MCA Solutions – Bringing the Aftermarket Forward, Part II

In Part I, we re-introduced you to MCA Solutions, a Philadelphia, PA company that specializes in after market service (and service parts) optimization, and noted that they were still going strong despite some recent shake-ups in the market (and the noteable acquisition of Servigistics and Click Commerce by Marlin Equity Partners, who also acquired Emptoris not too long ago). We noted that, in addition to completing a strong SAP integration, they’ve also added a considerable amount of new functionality in the last two years around reporting, plan analysis, and reporting management.

Since we covered their new reporting and plan analysis solution in the last part, today we’re going to cover their performance management solution. Since you can’t manage what you can’t measure, and the best way to measure is often with a balanced scorecard, it’s based on scorecards, but since managers don’t like columns of numbers, it’s implemented using a dashboard, but since MCA agrees with me that traditional dashboards are inherently dangerous and dysfunctional, they realized that the only way the application would be truly useful was if it clearly identified not what was right, but what was wrong (since a goal of after-market service is exception-based management so that you only expend resources where needed). More importantly, the scorecard dashboard would only be useful if it allowed you to quickly discern what was wrong and do something about it. So what MCA built is a dashboard scorecard that not only highlights any metric that is out of bounds in red, but an interactive graphical scorecard that allows you to drill down into the metric retrieve all of the data associated with that metric in a single click.

Just like you can drill into a spend cube, you can drill into any metric on the scorecard. The first level drill will bring up all of the metrics the high level dashboard is composed of, and highlight which metrics are a problem. You can then drill into those metrics and bring up all of the associated raw data. So, if you brought up the scorecard and saw on-time delivery was only 80%, when anything under 90% is unacceptable, you could drill in and see the problem ports are LA and New Orleans and that San Diego, Washington, Vancouver, Boston, and Halifax were all meeting or exceeding their on-time delivery targets. You could drill in again and see that at these ports, most of the late deliveries were from West Coast Warblers and East Cost Easies and instantly know that either these suppliers have performance problems or that you’re not allowing them enough time in your inventory network design to transport the parts require to replenish your North American stock from your foreign suppliers. But since you can also drill into the application and the underlying model associated with any part, location, or supplier you can quickly determine if it’s a performance problem or a network design flaw. For instance, lets say you only allow 14 days for replenishment of goods in your LA warehouses from Shenzhen. Considering that sailing time is typically 12-15 days, and that it probably takes at least a day to get your goods unloaded at the port, and another for them to clear customs, get loaded onto the truck, and transported to your warehouse, there’s no way you’re going to get that part in less than 14 days by sea and it’s probably going to take at least 17 days on average, especially if these carriers are running slower ships. Then you know you need to adjust your model, and measure the supplier against a more reasonable delivery time. But if you are allowing 21 days, and your third party carrier is consistently late, then you have a supplier performance problem.

Moreover, the scorecard dashboard is completely customizeable. Each component is actually a dashboard report, and with their new flexible reporting capability, you can build any report you want. So you can design the dashboard to focus only on reporting problems. That way you can ignore the 90% of your network that is running smoothly and dive right into the 10% that isn’t running right, analyze the situation, revise the model, analyze the revision, implement an improvement, and see if the situation improves over time. If not, you can dive right in and try again. And if everything looks too good, you can define more metrics, more sanity checks, and find new problems to work on. Which is precisely what an actionable scorecard should allow you to do!

And your suppliers in China and Japan can use it too. The product is double-byte Unicode compliant and, in addition to a number of European languages, has also been translated into Mandarin and Japanese. With these recent improvements, you should be able to plug it right into your follow-the-sun operation and, once it’s configured and your data is complete, close the loop on your end-to-end after market service (parts) operation.

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