If senior management teams were omnipotent then all decisions would be perfect, market share would increase, sales would spike, profitability would skyrocket and employee morale would be unparalleled. Unfortunately, the reality is that even the most sophisticated company rarely knows its financial position until the end of the month. Even then the metrics that determine competitiveness are obscured by financial discussions regarding budget, the annual business plan and a plethora of system issues. The true competitive driving force is obscured by financial double speak. Senior leaders may smile and accept what “is” but nothing takes the places of what is “needed.”
After a few monthly reviews and more than a few requests, I decided to publish my first set of key business indicators as “needed” by the senior management team of a Fortune 100 beverage company. The first round did not meet the team’s approval and I was sent back to the drawing board more times than I care to remember.
My first attempt was focused on retroactive indicators, using financial data driven by the monthly results to create the key indicators. I scrapped that idea, however, since I knew there were manual entries, assumptions and systematic gyrations included in the results.
My second attempt was a little more unorthodox. I proposed using proactive indicators, such as shipped cost per mile, pallet cost, unit handling, routing guide performance, etc. data that was extracted directly from our enterprise software system. The metric of cost per mile is a data indicator that compares the average cost per mile shipped versus a historical actual cost or annual business plan. If the actual cost per mile increased it may be due to higher fuel costs, shipping closer distances, to different locations or selecting a more expensive carrier – all of which need to be fully investigated and explained. A higher cost per mile would mean that the actual spend would be higher than the amount accounted for in the annual business plan and would require either a downhill cost offset or, worse yet, approval from senior management to increase the yearly transportation forecast.
The data from the enterprise system is updated in real time, creating true proactive measures. But I cautioned the management team that although these measures were directionally correct, they may change each week or even daily. I also advised that enterprise data in its purest form might have keypunch errors or missing information that may skew the key performance indicator (KPI) results.
Management decided to move forward with the enterprise data. After the initial successful roll out of the proactive indicators, my heart fluttered in anticipation of the praise for completing the project. I anxiously awaited the “atta boys” about to come my way. But that exuberance had to wait. The question that I feared the most came: “How can we tie the proactive/directional results with the financial results?”
The quick answer was, “It won’t match.” Now, that was not exactly true, nor was that the answer the management team wanted, so I acquiesced and created the reconciliation. The exercise was comparing line-by-line data of an enterprise system with missing values and voided transactions with that of SAP, our financial reporting package. If it were a simple direct flow of data it would have been easy, but given accruals, assumptions, journal entries and the accounting adjustments necessary to have accurate monthly results, the reconciliation quickly turned into a monstrosity.
After a week, I completed my reconciliation with a special accounting catchall category called “accounting adjustments.” After explaining all of the elements that go into a financial month close, the senior management team reluctantly agreed that the proactive reporting was far more valuable than a schedule tying the two results together. Success!
But my success was limited. I found that although the KPIs were helpful in the decision-making process, it took undue time for the senior managers to review each metric. To help them, I color-coded each metric result as follows:
The following figure is an example of the shipped cost per mile KPI report that I prepare on a monthly basis.
After a few monthly reviews and more than a few requests, I decided to publish my first set of key business indicators as “needed” by the senior management team of a Fortune 100 beverage company. The first round did not meet the team’s approval and I was sent back to the drawing board more times than I care to remember.
My first attempt was focused on retroactive indicators, using financial data driven by the monthly results to create the key indicators. I scrapped that idea, however, since I knew there were manual entries, assumptions and systematic gyrations included in the results.
My second attempt was a little more unorthodox. I proposed using proactive indicators, such as shipped cost per mile, pallet cost, unit handling, routing guide performance, etc. data that was extracted directly from our enterprise software system. The metric of cost per mile is a data indicator that compares the average cost per mile shipped versus a historical actual cost or annual business plan. If the actual cost per mile increased it may be due to higher fuel costs, shipping closer distances, to different locations or selecting a more expensive carrier – all of which need to be fully investigated and explained. A higher cost per mile would mean that the actual spend would be higher than the amount accounted for in the annual business plan and would require either a downhill cost offset or, worse yet, approval from senior management to increase the yearly transportation forecast.
The data from the enterprise system is updated in real time, creating true proactive measures. But I cautioned the management team that although these measures were directionally correct, they may change each week or even daily. I also advised that enterprise data in its purest form might have keypunch errors or missing information that may skew the key performance indicator (KPI) results.
Management decided to move forward with the enterprise data. After the initial successful roll out of the proactive indicators, my heart fluttered in anticipation of the praise for completing the project. I anxiously awaited the “atta boys” about to come my way. But that exuberance had to wait. The question that I feared the most came: “How can we tie the proactive/directional results with the financial results?”
The quick answer was, “It won’t match.” Now, that was not exactly true, nor was that the answer the management team wanted, so I acquiesced and created the reconciliation. The exercise was comparing line-by-line data of an enterprise system with missing values and voided transactions with that of SAP, our financial reporting package. If it were a simple direct flow of data it would have been easy, but given accruals, assumptions, journal entries and the accounting adjustments necessary to have accurate monthly results, the reconciliation quickly turned into a monstrosity.
After a week, I completed my reconciliation with a special accounting catchall category called “accounting adjustments.” After explaining all of the elements that go into a financial month close, the senior management team reluctantly agreed that the proactive reporting was far more valuable than a schedule tying the two results together. Success!
But my success was limited. I found that although the KPIs were helpful in the decision-making process, it took undue time for the senior managers to review each metric. To help them, I color-coded each metric result as follows:
- Red: Corrective action required and follow up is necessary
- Yellow: Corrective action is not required but follow up is necessary
- Green: No corrective action necessary
The following figure is an example of the shipped cost per mile KPI report that I prepare on a monthly basis.
Example: Shipped Cost Per Mile KPI Report
Usually the green items were either quickly reviewed or entirely ignored; the items in red and yellow were discussed more thoroughly. Unsurprisingly, I found that a chart has more meaning than just a numeric indicator. A simple visualization leads the eye to potential issues and away from successful projects.
In my efforts to add more value to these KPIs, I established a goal for each indicator. The goal-setting process should be driven by operations in conjunction with company leaders as the leaders are ultimately responsible for the success of the business. And without goals, it is impossible to determine a business or functions success or failure.
Adding text to accompany the charts adds context or a functional perspective to the indicators. For example, if an analyst identifies an upward spending trend in transportation, the analyst should be able to identify the cost driver, quantify the incremental cost and, if possible, offer a potential solution. These explanations not only help explain potential deviations but also assist in finding opportunities to offset potential losses.
By applying these methods, the number of key performance indicators has grown steadily over the last year – encompassing transportation, warehousing, supply and demand planning, marketing, and sales. Each of these metrics helps drive a first-in-class company, defined by an environment of hands-on management and responsive problem solving.
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