T’is time to go for a boutique? I’d like to draw your attention to this list of articles by Steve Banker of Arc Advisory Group:

Top SCM Boutique Consulting Firms: Part 1, The Logistics Boutiques

Leading SCM Boutiques – Part 2, Supply Chain Planning Vendors

10 Coolest SCM Boutique Consultants

Most of the firms listed in the lists above span from small consultancies to behemoths who make the industry and in some cases is the industry. So what is it that these small fish are thinking when they play in the playground of the behemoths? By the way, why are there small fish anyways? Are the big fish listening?

Tags: The SCM boutiques, SCM players, Consultants – big and small, Arc Advisory, Steve Banker

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Running down the path of metrics, I came across this take on the use of metrics in the business world. This article by Julie Fraser titled – Are metrics driving or killing your business? can be found at Manufacturing Business Technology.

The question is whether the behavior that most companies are rewarding actually helps performance, or hurts it.

Ms. Fraser’s line is not really what the right metrics are but whether the measured metrics actually help performance or hurt it. In other words, does it work or not?
Here’s the standard example given (and why am I not surprised that manufacturing gets the short end of the stick?)

Many talk about fact-based management, but outdated manufacturing metrics often conflict with corporate goals. For example, a plant that measures equipment utilization as the top indicator of success may in fact lead the company to carry excess inventory. In another scenario, minimizing overtime might hurt on-time shipments to customers and thus, overall revenues.

But both of these metrics are not manufacturing metrics but confusions arising from accounting. It is true that manufacturing measures equipment utilization is measured in addition to cycle times, changeover times and mean time to failure. However, utilization is measured for accounting reasons not because a manufacturing/plant manager is going to feel extremely accomplished because his/her machine was utilized 95% of the time. The concept of unit cost arises in accounting and not in manufacturing and everything else follows from that.
While Ms. Fraser indicates that measuring equipment utilization “may” in fact lead the company to carry excess inventory but that is not only because manufacturing managers are measured using the notion of efficiency but because unit costs are minimized in large batch production. Costs in production as it is/was measured is a fuzzy concept because it is not related to actual demand and the actual price paid by the customer but a weighted factor of allocation of overheads, raw material costs etc. In order to minimize unit costs using the accounting dimensions, utilization is a key lever and it has been pulled many a time.
But what can one make of the following set of metrics led dead-ends?

At the same time, finance and accounting often doom their own manufacturing operations by focusing on metrics that punish plants for doing a good job. Too large a focus on return-on-assets might argue for outsourcing when the local plant is doing a better job than a partner could.

Mind you, the above is without taking into account longer lead times arising from outsourcing, the larger inventories you need to hold in order to cover the longer lead times, supply risks etc. Then, there are issues about quality as well.

Even more pernicious are facility-level accounting metrics that punish innovations such as postponement, the migration to make-to-order, designing specialized products for various channels, or investing in important technology upgrades. Common metrics that thwart progress include expectations that overall manufacturing expense or raw materials and MRO inventory will invariably go down year-over-year. Or that productivity will rise even as the plant is making more complex products, or the warehouse is performing value-add manufacturing as well as materials movement activities.

So what are we to make of this? Is it really then an accounting problem at the root of it all? The language of the firm is dollars. If I were to put on my optimization hat, then the objective function of the firm is to maximize profits (though this same objective can be restated as minimizing costs in the abstract world of optimization but not as easily in the real world). If Profits are stated merely as Sales minus Costs, the firm’s ability to define and/or control Sales is relatively lesser than the firm’s ability to define and/or control Costs. The latter is difficult to do and that is where a substantial disconnect exists between the financial and operational side of the firm. In fact, I would argue that the definition of cost as it is expressed in accounting is a definition in a vacuum. At this juncture, I think it might be prescient to highlight the following post concerning the calculation of cost. Does it makes sense?
This disconnect is highlighted by Ms. Fraser as well,

Disconnects between financial and operational metrics abound. All of these metrics may seem perfectly logical from one pocket of the organization, but not when taken in context.

