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  • Listen to the data: it will speak if you let it

    As a leader, I believe it is imperative that you ask people to bring the data. I am sure that you have experienced a situation where something has “gone wrong” and everyone has an opinion. Everyone knows who or what to blame. And certainly, everyone thinks their opinion is correct.

    In situations such as these, I ask people to state crisply and clearly what they believe the situation is. They also know that I expect to have data that supports the issue or the cause for concern. Without that, there will be no discussion. I will gently turn them out of my office until they get the data.

    Why do I feel so strongly about being data-based? From my quality training, one statement is etched in my brain: “A point does not a trend make”. It is human nature to take one event, and draw conclusions. Those conclusions invariably are wrong. The result is time and effort wasted. Let me illustrate with an example.

    I was helping an organization with their call center operations. Initially, I received a few phone calls from corporate stating “no one is answering the phones”. This conjures up an image of 15 – 20 people sitting around with their feet on their desks doing nothing, while all around you hear the cacophony of phones but no one answering. Sitting on the floor with the team, I can assure you that never happened. I asked how they knew no one was answering calls. Did they have data? Oh, no data, a customer just called and told me.

    The beauty of the situation was the company had great telephony that captured the incoming calls, call times, wait times and dropped calls. They also had a daily staffing chart. The call center manager and I defined the situation as follows: in some cases a customer calls and cannot get through to customer service. Definitely, it is an issue that must be solved. However, it cannot be solved by just “telling people” – be sure to answer the phone. We needed to understand what was happening; we needed to see the data.

    A group of us huddled together, and determined to create the following:
    • Histogram of calls, in 15 minute increments for the last 4 weeks.
    • Chart of people working in 15 minute increments for an entire week. [This did not change by week.]
    • Chart of the number of dropped calls in 15 minute increments.
    • Histogram of the length of calls, and the average length of a call.
    • List of all one-off actions during this time, such as the launch of a new product or the mailing of a brochure.

    Once the data was assembled, we reviewed the data. The graphs made the issues easy to see visually. We found both daily and weekly patterns in the timing of the incoming calls. Not surprisingly, call volume was not a straight-line. There were peaks and valleys. However, in general, staffing was a straight-line. It was also apparent that when a significant communication touched the customers, call volume also increased.

    So, with the help of the staff, we created a weekly staffing document that more closely matched the call volume. We continued to monitor dropped calls, and found that they significantly decreased. The team agreed to chart the data on an on-going basis to ensure the customers were getting the service they deserved.

    The benefit of listening to the data to it is twofold:
    [1] It builds trust between teams and individuals. It takes the emotion out of conversations when something goes wrong. No longer are two teams pointing fingers at each other. Rather, they are working together to figure out what is going on and fix it.
    [2] It allows the team to see what is happening in the process. It pin-points the real issue and allows them to develop a workable solution.

    Without the data, the team would never have figured out what was going on. They could never have developed a solution. The lesson of the story is: find the data, it will always help you discover the root cause and develop a lasting solution.

    Published on March 15, 2012 · Filed under: Coaching, Leadership, Process Improvement, Supervision; Tagged as: , , , ,
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