Working Capital Strategy Revisited

This entry is part 3 of 3 in the series Working Capital

Introduction

To link the posts on working capital and inventory management, we will look at a company with a complicated market structure, having sales and production in a large number of countries and with a wide variety of product lines. Added to this is a marked seasonality with high sales in the years two first quarters and much lower sales in the years two last quarters1.

All this puts a strain on the organizations production and distribution systems and of course on working capital.

Looking at the development of net working capital2 relative to net sales it seems as the company in the later years have curbed the initial net working capital growth:

Just by inspecting the graph however it is difficult to determine if the company’s working capital management is good or lacking in performance. We therefore need to look in more detail at the working capital elements  and compare them with industry ‘averages’3.

The industry averages can be found from the annual “REL Consultancy /CFO Working Capital Survey” that made its debut in 1997 in the CFO Magazine. We can thus use the survey’s findings to assess the company’s working capital performance4.

The company’s working capital management

Looking at the different elements of the company’s working capital, we find that:

I.    Day’s sales outstanding (DSO) is on average 70 days compared with REL’s reported industry median of 56 days.

II.    Day’s payables outstanding (DPO) is the difference small and in the right direction, 25 days against the industry median of 23 days.

III.    Day’s inventory outstanding (DIO) on average 138 days compared with the industry median of 23 days, and this is where the problem lies.

IV.    The company’s days of working capital (DWC = DSO+DIO-DPO)5 have on average according to the above, been 183 days over the last five years compared to REL’s  median DWC of 72 days in for comparable companies.

This company thus has more than 2.5 times ‘larger’ working capital than its industry average.

As levers of financial performance, none is more important than working capital. The viability of every business activity rests on daily changes in receivables, inventory, and payables.

The goal of the company is to minimize its ‘Days of Working Capital’ (DWC) or which is equivalent the ‘Cash Conversion Cycle’ (CCC), and thereby reduce the amount of outstanding working capital. This requires examining each component of DWC discussed above and taking actions to improve each element. To the extent this can be achieved without increasing costs or depressing sales, they should be carried out:

1.    A decrease in ‘Day’s sales outstanding’ (DSO) or in ‘Day’s inventory outstanding’ (DIO) will represent an improvement, and an increase will indicate deterioration,

2.    An increase in ‘Day’s payables outstanding’ (DPO) will represent an improvement and an decrease will indicate deterioration,

3.    Reducing ‘Days of Working Capital’ (DWC or CCC) will represent an improvement, whereas an increasing (DWC or CCC) will represent deterioration.

Day’s sales- and payables outstanding

Many companies think in terms of “collecting as fast as possible, and paying as slowly as permissible.” This strategy, however, may not be the wisest.
At the same time the company is attempting to integrate with its customers – and realize the related benefits – so are its suppliers. A “pay slow” approach may not optimize either the accounts or inventory, and it is likely to interfere with good supplier relationships.

Supply-chain finance

One way around this might be ‘Supply Chain Finance ‘(SCF) or reverse factoring6. Properly done, it can enable a company to leverage credit to increase the efficiency of its working capital and at the same time enhance its relationships with suppliers. The company can extend payment terms and the supplier receives advance payments discounted at rates considerably lower than their normal funding margins. The lender (factor), in turn, gets the benefit of a margin higher than the risk profile commands.

This is thus a form of receivables financing using solutions that provide working capital to suppliers and/or buyers within any part of a supply chain and that is typically arranged on the credit risk of a large corporate within that supply chain.

Day’s inventory outstanding (DIO)

DIO is a financial and operational measure, which expresses the value of inventory in days of cost of goods sold. It represents how much inventory an organization has tied up across its supply chain or more simply – how long it takes to convert inventory into sales. This measure can be aggregated for all inventories or broken down into days of raw material, work in progress and finished goods. This measure should normally be produced monthly.

By using the industry typical ‘days inventory outstanding’ (DIO) we can calculate the potential reduction in the company’s inventory – if the company should succeed in being as good in inventory management as its peers.

If the industry’s typical DIO value is applicable, then there should be a potential for a 60 % reduction in the company’s inventory.

