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[Data] Decoded: How Much Time Is Your Company Wasting?

This post is a part of my thinking around the concepts I wrote about in my latest book, “The Decoded Company: Know Your Talent Better Than You Know Your Customers.”  You can see other thoughts about big data, organizational culture and talent management here

I spotted a recent HBR blog post last month that underscored our need for better data systems inside organizations. Entitled Quantify How Much Time Your Company Wastes, author Ryan Fuller, laments the wasted, untracked time that goes down the drain at the end of each business day. The numbers he quotes are frightening: one Vice President in the technology sector reported spending an average 44 hours a week on meetings, under 22 hours on emails alone.

“There are so many initiatives, goals, peoples, customers, and vendors competing for our time that it’s extraordinarily challenging to just simply focus,” he writes. “This is changing, however – just think about how many companies are utilizing sophisticated social intelligence algorithms to create a deeper understanding of their customers’ patterns and behavior.”

It’s Fuller’s next piece of advice that really caught my eye, and I think you’ll quickly see why:

 

The next step is turning these analytics inward – harnessing the massive amount of e-mail, calendar, and messaging data a company already has – to diagnose surprising inefficiencies that exist at an organizational level.

 

What’s that Ryan? Organizations should know their talent as well as they know their customers?  I totally agree! Though I might be a little biased. The Decoded model is built on understanding that attracting the best talent is now a survival imperative for companies facing today’s economic climate. Attracting those people is only half the battle: the real work is in making sure they are happy, empowered and motivated. That’s where data can come in to help create better training practices, introduce flexible policies and engineer the types of behaviours that create the best cultures.

The article lists three tips for organizations including: identifying expensive errors, monitoring partner relationships and personalizing feedback loops (which we focus on in depth in one of the chapters.)

I wanted to offer my own suggestion:

Measure your baseline time expenditure. 

Humans tend to be naturally optimistic when it comes to estimating the time of work it takes to get something done. We are more likely to under-estimate the actual time. We also are prone to losing small chunks of time that can add up. Plus, the human memory is a falliable thing that is often prone to rewriting experiences to fit our own narratives. This means that many of us think we have an idea of how many times we get interrupted in a day or how long it takes us to complete a task, but without data to back that up, we could be totally wrong.

Here are three ways to experiment with this:

  • Try a service like Rescue Time which runs in the background of your computer and tallies the websites you visit and the tasks you work on. You might be surprised (as I was) that you think you’re only “glancing at twitter every now and then” when you’re actually spending four hours a week on the social media platform.
  • For those that want a more analogue experiment here is a very easy one from the book. Take a pad of paper and a pencil. At the beginning of the work day write down your best estimate for the number of times that you’ll be interrupted between 9am and lunchtime. Then, every time you get interrupted from a task, be it a cheery colleague stopping by or an email that requires your attention, make a tally mark. At lunch time compare the number of marks to your theoretical number.
  • Ask your team to rate the usefulness of the meetings they attend on a scale of 1-10 for one month. They can do this in a shared spreadsheet or you can even ask them to anonymously submit scores on post-its at the end of a meeting, whatever works best for you. At the end of this period, take a look at your numbers. Most people we’ve worked with who have conducted this experiment have discovered that there were a few meetings (or more) that no one found useful. By eliminating these meetings they were able to increase morale and productivity!

Consider the following questions:

  • Were you surprised by the results?
  • Were your estimations of time expenditures accurate?
  • What is the major insight about how you spend your time?
  • Is there something that can be changed?

 

The best tool you have is knowledge, a true understanding where your time is going. It’s only by understanding your baseline that you can start to make constructive changes, and identify underlying issues – like too many meetings or Kevin from accounting who always drops by for chats that last for 20 minutes.

If you’d like to learn more about how you can apply The Decoded Model within your own organization, feel free to email me as I often (time permitting) take on a few clients to help implement our principles. You can contact me here.

 

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