making tactical adjustments to align demand and supply, such as those discussed above (e.g. changes to production schedules, expediting shipments, etc.). However, in highly disruptive times, as we are going through now in the pandemic, the need for more drastic, yet extremely quickly executed strategic adjustments becomes imperative for survival. This could involve changing a company’s product, market, or channel strategy within an intensely short period of time. For example, Twin City Die Castings’ main business was making automotive car parts. When General Motors and Ford halted production early in the pandemic, orders dried up. Twin City almost immediately pivoted to an opportunity to make pistons for ventilators. These are quite different from automotive pistons. They compressed what would normally be months of development work into a few days and began producing pistons shortly thereafter. It was a matter of survival. In another example, when the COVID 19 pandemic hit, the demand for commercial toilet paper all but disappeared, while the demand for consumer toilet paper took off. The raw materials, manufacturing processes, and machinery for consumer toilet paper are all different from those used in commercial toilet paper. The manufacturers not only brought on every bit of idle capacity they could find, but some of them retooled machinery in order to meet demand. A third example is large food service companies whose primary business has been supplying restaurants and cafeterias. When demand from their usual customers collapsed, some of them pivoted to supplying grocery stores and selling direct to consumers online.

Probably the most widespread strategic shift during the pandemic has been massive ecommerce adoption. Ecommerce sales are expected to grow by over 18% this year, while store sales have simultaneously collapsed during the same time. One apparel brand company we spoke with saw their ecommerce sales increase by 15 times. For many retailers, the ability to rapidly ramp up their ecommerce fulfillment capabilities and things like curb-side pickup, is making the difference between surviving vs. going out of business during the pandemic.

Systemic Agility and a Culture of Agility

Excellence at aligning demand and supply requires both ‘systemic agility’ and a ‘culture of agility.’ Systemic agility is where agility is built into a company’s systems and processes. Systemic agility is most important during normal times, because it creates repeatable and reliable agility in response to normal fluctuations in demand and supply. Systemic agility will be the main focus of most of the rest of this paper.

A ‘Culture of Agility’ is where employees are encouraged to be constantly on the lookout for the next big pivot or shift the company needs to make, and are ready, willing, even eager to take an all-hands-on deck, no holds barred approach to rapidly implementing dramatic changes. Companies like Tesla and Amazon are good examples — ready to take big risks and evolve quickly. Working in these kinds of companies can be quite stressful or exhilarating, depending on the disposition of the employee. A culture of agility helps companies make radical strategic changes quickly, which can be essential during highly disruptive times such as the pandemic.

Undersupply vs. Oversupply

Deviations from plan can cause both undersupply and oversupply situations. These may be localized, such as a shortage of an item at only one or a few specific locations. If there is a simultaneous oversupply of the same item elsewhere in the network, it may be possible to ship inventory from the oversupplied locations to the undersupplied locations. At a minimum that extra step of transshipping from one location to another eats into profit. For low-value high-weight/cube items, it is often simply not worth the cost of shipping them. This is one reason companies are trying to get smarter about better assortment and range planning, as well as holding back some portion of inventory at centralized locations until demand is more precisely known.

Figure 3 – Undersupply and Oversupply Scenarios — Both Have Negative Consequences

Both undersupply and oversupply are undesirable. Undersupply can result in lost sales and lost customers. Oversupply erodes or even decimates profits. Undersupply is usually more time-critical to address. The greater the delay addressing undersupply, the greater the impact on the cost and feasibility of solutions, as well as on customer satisfaction. Though less time-critical, oversupply situations still should be solved in a timely manner. At a minimum, there are carrying costs being incurred. There may be other reasons to act soon. For example, the earlier in a season that a markdown ladder can be adjusted for a slower moving item, the less profit is eroded by being forced to make more dramatic markdowns or liquidation at the end of the season. Similarly, cancelling orders or productions runs before it is too late avoids exacerbating an existing oversupply problem.

The next installment, Part 1B of this series, provides a framework for the elements of ADSA: Detect, Understand, Prioritize, Decide, Act, Monitor.


1 Execution happens primarily between the time an order is placed with the supplier until the goods are delivered. Execution, as defined here, includes both production and logistics. — Return to article text above
2 Similarly, in a design-to-order or engineer-to-order model, production doesn’t start until after an order has been placed. — Return to article text above
3 The speeding up of planning cycles has been largely enabled by in-memory computing models, highly scalable and elastic compute services, and increasing hardware speeds. What used to take many hours, or even days in previous decades can now be done in minutes or even seconds. — Return to article text above

To view other articles from this issue of the brief, click here.

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