All Posts

How to Increase Field Service Performance by Reducing Variability

If the name Garrison Keillor rings a bell, you know that in Lake Wobegon, “all the children are above average.”

“We just want you to be average.”

I used to work with a field service manager who was fond of telling technicians “We just want you to be average.”

I asked once why he didn’t want them to be excellent, or even very good. He showed me graphs charting the time it took different technicians to solve the same problem on different calls. These graphs of “same issue resolution time” all looked the same: A bell curve skewed to the left, that showed a short tail of techs solving the problem quickly, the peak of the curve near the mean time to repair (MTTR), about 2/3 of the techs solving the problem within half an hour on either side of the mean, and then a long tail to the right of techs taking a lot longer to solve the problem. Then he said, “It’s not the mean that is killing us, it’s the variability. If techs would perform closer to the mean, we could handle more calls per day.”

Then he told me the part that seemed radical: “In fact, we could even increase the MTTR, but if we drive the variability down enough (i.e., shorten the tails), we could handle 25% more work with the same workforce.”

That’s right – in Field Service Management - if we increase the average time to repair, but have performance closer to the mean, we can do more work (see the inset for an illustration).

EA_Illustration_FS-Be-Average_2014-01-22

So how can we help make your technicians be more “average”?

  • Focus on task-oriented content – how to diagnose, repair, and test. Task-oriented procedures are the essence of best known methods, and providing them this structure will have them all running the same plays.
  • Give them information they need, in a useful format. Technicians won’t use paper-based documentation for lots of reasons. Give them information they can search and display on their go-to portable device.
  • Give them information they can trust – that is current, authoritative, and reflects the world they operate in – which is not the world the technical writer envisioned when the product launched.
  • Help them collaborate to solve emerging issues that aren’t documented, and make their collaboration searchable.
  • Measure what they use and search for – and use this to inform what information is missing, and what deserves to be better.

For a look into how we use information architecture as the foundation for digital transformation read our whitepaper: "Knowledge is Power: Context-Driven Digital Transformation

Earley Information Science Team
Earley Information Science Team
We're passionate about enterprise data and love discussing industry knowledge, best practices, and insights. We look forward to hearing from you! Comment below to join the conversation.

Recent Posts

Use Customer and Behavior Data To Create Personalized Experiences

The more quickly customers can find the product they are seeking, the more likely they are to complete a transaction and to return to the site in the future. Personalizing offers and making well- targeted recommendations can bring customers and products together faster, and are effective ways to engage customers by creating a more positive customer experience. In order to do this, companies need to capture and use as much relevant information as possible. The more that is known about the customer, the more effectively the recommendation system works. Customers generate many signals through their online behavior, and those signals can also be used to understand their interests, purchasing patterns, and needs. Reading their digital body language accurately and creating a valid customer model is essential to anticipating and fulfilling those needs.

How to Instrument KPIs Throughout the Customer Journey

You're probably using metrics to determine if your marketing programs are effective. But, have you selected the right metric at each stage of the customer journey?  Which ones connect to your strategic goals? In this session Seth Earley and Allison Brown talk about how each stage of the journey can be instrumented to use feedback from course corrections to further improve the process. You'll learn: Types of operational and user experience metrics and KPI’s How to select and collect the right metric for each stage of the customer journey How KPIs can be used for data-driven decisions How to manage conflicting goals and metrics

First Party Data - Managing and Monetizing the "Data Exhaust" From Your MarTech Stack

Understanding, anticipating and responding to the wants, needs and behaviors of your customer is the competitive battlefield of 2022. However, with new limitations and regulations regarding second and third-party data and tracking cookies, marketers, digital leaders and ecommerce executives have to consider their own methods of collecting and acting upon the data they gather about customers. In this webinar Seth Earley will talk with industry experts about how you need to model, collect, normalize, organize, manage, analyze, and act on customer information. The time to do so is now and we’ll discuss practical ways to move the needle on customer data, customer analytics and orchestration of the customer experience.