Inventory Performance 2017 Part 2

I am going to let one big graphic do most of the talking this week.

Relative to inventory management that is. I am back again this week with more analysis of inventory performance , after last week's first introductory column (see Inventory Performance 2017).

In that column, I noted that overall inventory performance is gauged by two main measures: Days Inventory Outstanding (DIO) and in logistics circles the more common inventory "turns."

 Reviewing  briefly:

DIO = End of Year Inventory Level/[Total Cost of Goods Sold/365]

So, you calculate the average cost of goods sold for one day, and then see how many of those COGS days you keep in inventory (based on year-end balance sheet numbers).

As such, DIO is sort of the reverse of inventory turns, in that a higher DIO, all things being equal, means poorer inventory management performance, while a lower number signals improvement. You are being more efficient with inventory versus a given level of COGS.

Inventory turns is measured as follows:

Cost of Goods Solid/End of Year Inventory

SCDigest went through the rather tedious effort - even with some tools we built to help us - of gathering turns information for 554 companies, and then grouping those companies into more than 60 sectors. As I explain each year, there are some sectors where this is easy (e.g., department stores) and others where it is more difficult (e.g., machinery).

Nevertheless, below is a chart with data on almost 70 sectors, listed in order of their inventory turns in 2016. Also shown is the sector turns in 2013, from which we calculate the change (positive percentages being a good thing) over that period.

In the last column, we also provide the resulting DIO, which is calculated by dividing 365 by inventory turns. We also indicate how many companies were included in each sector and example companies:

A couple of notes. You will find a few "special cases," where for example we didn't include Apple with "computer hardware and peripherals" because Apple's turns, for reasons that aren't immediately clear, were so dramatically higher than everyone else it would have greatly distorted the average. Ditto with restaurant chain Cracker Barrel, which had turns far lower than the industry average, I assume due to all that merchandise it carries beyond food.

I will also note we are dependent on the financial data supplied by sources such as Yahoo or Google finance, and sometimes there are some anomalies. In some cases, data is missing. And we found Yahoo and Google have somewhat different numbers for cost of goods sold for Procter & Gamble's most recent fiscal year, as an example. Who knows.

But I hope with all that that you find this data interesting. The bottom line, as we reported last week, is that inventory turns are in general flat if not down somewhat in recent years, despite lots of attention and much technology thrown at the problem.

Why is that? I would be interested in your observations.

Anyway, take a look. We will do still more analysis of this data in OnTarget next week.

Any reaction to this inventory data? Why have inventories been creeping up on the past 5 years?  What explains differences in turns between similar companies in a sector? Let us know your thoughts at the Feedback button below.