We all collect lots of data.  We all have financial and operational data and many of us also conduct satisfaction and loyalty surveys.

We tend to look at each data set as a separate entry or maybe as part of a close set like satisfaction and loyalty.  Interesting, but the real value of our data is extracted when we look at it in conjunction with other data that, when combined, tell a great story.

Financial Data

In addition to an overall P&L or an Income Statement, we also have very detailed data about each customer, each installation, each serial numbered item, and each product by model number.  Looking at any one specific type of information will show us areas to improve.  

For example, look at year-over-year warranty costs by model number.  Is initial quality improving?  Are repair costs decreasing?  Does user “context” shed light on high cost installation types like cement plants for analytical equipment or heavy construction equipment for communications gear?

Operational Data

If your responsibility includes the call center, then you have information about call wait times, hold times before a call is abandoned, talk time, number of handoffs (if applicable), and number of calls for the same ticket number.  Each metric tells a story.  And you can combine data to really gain insight.

For example, look at abandoned calls and hold time.  Do your customers run out of patience in two minutes, ten minutes or never? How does hold time vary with the number of previous calls on the same ticket?  Are customers more patient on the first call and ready to reach through the phone and strangle someone by the third?

Customer satisfaction and loyalty data

You are probably conducting CSAT and Loyalty surveys.  From the surveys, you look at how satisfied customers are with different aspects of your organization and try for steady improvement.  You may even be looking at results by level of respondent or importance of the customer to your overall business.  

Also, you may be doing correlations to see if you can determine the drivers of loyalty or overall satisfaction.  And you may be identifying at-risk customers based on their survey results.  But the first time you showed at-risk data to your CEO or MD, she probably asked “How much annual business do we get from each member of this at-risk group and what can we do to turn them around?“ Obvious question, right?

Combining different types of data (Linkage analysis)

This simplistic table shows where you can combine different types of data and get meaningful insight.

Lets look at a few examples 

Combine financial and operational data

Using data from your call center, calculate the cost of a specific support calls either for all or a sample of your agents. Use actual labor rates and actual talk time.  Do you see agent-to-agent differences?  Look at the top and bottom 10%.  Are there differences in experience or training? Are you being penny wise and pound-foolish by cutting back on training or coaching?  

Now look at the satisfaction rating received for these top and bottom 10%.  Any useful story here?

Combine Operational and CSAT data

We all have goals or targets for the important aspects of our business.  Some are based on “industry best practice”, some are based on feedback from a small number of important customers, and some were established in the early days of your organization’s history and never updated.  But there is a much better way to establish targets – based on your customer’s feedback.

This figure, from “When Citizens Are Your Customers” by Sebastian Katch and Tim Morse in McKinsey Quarterly Aug. 2009 shows breaks in the CSAT vs. resolution time relationship, indicating appropriate targets.


For a skilled data analysis junkie, not a data scientist, there is a great deal of useful information to be gained by looking at all your data together and drawing the appropriate conclusions to improve your customer’s experiences, financial results, and employee satisfaction (a side benefit of making your customers happier).

At Middlesex Consulting we can help you analyze your data and get started down the path of moving towards operational excellence.  Contact us to find out how to start.