Even if this overstates the true potential it is obvious that a fairly large reduction is possible since 98% of the 1000 companies in the REL report have a value for DIO less than 138 days:

Adding to the company’s concern should also be the fact that the inventories seems to increase at a faster pace than net sales:

Inventory Management

Successfully addressing the challenge of reducing inventory requires an understanding of why inventory is held and where it builds in the system.
Achieving this goal requires a focus on inventory improvement efforts on four core areas:

  1. demand management – information integration with both suppliers and customers,
  2. inventory optimization – using statistical/finance tools to monitor and set inventory levels,
  3. transportation and logistics – lead time length and variability and
  4. supply chain planning and execution – coordinating planning throughout the chain from inbound to internal processing to outbound.

We believe that the best way of attacking this problems is to produce a simulation model that can ‘mimic’ the sales – distribution – production chain in necessary detail to study different strategies and the probabilities of stock-out and possible stock-out costs compared with the costs of doing the different products (items).

The costs of never experience a stock-out can be excessively high – the global average of retail out-of-stocks is 8.3%7 .

By basing the model on activity-based costing, it can estimate the cost and revenue elements of the product lines thus either identify and/or eliminate those products and services that are unprofitable or ineffective. The scope is to release more working capital by lowering values of inventories and streamlining the end to end value chain

To do this we have to make improved forecasts of sales and a breakdown of risk and economic values both geographically and for product groups to find out were capital should be employed coming years  (product – geography) both for M&A and organic growth investments.

A model like the one we propose needs detailed monthly data usually found in the internal accounts. This data will be used to statistically determine the relationships between the cost variables describing the different value chains. In addition will overhead from different company levels (geographical) have to be distributed both on products and on the distribution chains.

Endnote

Days Sales Outstanding (DSO) = AR/(total revenue/365)

Year-end trade receivables net of allowance for doubtful accounts, plus financial receivables, divided by one day of average revenue.

Days Inventory Outstanding (DIO) = Inventory/(total revenue/365)

Year-end inventory plus LIFO reserve divided by one day of average revenue.

Days Payables Outstanding (DPO) = AP/(total revenue/365)

Year-end trade payables divided by one day of average revenue.

Days Working Capital (DWC): (AR + inventory – AP)/(total revenue/365)

Where:
AR = Average accounts receivable
AP = Average accounts payable
Inventory = Average inventory + Work in progress

Year-end net working capital (trade receivables plus inventory, minus AP) divided by one day of average revenue. (DWC = DSO+DIO-DPO).

For the comparable industry we find an average of: DWC=56+39-23=72 days

Days of working capital (DWC) is essentially the same as the Cash Conversion Cycle (CCC) except that the CCC uses the Cost of Goods Sold (COGS) when calculating both the Days Inventory Outstanding (DIO) and the Days Payables Outstanding (DPO) whereas DWC uses sales (Total Revenue) for all calculations:

CCC= Days in period x {(Average  inventory/COGS) + (Average receivables / Revenue) – (Average payables/[COGS + Change in Inventory)]

Where:
COGS= Production Cost – Change in Inventory

Footnotes

 

Series Navigation<< Working Capital and the Balance Sheet
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  1. All data is from public records []
  2. Net working capital = Total current assets – Total current liabilities []
  3. By their Standard Industrial Classification (SIC) []
  4. Katz, M.K. (2010). Working it out: The 2010 Working Capital Scorecard. CFO Magazine, June, Retrieved from http://www.cfo.com/article.cfm/14499542
    Also see: http://www.strategy-at-risk.com/2010/10/18/working-capital-strategy-2/ []
  5. Days of working capital (DWC) is essentially the same as the Cash Conversion Cycle (CCC). Se endnote for more. []
  6. “The reverse factoring method, still rare, is similar to the factoring insofar as it involves three actors: the ordering party, the supplier and the factor. Just as basic factoring, the aim of the process is to finance the supplier’s receivables by a financier (the factor), so the supplier can cash in the money for what he sold immediately (minus an interest the factor deducts to finance the advance of money).” http://en.wikipedia.org/wiki/Reverse_factoring []
  7. Gruen, Thomas W. and Daniel Corsten (2008), A Comprehensive Guide to Retail Out-of-Stock Reduction in the Fast-Moving Consumer Goods Industry, Grocery Manufacturers of America, Washington, DC, ISBN: 978-3-905613-04-9 []

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S@R develops models for support of decision making under uncertainty. Taking advantage of recognized financial and economic theory, we customize simulation models to fit specific industries, situations and needs.

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