Comparative profitability of business lines. Automatic and with unexpected results

May, 2012
proto$ gen VI mod 3FFECA (Londinium)
Ruki Iz Plech
Honest analysis of various goods groups cost-effectiveness, with all the overhead costs included in the calculation, is an arduous task, something next to impossible. On the other hand, without such an analysis, the manager’s idea of what the company gains from and what it loses on will have little to do with reality: they have to use intuition, guess, interpret their dreams, and poll corporate experts like Joe Schmoe. dia$par provides you with such an analysis in a matter of seconds in one click.

Some time ago we have already considered a theoretic example of rake trade?. Let’s rest on rakes in our reasoning once again. You see, rakes — they don’t care.


Imagine a rake megamarket. The variety of rakes is quite high, ranging from small children’s three-tooth toy rakes to massive harrows pulled by tractors.

All these items are intended for raking. The difference between them is price, mark-up (and gross profit margin), weight and size (as well as cost of handling), competitive environment, target audience, and many other things for sure.

Our task is to identify those positions (or groups) that make money for the megamarket and those that don’t (including all connected costs). After that the megamarket plans to take corrective action – make changes in markups and in the assortment matrix.

The task is a bit more complicated than it appears at first. We can quickly calculate gross margin and gross profit via a sales report. But what we really need is basically NET profit by assortment groups. Then how do we post costs? Sales personnel salaries? Accountants salaries? Rent? Taxes? Utility services?

The traditional solution is simple, fast and (exactly as the saying goes) wrong: posting all costs proportionately with the sales volumes of the assortment groups.

This solution has a number of drawbacks. Let’s have a look at the most telling one. Suppose, there’s a group of unmarketable ?positions. We’ll try to be modern and call them titanium nano-rakes. They were purchased in huge numbers at one time and take up half of warehouse space (there’s literally no room left for decent merchandise), however their sales are non-existent. They just don’t sell — a perfectly unmarketable position.

When trying to calculate net profit by assortment groups in accordance with the traditional approach, we’ll come up with the zero costs on the titanium nano-rakes group since they have a zero share in total sales. While in the reality they take up warehouse space (which is paid for), stockkeepers" labor, tied-up working capital. And the total amount of nanorakes costs is transferred on other groups that actually sell and generate profits.

The value of the report on relative profit efficiency of various product lines, produced via such approach, is perfectly clear.

Conceptually, it is clear, that every type of costs should be posted in its own way. E.g. rent — based on the warehouse space taken up by product groups (in monthly averages), stockkeepers" wages — based on the volume of operations with account for weight and size parameters, sales personnel salaries — based on gross margin, etc. But this would mean such a gigantic work load that in reality these kinds of solutions are almost never put to practice.

This is, however, a true-life task: similar problems with understanding relative profit efficiency of product lines caused major manageability difficulties in Samsung in the 1990’s (they might not be completely overcome up to these days). Its chaebol brother Daewoo went down the tubes altogether. In fact, when your company manufactures an impossible number of different products from LED displays for watches and memory modules to military ships and supertankers, it would be good to know, what really makes you money and how much.

If it does.

In the Western tradition, similar problems are solved through establishing a holding structure, where subsidiaries are assigned completely different businesses altogether. General Electric would be a prime example: it manufactures an unrealistic number of different products, ranging from five dollar phones to nuclear power plants to turbojet engines. It also incorporates a banking subsidiary. Such approach, however, on one hand, doesn’t solve the problem completely (every company within the GE group still manufactures a wide variety of products), and on the other hand, due to its costliness, this approach is viable only for gigantic companies.

So what do other smaller companies do?

First, migrate into dia$par.

Let’s have a look at the example of Ruki Iz Plech(which is translated as "handy"), a leading company on the Russian electronics post-warranty maintenance market.

Various types of maintenance works (such as laptop repairs, video electronics repairs, repairs of Apple electronics, computer emergencies, IT outsourcing in the form of subscription services) is the Ruki equivalent of assortment groups as in the example with trading and manufacturing companies. These are all very different lines of business with different competitive markets, target audiences and profit generation technologies.

Having said so, the main channel of lead generation in Ruki is contextual advertising in Yandex.Direct and Google.AdWords (Ruki has one of the largest budgets for this particular advertising channel in Russia). Payments are made per clicks on ads that are linked to the advertiser’s website, and the cost of such clicks constantly changes online through an ongoing auction.

The competition is fierce and ads are very expensive (the cost per click may be as high as dozens of dollars and more). So in order to keep the profitability of every line of business within the company (and the company as a whole) at a reasonable level, at any given time you need to know the current profit level and the quantity of currently available orders, so that you could step down on the throttle or lift off it a bit (i.e., bid higher prices for the leads, or, on the contrary, bid lower and settle for a reduction of the incoming flow of leads).

Before migrating to dia$par, it all had been a fiction. Not a science one.

Exact amounts of the company’s costs were not available before the middle of the month following the accounting month. The only time they tried to objectively post costs based on lines of business bumped up against the fact that they needed to manually process about 500 (!) Excel files. That was the end of it, as you might have guessed.

The Advertising Campaign Efficiency Report Proper

Now the Ruki personnel receive the full picture on cost/revenue ratio for every company’s business-line with a single touch. Everything is posted automatically (the Google and Yandex statistics are also imported and processed in the background mode).

The effect is cumulative.

E.g. savings on the advertising budget (without decreasing the inflow of leads) were 34%. In case of Ruki it is the second highest cost item in the profit and loss statement.

Imagine how this would work in your business, my fair readers.

"How did they do it?"(They — meaning the dia$par).
The notion of business-lines was integrated into the core at the design stage and is now an organic part of data model. All postings can be located according to business-lines both in automatic mode (by default, but still rather intelligently) and along with business rules set at the transit stage.
For each particular installation the administrator may build the list of
business-lines in two ways:
- by item groups (that’s what we discussed in this case)
- by counterparty groups. A lot less common are the situations, where business-lines are defined by customer mix stratification. E.g. wholesale — retail – corporate. Or red-headed — retired — left-handed.
NB. The task of providing high quality posting of costs and revenues by geographically detached business units (commonly known as "branches") is disregarded here in view of its triviality.

Dream bigger, my fair readers.

Being inside dia$par. Some stories
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