Many organizations end up in the undesirable position of running out of cash. All the time and attention of the top management is then consumed in fighting one payment crisis after another. The RBI’s new takeover policy has once again brought stressed loans in the spotlight and forced companies and banks to find effective means to improve operational performance and cash management. A recent report by ratings firm Fitch confirms that pressure on asset quality will continue in future. In FY15, the system non-performing loan (NPL) ratio rose to 4.6% of total assets from 4.1% in FY14. As per RBI’s financial stability report (FSR), this ratio might increase to 4.8% by September. After the RBI’s new guidelines have been issued, banks have become more aggressive in recovering dues. The new rules allow banks to take control of repeated defaulters by converting debt into equity and recover the arrears by selling the assets.

Initially, when an organization starts making losses, it starts withdrawing from its past reserves. Over a period of time, as past reserves are exhausted, working capital starts getting depleted in a non-linear manner. Cash crunch illustrates the case of a company that is precariously balanced. A small increase or decrease in cash can make or break an organization. The writing on the wall is clear — partial measures will not suffice. Theory of Constraints (TOC) provides some unorthodox solutions for getting out of this life-threatening crisis. In most cases, it is possible to overcome this constraint within 13 weeks, or one quarter. Here are five questions that the managements of stressed companies need to ask in order to take control of the situation and take corrective actions that lead to fast results.

Question 1: Where is your organization constraint currently? Is cash really your constraint?

TOC improvement methodology provides a simple and effective process for systemic improvement. The first step is to identify the weakest link or the constraint. The following step-by-step approach will help identify the constraint of a for-profit organization. The organization has a constraint in the market if it has a very large (~50%) share of the world market. Most organizations other than Microsoft, Intel or some niche players are unlikely to have this constraint. An organization has a constraint in orders when it delivers consistently more than 95% and on time in full (OTIF). Most organizations do not even have OTIF of 50%.

Cash Crunch: Precariously Balanced System

*All expenses excluding raw material; Raw material cost assumed as % of Net Sales = 50%

There will be a constraint in operations when organizations do not achieve OTIF of more than 95% despite receiving input materials on time. In case any organization’s equipment has an overall equipment effectiveness (OEE) greater than 90% on a 24X7 basis, then it will have a constraint in this equipment. If that’s not the case, then operational policies are turning a non-bottleneck into bottleneck, creating an artificial constraint.

When an organization has OTIF less than 95% and is unable to get input materials on time due to its inability to pay suppliers, it faces the worst type of constraint, that is, cash constraint. Cash shortage is not the same as cash constraint, though cash shortage will lead to cash constraint in due time.

Precariously Balanced System: Slight dip in cash at the beginning of the second month leads to rapid deterioration

Cash outflow to cash inflow time = 1 month

An organization has a cash constraint if and only if it has sufficient orders (OTIF < 95%), enough manufacturing capacity (OEE < 90%), a reasonable number of suppliers and yet suffers from material shortage as suppliers refuse to give credit. In this situation, the key issue is not sales, not even profit or loss — it is cash. Companies need to make decisions taking into account a key parameter, cash velocity. Cash velocity is defined as an increase in cash per unit of cash in one period of time. Let us assume that the totally variable cost (TVC) is 50% of sales and the time from cash outflow to cash inflow is one month. In other words, a cash induction of Rs. 50 will become Rs. 100 in one month’s time. Here, the cash velocity will be 100% per month.

Question 2: How are you making full use of the constraint? 

We need to squeeze as much throughput as possible through effective utilization of existing cash. Even a small increase in cash increases sales, throughput, OTIF and profit significantly. In most cases, it may be possible to overcome cash constraint in less than 13 weeks by increasing cash velocity. Therefore, it is imperative to prioritise actions to reduce cash-to-cash cycle time.

Reduction in customer payment time: More often than not, customer payment time is the single-largest component of the cash-to-cash cycle time.  Most managers think that when they reduce payment time by one week, they save interest cost only for one week. It is extremely important to note that even this small decrease in cash-to-cash cycle time increases cash velocity significantly, thereby impacting throughput non-linearly. As we get huge benefits from shrinking customer payment time, we must explore all possibilities, including discounts for immediate payment.

Shrinking manufacturing lead time: Drum-Buffer-Rope (DBR), the production solution of TOC, shrinks the manufacturing lead time by a factor of 2-10. This is particularly effective when manufacturing lead time is a significant part of the cash-to-cash cycle. For organizations that make capital goods, these tools help immensely in reducing manufacturing lead-time. In several cases, this paves the way for increased selling prices by offering reduced lead time. Firms that make to stock also benefit by reduced work in progress (WIP), and finished goods inventory, thereby releasing cash.

