In our previous article – Lean Working Capital; the gift that keeps on giving – we introduced the term SETPOINT to describe a working capital steady state in which a supply chain operates in harmony with all internal and external stakeholders, improving not only working capital but also top line and cost.
This article will explore the reasons why companies often find themselves operating with excess working capital – without fully understanding their setpoint targets in the first place – and why an incremental approach to improve this situation is advised. We will discuss the use of structural- and rapid-cash approaches in following articles (refers to figure 1 below).
FIGURE 1. Incremental vs. Structural vs. Rapid Cash approach
A working capital SETPOINT is challenging to find – let alone reach – as it involves multiple stakeholders with often conflicting strategies, targets and KPIs. These conflicts are not only prevalent in a company’s relationship with its external stakeholders, but internally as well. We find that many companies’ individual functions are inclined towards solutions favoring themselves, with less focus on the carryover effect on neighboring areas of the supply chain – often resulting in a sub-optimization of the supply chain as a whole. We call this inclination SUPPLY CHAIN BIAS.
Distinguishing between inherent supply chain constraints and supply chain bias –by inherent constraints we refer to the underlying working capital drivers (e.g., capacity, complexity, predictability, and lead-time) that together determine the levels required to sustain or grow your business. These drivers are what defines your true setpoint and it will remain what they are unless a structural change.
Supply chain bias on the other hand refers to often informal mechanisms put in place to offset local symptoms of supply chain inefficiencies, or in response to misaligned processes and/or incentive structures. These symptoms are often subjectively perceived, with multiple interpretations across Sourcing, Operations and Commercial functions (see Nordstrom Advisory’s Cash Conversion Cycle model for reference). Some core reasons for supply chain bias we have encountered include:
SAFETY BIAS Person installing or modifying process buffers to secure own delivery, e.g., issues with missing input materials, leading to costly over-night deliveries and delayed production starts, made the inventory planning manager increase safety stock levels of missing items, as well as move receipt date ahead of time for future deliveries.
HEDGING BIAS Person modifying input planning assumptions to increase likelihood of meeting own priorities, e.g., more or less frequent issues in production, leading to delayed shipments and some lost orders, made the sales manager over-forecast future demand to increase availability and pick-rate of his/her goods.
INCENTIVE BIAS Person incentivized to improve specific performance metrics disregarding effects on the business as a whole, e.g., a top-down drive for improved DPO made purchasing push standard supplier terms from net 45 days to net 90 days in one go, leading to weakened supplier relationships and a long-term negative effect on supplier pricing and service level.
TECHNICAL BIAS Person seeking to optimize a specific assets performance, disregarding implications to the larger value chain as a whole, e.g., in order to reduce in-process waste, engineering recalibrated its equipment to allow for multiple variation SKUs, driving complexity and reduced flexibility (see case example below).
LEGACY BIAS Person holding on to anecdotal evidence and company folklore describing terrible things that have happened in the past when someone tried to make a change, regardless of what current data and logic would say. Case example – incentive and technical bias
A multi-billion USD vertically integrated company with a diverging supply chain saw a massive build-up of work-in-progress inventory, increasing logistical costs and a failing service delivery performance.
Some background: operations had all but eliminated its downstream in-process waste. This was achieved through heavy customization of upstream products, creating a multitude of unique and end-customer specific work-in-progress SKUs – limiting flexibility to reallocate and meet the frequent changes to short-term demand.
A review showed the company could reduce internal SKUs by a factor of 10 by implementing fewer standard sizes – with minimal impact on cost, as any subsequent increase in downstream in-process waste would go back as input material to own processes - using return freight. The reduced complexity resulted in significant improvements to working capital, logistical cost as well as delivery performance.
