Shafqat Azim, Executive Vice President
If you weigh yourself every morning, you’ll lose weight, right?
An absurd expectation, of course. But it is interesting how often organizations experience a piercing sense of disappointment when a sophisticated performance measurement system, deployed with great fanfare, effort, and cost, fails to deliver a significant boost in performance.
What could be more important in today’s high-pressure economic environment than measuring the performance of your sourcing arrangements? Whole businesses ride on that performance, to say nothing of your bonus and those of your colleagues and their next several assignments.
Performance measurement is intrinsically critical to any sourcing initiative. It lies at the heart of virtually any hoped for improvement in systems, individuals, and organizations. Yet performance measurement systems regularly disappoint. They fail to provide the appropriate level of decision support to key stakeholders. They don’t deliver the comfort that they are making the right decisions at the right time for the right business reasons.
We believe organizations can extract the full value of their performance measurement initiatives if they embrace three guiding principles.
Principle 1 – First know whom, and what decisions, the measurements will influence.
You know the old saying, “You can only manage what you measure.” That’s true as far as it goes but measuring isn’t managing. Measuring is still, well, measuring. Measurements don’t matter until they end up in the hands of the person or people who will, based on what the measures say or don’t say, make a set of decisions to improve performance. Too often, those who create the measures are unaware of what the decision-makers want to know and need to know.
The sourcing world is rife with disconnects of this nature. We were once brought in by a COO who asked us to determine the wisdom of outsourcing his company’s entire back office processing entity. We analyzed its data carefully, looking for the potential savings and improvements. To our mild surprise, we had to conclude that not only was the savings potential low, but his operation was one of the more efficient we had ever studied. We reported that back to the COO. He sent us back to dig a little deeper, make the data more granular.
This happened several times. Each time we came back with more data that validated our conclusion that little could be saved by outsourcing this function. Finally we got the chance to present our information to the CEO. We affirmed our conclusion once again – no savings here to justify outsourcing.
There we learned what we needed to know all along. The CEO wasn’t interested in the relative efficiency of the operation. He believed back office processing to be extraneous to the core business of company. He wanted to outsource it regardless. Our many forays to keep finding more data that improved our measures were irrelevant to the needs of the decision-maker. He outsourced his operations.
Builders of performance management systems need to find a different starting place. Not, what shall we measure, nor even what shall we manage? But what is our objective in measuring in the first place? Who will make decisions based on the data we assemble. What drives that decision-maker? What are his or her objectives for the business we are measuring?
When you know what set of decisions will come out of the measurements, the measurements tend to fall into place. And one extra bonus, they tend to be fewer! When you’re not sure why you’re measuring, you have to collect a lot more data to cover the uncertainties.
Principle 2 – Your data is good enough. Really, it is.
A few years ago I helped some clients arrive at an important sourcing decision based on data that was admittedly somewhat murky. They reached a tentative decision based on it, but sent us back several times on data-cleansing missions, trying to eliminate any inconsistencies and fill in any gaps. We were at it for weeks while the rest of the organization waited for their decision. Finally we asked them, “Let’s say we get the data immaculate – no one could possibly question it. How could that change your decision?” It wouldn’t, they admitted. They were just uncomfortable with the decision they had to make, so they delayed the inevitable by pressing us to make the data to be unassailable.
The corollary to principle 2 is this: Your data will always be murky. No decision important enough for executives to make will ever be buttressed with the perfect data we all dream of. If it were perfect the proverbial monkeys could be managers. There will always be a flaw of some sort, and it will always come up short for the context of the decision being made. This report doesn’t account for last year’s acquisition. That report came from two different systems, manually integrated. They calculate things differently in the UK office. That group allocates costs based on head counts, not volumes.
Organizations are dynamic, mobile, and – hopefully -- growing. Things change and when they do they create data anomalies. Only in the most moribund environment where nothing is supposed to change or improve would a decision-maker hope to find data free of all anomalies.
That’s where executive talent comes in. Performance measurement works brilliantly when executives make themselves comfortable with the best available information, make the decisions it points to, and then move on to the next decision. They have a business to run, not a data set to perfect.
Principle 3 – Efficacy has three dimensions, and the third is first among equals.
Like the drunk who loses his keys in a dark alley but goes looking for them under the streetlight “because it’s easier to see there,” many measurements don’t look in the right places.
They measure efficiency – the cost and speed of getting a job done. They measure effectiveness – is the job getting the right thing done right? Both are calculable. Data can be fairly easily collected on both counts, easily compared, and easily reported.
But jobs don’t exist to be fast or to be right. They exist because the organization needs to see the value that the job was invented to deliver.
But how many performance measurement systems calculate and report value? Back to our earlier example of the CEO who questioned whether back office processing was core to his business: The COO kept sending us back for more and better data on efficiency and effectiveness. The CEO kept thinking value. There was never a hope that his COO’s performance measurements could tell him what he really wanted to know—what is the value of back office processing to our company?
The question the CEO needed to pose to the COO, and he to us, was this: Would the same effort expended elsewhere bring better value to our company than the effort expended on the back office? Sometimes value might be a financial measure, sometimes it might have more to do with establishing market dominance, or it might be a measure of competitiveness. All organizations focus on efficiency. Increasingly, mature organizations measure effectiveness. But very few make the connection to value.
In the end, performance measurement is more an art than a science. The more you adhere to the three guiding principles for measurement system design, the better you will be able to contribute to your organization’s decision-making process.
Shafqat Azim is Executive Vice President of Collabera, Inc. He can be reached at firstname.lastname@example.org.