What we get wrong about 'Big Data' in field service management

‘Big Data’ -- or even just data in general and not of a ‘big’ variety -- is very important to the monetization of field service. Collecting, then analyzing, then using data properly can be a huge benefit to your business. But check this out: there were three steps listed there.

1. Collect

2. Analyze

3. Use

Organizations often don’t go through all three steps, or get stuck focusing on the processes involved at one specific step. Without moving through the steps logically, it’s hard to achieve any business advantage from data.

Consider this image:

That’s a data visualization Florence Nightingale did over 100 years ago; it’s from this post from Kellogg (Northwestern), which is a great article about visualizing data.

On the surface, do you completely understand what’s happening in this visualization, or what it represents? Most people would probably say they don’t completely understand what’s happening, and that’s akin to how most data processes fall apart.

In this case, from over 100 years ago, data was clearly collected, and then there was an attempt made to analyze it (the graphic above), but then you come to a problem: use.

If people don’t understand the data or how the data is being contextualized and presented, no one will be able to use it properly. Remember: this is from over 100 years ago. Jobs are busier and more comprehensive today. People have a large range of responsibilities. If they’re presented with something new and can’t figure it out relatively quickly or know what to do with it, they will move on back to things they understand and have to work on, such as their daily tasks.

You can’t move from ‘collect’ data to ‘analyze’ data to ‘use’ data without having people that can explain the data to the widest possible audience.

That doesn’t necessarily mean hiring a series of data analysts for your field service business. First off, that might be expensive from a headcount perspective. Secondly, data analysts are often very smart and great additions to a company, but because of their connection to the data and information you’re collecting, they often can’t explain it back in a way that your sales team would understand or appreciate.

Consider this, from the same Northwestern article above:

“Nobody ever gets taught these rules. You take writing classes in college. You don’t take a graphical communication class. This is a skill that people need to have. If you learn these rules, it will have a multiplicative impact on how well you can convey your ideas to people and how well those ideas will actually sink in and then lead to action.”

In a field service organization, what you actually want to do is try and create ‘a culture of analysis,’ which can sound like a series of buzzwords, yes. Here’s what we mean: anyone who works with customers -- probably most of your organization -- should be able to understand the key KPIs that the organization tracks, know how to locate them within your systems and processes, and know what to do with them once they’re located. ‘Data’ needs to be a shared responsibility, not one reserved for a few analysts or ‘data guys.’

We've seen that the point of 'Big Data' isn't so much collecting all the data, but collecting the targeted data -- or, in other words, the right data for your field service organization. That will allow you to make smart decisions with regard to your customers. But why is THAT important? For dozens of reasons. To learn more about the crucial role of field service management in customer experience, download our eBook. Once you've read it, contact us with any questions. We'd love to help you with data applications and customer experience modeling -- and show you how to tie the two together for business growth. 

Written by Jim Hare