Why Embedded Analytics Beat Dashboards & Reports

Benjamin Wootton

Benjamin Wootton

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Why Embedded Analytics Beat Dashboards & Reports

Most Business Intelligence or analytics projects today aim to deliver reports and dashboards as the eventual output.

The idea is that these reports or dashboards will be periodically used by someone in the business to inform their day to day activities or longer term strategic decision making.

Whilst of course reports and dashboards can deliver great value, there are often more effective delivery routes. For instance, maybe we would be better to send an SMS alert in response to some situation, or enhance some application such as a CRM system with the insight.

We sometimes refer to this approach as Embedded Analytics, whereby we are taking analytics off of dashboards, and instead directly embedding them within the users experience.

The benefits of embedding analtyics and insights closer to the users day to day activities are as follows:

  • The time is reduced between some event happening and getting the insight into the hands of the user
  • The insight is more likely to be acted on if it is placed front and centre in front of the employee
  • Acting on the insight takes less effort when it is placed directly into the customer experience
  • We begin using data and analytics more operationally and proactively, before KPIs are impacted rather than after

Examples

With Embedded Analytics, we aim to take the insights generated, and integrate them directly into an operational business process so that KPIs are improved immediately rather than after the fact.

For example:

  • If you identify that one of your call centre agents has high customer service reviews, you should automatically route high value customer calls to that agent;
  • If you identify that a machine is running hotter than usual, you should automatically shut down the machine and schedule maintenence;
  • If you identify suspicious activity on a bank account, you should automatically block the relevant transactions until a human has investigated;
  • If you identify that a popular product is running low on stock, you should automatically place an order for new stock proactively earlier in the day.

Bringing intelligence into your operational activities in this manner could have huge impacts to revenues, cost profile or customer experience.

Delivering Insights In Context

In order to make use of Data and Analytics for operational purposes, we need to be much more proactive in pushing insights to employees through more dynamic and immediate channels than reports and dashboards.

For instance, pushing notifications into the day-to-day applciations that people use, triggering notifications via email or SMS, or developing custom mobile applications.

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