How complete a picture do you have of the effort needed this year to answer telephone questions?
To what extent do your forecasts of the number of telephone questions differ from reality?
What are the Top 5 reasons why the actual number of telephone questions differs from expectations?
If you work in the public sector, this often means you have access to a budget and want to provide as much service as possible with that budget. Unforeseen events can have a detrimental effect on the basic service provision that citizens have come to expect from you. Unexpected costs often result from complex processes that are being undertaken to comply with the latest applicable legislation and regulations. However, these processes are often far from clear to citizens. This leads to more telephone questions than initially anticipated, a larger proportion of complaints and appeals against decisions taken, a larger proportion of applications and letters to send, and so on. How can you gain greater control over your interactions with citizens? And how do you avoid these creating costs in excess of your budget ceiling?
At Cmotions we use artificial intelligence to gain more control over interactions with citizens. We do this in The Analytics Lab, which is a kind of laboratory where we use state-of-the-art methods to add value in organisations. This includes forecasting the volume of telephone questions. The number of questions is sometimes difficult to predict and control, which causes inefficiency in costs and a drop in customer satisfaction. Using artificial intelligence enables us to:
This means the gap between the forecast and the actual volume is significantly reduced. This directly saves money on the FTEs available and the number of inbound lines and office spaces. This also increases customer satisfaction: waiting times are minimal and there is less pressure on the Average Handle Time during a conversation.
Does this situation sound familiar and is there room for improvement? If so, you should get involved in developing dashboards that give you more control. By forecasting the unexpected, you can do so much more with the resources available. In addition to a number of standard metrics supplied in a clear Dashboard, you also get more control of the unexpected from the:
Based on a dataset that we created ourselves, we used our data sampler to make a preliminary version of a dashboard to get more control over unexpected costs. You can see the initial results of this below. This Dashboard is in constant development.
We work towards a situation where we use artificial intelligence to get better control of unexpected interactions by following the steps below. We can get started with them today. Are you interested in only part of our solution? That is possible too – we like to take a pragmatic approach to achieve results quickly.
