There is no doubt that we can all learn something from history. Apart that is from me! I seem to be doing the same stuff and funnily enough get the same result. Change can be difficult!

Each month we process our clients billing data to review and report. Last month, as one particular clients’ data started to roll through the system, our data visualisation programme began to produce its results and noted a massive 300% spike in toll-free costs over the previous month! Alarm bells started to ring as we had just finished assisting the client with the transition to a new service provider. Initially, the resulting Toll-free costs were lower than even we expected. With widely different toll-free billing the client needed to identify the causal issues so that they could set a budget for 2019.

Your first thought might be to assume a billing error; perhaps the charged rate was incorrect or had the carrier overbilled the number of calls? On checking, all billing was accurate, but the data showed a considerable increase in call volume. We compared data year on year to see if we could see any patterns. Fortunately, we had been storing several years of data and the ability to quickly produce an analysis of the previous five years of monthly calling patterns.

After analysing the problem with the client, we were made aware of an early sales and marketing push which successfully resulted in call volume over and above the normal promotional peak in calls. The result of the campaign exacerbated the bill shock effect as the call volume in December is always the lowest and January one of the highest.

If this pattern continued how would it affect the telecommunications budget and call loading in the call centre? As we had renegotiated the contract last year the toll-free rates had significantly reduced, so it wasn’t necessarily straightforward to calculate. However, with the historical data, we were able to get an excellent idea of what might happen using Tableau visualisation and forecasting tools and advise the client accordingly. See an example of the visual analysis below.

Des Small
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