It is not merely that financial and operational metrics are disconnected but that financial notions of cost assume a primacy in the functions of the firm simply because dollars are the language of the firm. If a manufacturing manager were to say that mean time to failure was increased by 5% for the milling area – what the heck does that translate into in terms of dollars and cents, in terms of the Profit objective above? The disconnect exists not between the financial and operational areas but in the languages of the financial and operational areas and the language of the firm. Nowhere in the above discussion am I trying to say that manufacturing managers or analysts have not done their part to translate the difference between 95% and 98% customer service levels into dollar values. Is it even possible to do that?
However, what I am saying is that simply because the financial side of the firm is closer to the language of the firm, driving the firm from the financial to the operational is simply the wrong thing to do. In my opinion, and taking the control systems analogy, a portion of the financial side is on the feedback loop of the firm when it pertains to operations and the firm in general. As it is currently expressed, what is on the feedback loop for operations are a set of operational metrics that are disconnected from the financial aspects of the firm. Hence, the firm is pretty much operating as an open loop system in the broader picture even though the operational subsystem (and other subsystems as well) is running a closed loop system.
In such a state of affairs, can one even choose a set of metrics that will enhance the performance of the firm? If you have chosen a set of metrics and it works, is it just a coincidence? Or has the choice tapped into an implicit layer of the firm which for the time being works in some sort of desired fashion?

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Tags: Metrics of the firm, Manufacturing Business Technology, Financial Metrics, Operational Metrics, Cost calculation

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I have spent the last few days thinking further about metrics (supply chain metrics, financial metrics and all sorts of other metrics) but I haven’t hit upon a foundational idea (or a set of ideas) to order all my thoughts. So the rummaging continues and I took some of that rummaging online:

A thought process when thinking about metrics (any sort of metric) is to ask, how the other metrics in the firm look like. An example of that would be stumbling upon such as this observation by Brad Feld,

Several years ago, some of y’all may remember an event called “the bursting of the Internet bubble.” Immediately preceeding this event, companies (and investors) focused on growth at any cost. This growth took various forms ranging from the one key financial metric that everyone cared about at the time (revenue) to non-financial metrics such as eyeballs, click-throughs, and affiliates. Shortly after the bubble burst, people started focusing on net income, cash flow, cash on hand, and other financial metrics. Not surprisingly, these were things that most rational business owners had paid attention to since – oh – the beginning of time.

Brad is talking about metrics in an industry that for a short period of time saw tremendous growth – the one financial metric used was revenue along with a host of other metrics such as eyeballs, click-throughs and perhaps even today – page views.
As Brad notes further down in his blog, the staple of financial metrics as used internally within a firm would be more along the lines of,

Monthly data we collect (and consolidated so everyone in the firm sees it on a weekly basis) includes revenue, cost of goods, operating expense, EBITDA, headcount, cash burn, cash on hand, debt, projected insolvency date, additional cash required to breakeven, and projected first quarter of profitabiity.

Another interesting take on operational metrics is the following that comes from the profession of lawyers (i.e. a service/consulting type of environment):

The Law Practice Business Model was introduced in 1984 by David Maister as a mathematical expression. Maister’s formula is as follows:
NIPP = (1+L) * (BR) * (U) * (R) * (M) where,
NIPP = Average partner income
L = Leverage (ratio of associates to partners)
BR = the “blended” hourly billing rate
U = Utilization (client hours recorded)
R = Realization (revenues divided by “standard value” of time recorded)
M = Margin (partner’s profit divided by revenues)

M. Thomas Collins notes further that

Maister’s model doesn’t tell the whole story. The financial manager has to be just as concerned about metrics that measure unbilled fees (work-in-process) and billed but uncollected fees (receivables). The managing partner has to be concerned about metrics that are not reflected in the financial numbers but will impact those numbers in the future. For example, are we opening new matters faster than we are closing old ones? Are the partners meeting their individual marketing goals? Is client satisfaction on track or veering off-course? While the Maister model is not the whole story, it is at the heart of the story.

The above mathematic expression is really a current snapshot and I assume that such a snapshot is taken at the end of some period such as a month or quarter. In fact, it can be characterized as a trailing metric (the stock market analogy would be ) and as such is not forward looking because it doesn’t take into account an unfolding reality.

Other viewpoints to consider would be the kind typified in this summarized version of the Balanced Scorecard,

The financial perspective addresses the question of how shareholders view the firm and which financial goals are desired from the shareholder’s perspective. The specific goals depend on the company’s stage in the business life cycle.
For example:
* Growth stage – goal is growth, such as revenue growth rate
* Sustain stage – goal is profitability, such ROE, ROCE, and EVA
* Harvest stage – goal is cash flow and reduction in capital requirements

Here, one of the articulated requirements to develop a clear idea of what sort of financial metric to use is the company’s maturity within the business life cycle. However, some firms have different divisions/areas/product or service groups in different stages of the business life cycle or product life cycle. Should a defined set of financial metrics be used uniformly across different divisions/areas/product or service groups?

