The concept of data analysis and analytics has become mainstream over the last few years. From consumer behavior to the Internet of Things, analytics have been applied to help us dig deeper and unearth trends not previously seen.
On the surface, this seems to be the perfect solution to understanding your business. More analytics means better business. Or does it?
The danger I see in this is when an organization buys into the concept of analytics, for the sake of analytics. For analytics to drive business value, it needs to deliver actionable insight. Actionable means that you can base a business or operational decision on the insight gleaned from your analytical methods.
We need more than colorful charts.
Analytics for the sake of analytics can mean you end up with pages of pretty graphs and visualizations, but have created so much noise that it’s tough to identify the key drivers of your business.
At SpryPoint, we’ve been digging into what many would call analytics. In developing our analytical tools our objective has been simple: If analytics don’t deliver actionable insight, what’s the point?
Let’s take a look at our work in the utility industry. Our initial foray into utility data analytics has been focused on profiling consumption and demand trends of commercial and industrial customers.
Why focus on commercial and industrial utility customers?
Since we’re talking analytics, let’s take a quick look at the data. According to figures released by the U.S. Energy Information Administration in January 2015, total kilowatt-hours consumption is similar between Residential and Commercial customers. Here, we see Commercial customer consumption averaging about 95% of Residential consumption over the 10-year period ending in 2014.
Now, incorporating Commercial plus Industrial consumption in the analysis we see that over the last ten years, usage has averaged 166% of Residential consumption.
While our experience has shown that for many utilities, Commercial and Industrial customers represent a large segment of revenue and power usage, the data helps confirm this experience.
Let’s get back to delivering actionable insight.
For an electric utility, reducing peak demand can have a material impact on your overall power costs and subsequently the amount being charged to your customers. While it would be ideal to have all customers (Residential, Commercial and Industrial) reduce peak demand, this can be an intimidating endeavor and a costly objective to achieve.
However, if we look at the Commercial and Industrial customers for many utilities, this cohort typically accounts for a small fraction of your overall customer base, yet is commonly responsible for over 60% of total energy consumption.
Our hypothesis is that if we can help these customers visualize and make sense of their consumption and demand profile, the customer will want to adopt business practices that reduce their utility expenses. As a result, the utility should see a reduction in overall power and infrastructure costs.
We’re going to continue the discussion on analytics over the coming months and look at different ways in which analytics may be able to help your organization reduce operating costs, identify collections issues and more.