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Metrics in the firm – Inside and Outside

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…

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Category: ERP, Personal Observations, Supply Chain Management

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