Inventory Performance 2015 Part 2

I am going to let the pictures do most of the talking this week.

Relative to inventory management that is. I am back again this week with more analysis of the working capital data compiled each year by REL, a Hackett Group company.

To repeat from last time, our biggest value-add in this process is taking the data REL makes available to SCDigest to recategorize the companies into more narrow sectors, to make comparisons better.  So for example, we take the three retail categories in the REL data and create more than a dozen in total, grouping retailers into more specific categories.

While that does improve the accuracy, if you will, with ever growing consolidation in every industry, it also really limits the number of firms in many categories . For example, we were down to two office products retailers for this year's data,  based on 2014 results, after Office Depot acquired OfficeMax. That will be down to one company next year, after Staples takes over Office Depot.

The good news on the REL data is that this year, they provide info that can be used to calculate inventory turns. That wasn't possible when the key metric they use for inventory - Days Inventory Outstanding or DIO - was calculated using revenue in the equation:

DIO =End of Year Inventory Level/[total revenue/365]

This year, it was also calculated using Cost of Goods sold, or COGS. This REL said was to limit the effect that widely different gross margins across industries/companies had on DIO levels - a point SCDigest readers have made for years after our analysis of the REl numbers.

But using this formula:

DIO =End of Year Inventory Level/[COGS/365]

you take out the impact of margins - and instead calculate how many days worth of COGS a company has in inventory. That the allows SCDigest to calculate inventory turns using this simple formula:

Turns = 1/(DIO/365)

Below is a massive chart of the 60+ sectors we created, sorted by highest to lowest inventory turns in fiscal year 2014 from most to least on average in each sector. It also shows 2013 turns, the percent change from 2013 to 2014 in the sector, how many companies were in each sector, and just for jollies 2014 DIO to compare to turns.

Turns range from over 70 in the restaurant sector to a paltry 1.3 in the spirits industry, as can be seen:

Source: SCDigest based on Data from REL

We also created another chart that shows this data plus the companies with the highest and the lowest turns in 2014 in each sector - you will find that table here: 2014 Turns by Sector with Companies with Highest and Lowest Turns

Some sectors are more homogenous than others. Consumer packaged goods, food manufacturers, and department stores, for example, have very comparable companies. But despite our best effort, some categories are more varied, such as the machinery category. It includes companies ranging from Lincoln Electric (welders) to Timken (bearings) to truck engines (Cummins).

Still, it is interesting to consider much of this data. Why can't consumer packaged good companies, for example, muster up better than 5.9 turns per year, a number that hasn't really changed for years?

Toy maker Hasbro had slightly better turns than rival Mattel (6.0 versus 5.4), but if Mattel had equaled Hasbro's level, it would have generated an extra $58 milllion in cash flow in 2014.

In the detail on food manufacturers. why does JM Smucker have just 3.8 turns per year, while Kraft Foods had 7.5?

Anyways, take a look. We will do a final bit more analysis on this data in OnTarget next week.

Any reaction or other analysis to this inventory data? Let us know your thoughts at the Feedback button below.

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