The last insight that I came across is to see how metrics (even financial metrics) are applied within Project management and Project selection and decision making,

What kinds of metrics reflect impacts on value? Many organizations have trouble answering this question. Organizations tend to measure what is easy to measure, not necessarily what is important. Most organizations use a bottom-up approach. They define interesting metrics, but then can’t come up with the algorithms for computing value based on those metrics. Unless there is a way to combine the metrics to determine the value added by projects, the metrics will not be of much help in identifying value-maximizing project portfolios. How can you determine the value added by projects?

Here the notion of value is a general notion such as shareholder value, stakeholder value, or mission value. The recommended method here is to develop the value model using,

techniques based on multi-attribute utility analysis, influence diagramming, and causal modeling

Further,

The value model establishes an explicit connection between the characteristics of the business that may be impacted by proposed projects and the value ultimately derived.

Now, I am not so concerned about the value of proposed or future projects as much as the value inherent in current operations within a supply chain or some other similar operation. There is a certain similarity between the value of proposed projects in the pipeline that one experiences in a project management role and the scheduling or allocation decisions that have to be made in a supply chain or manufacturing environment.
The other related insight that is in the same train of thoughts deals with Metrics as “Observables” and the Clairvoyant Test,

To the extent possible, metrics should be observables; that is, characteristics of projects or project outcomes that can be observed and measured in the real world. Since estimating project value requires forecasting the future, metrics don’t, obviously, all have to be things we can observe today. Metrics can, for example, include a projected future state of some observable, for example, an improvement in a reliability-of-service statistic important to customer satisfaction.
A useful device for checking whether a metric is observable is the so-called “clairvoyant test” devised by my college mentor, Professor Ron Howard. Before accepting what appears to be a good metric, consider whether a clairvoyant could give an unequivocal value for that metric given that a project decision is made in a specific way. Oftentimes, the clairvoyant test points out inexactness of what initially appears to be a well-defined metric. For example, “customer satisfaction” doesn’t pass the clairvoyant test. However, “percent reduction in recorded customer complaints” and “company ranking in the next industry customer satisfaction survey” are metrics that do pass the test.

The rummaging continues…

Tags: Metrics, Metrics used in Law firms, Brad Feld, David Maister, Calculating Average Partner Income, Balanced Scorecard, Max Wideman, Metrics as Observables, Clairvoyant Test

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SCDigest reports on strong rumors about merger talks between IBM and SAP.

These are just rumors, to be sure, and have been circulating at some level for almost a year.
SAP has strongly denied the rumors during that time, though chairman Hasso Plattner unintentionally put some fuel in the fire last May by saying to the German Financial Times last year that: “There are only three potential buyers [of SAP]: IBM, Microsoft and Google. Of all companies, I don’t see anyone else. If shareholders think that a combination, and not independence, is better, then it will happen.”

From the services model that IBM follows, it makes sense to acquire a behemoth like SAP purely for its installed base and then sell all sorts of services to them. But the larger question is – what’s the room for growth here? From a software sales point of view, the market is pretty much saturated. My own view of the ERP behemoth is that given the utter complexity of something of the order of SAP/Oracle and the implicit insistence that the firm adapt to SAP’s version of reality – there is quite an opportunity for an intelligent class of enterprise software to make deep inroads.
Whatever the big honchos at IBM are thinking, I’m skeptical of such a merger simply because of revenues from any sort of installed base growth. The market space where there is some growth potential seems to be:

IBM and SAP have an existing partnership to bring ERP to the small and mid-sized company market. Penetrating these smaller companies has been a key marketing goal of SAP for the past few years.

The question is – why pick an elephant (or a sheared down version of an elephant) to run what needs to be, strategically and execution-wise, a nimble organization? Any new entrant in the enterprise software space needs to enter via the small and mid-sized company market because that’s where the behemoths are concentrating their efforts.
Old Chinese (Confucius) saying: “Do not use a cannon to kill a mosquito.”
This makes for an exciting few years ahead.

Tags: ERP, Rumors of merger between IBM and SAP, IBM, SAP, SCDigest

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SeekingAlpha reports about the results that SAP AG reported today – SAP Warns, Sending Shockwaves Through Enterprise Software.
Eric Savitz of Barron’s reports,

Bad news for the enterprise software sector this afternoon, as SAP (SAP) just warned that fourth quarter software revenue growth came in short of previous guidance. This is a bit confusing, so bear with me. SAP reports product revenues, software revenues, and total revenues, and it reports on both an actual and constant-currency basis. But the bottom line is that software sales came up short for both the quarter and the full year.

The SAP stock (SAP) is off more than 10% as I write and Oracle (ORCL) is also taking a late afternoon dive.

Tags: SAP warns, Enterprise software sales

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