Reducing supplier lead time: This aspect is often overlooked and companies pay heavily by not modifying supplier policies in a cash-constraint situation. Reduction in supplier lead time is one of the important means of crashing the cash-to-cash cycle time, as the raw material inventory holding requirement comes down with the reduction in supplier lead-time. In some cases, it may also be worthwhile to switch to a supplier who has a higher price per unit but faster and more reliable deliveries, or is willing to supply in small lots. This may impact the gross contribution or throughput (though not significantly) but it can provide some much-needed liquidity. These decisions should be taken after evaluating the impact on affected parameters such as input price increase, reduction in cash-to-cash cycle time, reduction in raw material inventory requirement and, most importantly, improvement in cash velocity. While the above might seem like common sense, this is not common practice. Local measurements or departmental KRAs often prevent companies from adopting these practices.

Question 3: Can you subordinate policies to the constraint?

Functions in organizations do not work in a vacuum. Actions and decisions in one department invariably impact performance in other functions. All functions, departments and decisions should be aligned to get the most out of the constraint. In our experience, this is often difficult to implement, as it requires changes in existing practices and policies of local optimization.

Many organizations waste their most precious asset — cash — for purchasing more than the immediate requirement just because the purchase team can get a volume discount. This cash outflow starves the organization of other required materials, thereby jeopardizing full material availability. We have often observed that dispatches are held up because of non-availability of one of the insignificant inputs. This increases cash-to-cash cycle time and hastens bankruptcy. It is recommended to buy just the minimum quantity required for making ‘full kit’ for immediate production.

Similarly, chasing local optima in manufacturing leads to more production to achieve better capacity utilization. Plant managers produce more quantity of some products to save on set-up times. The additional production blocks cash and increases cash-to-cash cycle time, delaying other products. There is one common behaviour that I’ve observed almost every time I am called upon to turn around operations of a stressed unit. Organizations are extremely reluctant to change current business practices, be it in buying materials, manufacturing or selling.

Let me illustrate this through a case study. This client was in the business of making switches. It declared a loss for the first time after making profits for 42 years. The situation became extremely critical as suppliers stopped selling material unless paid upfront. Consequently, capacity utilization dropped to less than 50%. Totally Variable Cost (TVC) as a percentage of net sales was 40%, manufacturing lead time was three days and realization time was 60 days, as it was selling primarily to retailers. Every additional Rs. 40 would generate additional sale of Rs. 100 and cash inflow of Rs. 100 after 63 days, meaning every additional Re. 1 gets converted to Rs. 2.5 after 63 days.

When I asked the owner if it would be feasible to shrink realisation time by offering discounts, he refused point-blank, as this would increase losses even further. I suggested that we do this exercise on paper. I suggested that he could offer 50% discount for payment upfront. For every additional Rs. 40, we will have sales of only Rs. 50 (50% of 100). However, the conversion time now gets reduced to six days (three for manufacturing and three for getting the credit in the bank). Or, every additional Re. 1 will now generate cash of Re. 1.25 but after six days. After another six days, the Rs. 1.25 realized would generate Rs. 1.56 (1.25 X 1.25). Continuing this for 60 days, the initial Re. 1 would get converted to Rs. 9.31, a little less than four times of Rs. 2.5 being generated the conventional way. The organization offered this proposal in a segmented market and turned around in less than three months. Segmented markets are those where volumes sold in one segment do not impact volumes and prices in others.

There’s no magic to this — we just need to work out the rate at which cash is being generated in a period of time. Here, the existing cash velocity was about 55% per month and in the proposal, it was 205%. Ten years later, the company was sold to an MNC for Rs. 650 crore.

Question 4: Should you elevate (borrow or induct) cash at significantly higher rate of interest?

In most situations, recognizing that cash is the real constraint and exploiting and subordinating all organizational measures and policies to the cash constraint will shift the constraint either to orders or operations within 13 weeks. However, in extreme situations, it may be necessary to induct additional cash. For stressed assets, cash may be available only at a significantly higher rate of interest. Here, we must understand that for most organizations, cash velocity varies from 10-30% per month.  Hence, it makes sense to borrow even at a very high rate of interest, so long as it is less than the cash velocity. Another caveat is that partial induction of cash will not work. Either induct the total minimum required cash or none at all.

The main obstacles in overcoming cash constraints are the local measurements (sales, market share, tonnage, freight cost control and interest cost control) that companies continue to improve when in cash constraint. Continuing to use the same measurements leads to further deterioration of the situation. Companies do not fold up when they make losses, they shut when they run out of cash. Survival time is the period of time in which the existing cash can cover fixed expenses. Any action that has beneficial impact after the survival time is irrelevant. All actions should be taken to increase survival time by shrinking cash-to-cash cycle time.

Question 5: What should you do when cash constraint is broken?

Once the constraint has been overcome, go back to step 1: identify the current constraint. Where is your constraint now — is it in orders, operations or supplies? Do not let inertia be your system constraint.

This article was co-authored by Ira Gilani Lal