Implications of a supply chain bias – the activities and precautions originating from a supply chain bias can often make sense at first or even second glance. However, the habit of hedging or buffering to offset a symptom – rather than solving the underlying problem – tends to have long term negative effects:
It leaves the problem unsolved and fosters a culture of complacency rather than continuous improvement;
It creates disturbances to the natural flow of a supply chain, with a negative effect on process stability as well as trust between internal and external stakeholders – often resulting in additional biases piling on each other, impacting not only working capital but also service delivery performance and cost;
It builds up “wrong” type and often slow-moving working capital – taking space from in-demand high runners – creating an imbalance in the supply chain set-up. This imbalance reduces flexibility to meet changes to short-term demand, as well as the agility to move quickly and adapt to new market situations; also
When left unattended for too long, it often becomes the truth. Most legacy biases are reminiscences of safety- or hedging biases of the past.
Moving beyond supply chain bias towards your setpoint – as discussed, to understand and subsequently reach a working capital setpoint, a company must first distinguish its inherent constraints from its supply chain bias. Then, it must realize and resolve the underlying issues which put the biases in place to begin with. Only then is it safe to strip away the excess working capital layers.
The interdependencies between process inefficiencies and working capital were already addressed as part of the original Lean concept and became famous in the analogy “The Japanese Sea”. The analogy imagined a boat sailing across an ocean: below the surface rocks were protruding from the seabed, but if the water level was high enough there was no danger to the boat.
The boat symbolizes a company’s business processes and the water represents the working capital level maintained to keep the processes moving. The bottom of the sea in turn represents the daily performance of the various stakeholders involved in the process, and the rocks your supply chain inefficiencies.
A common interpretation of the analogy suggests a company should start by draining the water – to expose the underlying inefficiencies – and thus force a problem-solving approach. However, draining the sea without first reducing or removing the inefficiencies will strand the boat. And how do we react to a stranded boat? We restore the water to its original level – or even higher for extra safety measures.
This is a reason why many companies struggle to maintain working capital improvements: they force a reduction before underlying inefficiencies are resolved, often leading to issues with delivery performance, quality and cost. Also, if not understanding their setpoint level, they face the risk of cutting too deep, adding fuel to the fire. The fastest solution to this situation will always be refilling working capital.
Nordstrom Advisory’s Lean Working Capital takes a holistic and customer-centric approach on the full cash conversion cycle – highlighting the importance of understanding your true setpoint level, and to reduce or remove the relevant protruding rocks before lowering the water level. However, this is not easy:
FIRST – Biases are not always easy to spot Inefficiencies and their symptoms are often interpreted differently: a bias is subjective by nature, and the person who installed it in the first place might not even be aware it is a bias. In cases where the person would be aware, there is often an element of mistrust towards the organizations’ ability to identify and solve the underlying issue, making him/her less prone to step forward.
SECOND – Underlying root causes are not always easy to fix It is not always easy to identify and agree on the underlying root cause. And – even though companies often find low hanging fruits, some of the issues and root causes can be complex and time consuming to resolve. Also, sometimes the solution would have a direct negative impact on individual performance metrics, even though supply chain as a whole benefit; and
THIRD – it will take time and effort All above must be done in parallel to daily operations, on top of an often already full workload – in competition with other pressing initiatives. It is often not a sprint consisting of a few larger activities, but rather several incremental steps towards a setpoint.
In conclusion – Companies should invest time and resources to identify and remove its supply chain biases – as part of achieving its working capital setpoint. They should also resolve relevant underlying root causes to supply chain inefficiencies before attempting to reduce its related working capital levels.
A setpoint steady state is not achieved through few larger activities, but through multiple incremental steps over time. However – in order to secure resources, structured approach, and top management’s attention, we recommend a focused working capital program to kick-start and get momentum.
Many companies decide to solicit advice and feedback from external experts, to identify and support removal of biases from their supply chains. An objective third party view also helps with moving focus from individual KPIs to a holistic and integrated supply chain approach.
More on Nordstrom Advisory’s LEAN WORKING CAPITALTM in coming articles.