What goes into a business process? What comes out? What doesn’t? And why?

How fast does your process move inputs to outputs with desired outcomes? With undesired outcomes? What speeds it up or slows it down?

Are there outliers or one-time events that skew your understanding of “average” process performance, causing you to solve problems that don’t exist or wrongly assume everything is OK?

Having your business data packaged into KPIs and Dashboards can help you accurately diagnose a process not performing as designed and increases the probability that you can take right action to correct it. You can improve the yield and speed of a business process by looking to your data for answers and action that drives desired profitability and performance.

Application: Lead Funnel and Sales Pipeline

How many Leads result in Closed Won Opportunities, and how many do not? Why?

Some qualified Leads result in immediate Opportunities that close quickly, while others require a longer time frame to nurture. Why?

Are the Leads you’ve created YTD on track with your YTD goal because of consistent monthly performance, or was there a one-time event generating a large spike in new Leads that is not indicative of likely future performance?

If you use a CRM, you are probably already generating the data you need to understand and diagnose when your Sales process performs as designed, and when it does not. Using that data to create KPIs delivered via Dashboards, you can see where past performance is more likely to generate the outcomes you want in the future. You can target new Leads from the most productive lead sources in your Marketing efforts, so that MQLs convert to SQLs and Deals more frequently and more quickly with the same cost of sales.

Application: Customer Service Desk

Calls for help/service are either resolved or unresolved.

How many calls does it take to get to an outcome? How many days did it take from the first call to final call? Is the duration impacting customer satisfaction and potentially repeat business?

If you just look at “average” call time as a measure of call center performance, how will you know if your results being skewed by outliers, potentially masking worse performance OR causing to fix a problem that may not exist?

Where your process does not perform as designed, focus your attention on understanding root cause with data before making decisions on actions to optimize process performance. Is there 1 employee, or several, that aren’t resolving the percentage of calls you require? Is there 1 product/service, or many, that are associated with calls that go unresolved or take too long for resolution? Where actual performance does not meet required performance, don’t guess or take a shotgun approach; use data to find the points of greatest leverage for the time and money you’ll spend to optimize process performance.

Application: Project Delivery

Projects are delivered on time, early or late when compared to an original baseline schedule.

Projects are delivered on budget, under budget or over budget when compared to an original baseline budget.

How many change orders are there on projects that are delivered late or over budget?

Which resources were not available as originally planned, or did not have the skills/experience to produce deliverables by required milestones?

Which tasks were slowed by unanticipated delays, where effort was on-target but duration was not? In which situations were these one-time events, and when are they predictable and more manageable?

Good project management discipline practiced with even simple tools can create the data you need to understand why tasks aren’t delivered, resources aren’t available, budgets are insufficient or schedules overly optimistic.
Use your data to create information and insights to improve future project delivery, profitability and customer satisfaction. Create KPIs delivered by Dashboards that are leading indicators of likely future problems with impacts that can be mitigated or avoided altogether.


IMHO, a business problem that cannot be quantified is a problem that probably isn’t ready to be solved. Look at the business data you already have to identify and diagnose real process performance problems. Then decide if the potential upside to talking action is worth the investment to create a solution, and using your business data again, measure the future value created by that solution.

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