The Risks of Short-Term Monitoring of Measures

July 15, 2014 by Stacey Barr

Lots of my new clients share the same habit (a bad one): they conclude whether performance is getting better or worse by comparing the current month’s (or week’s or quarter’s) performance measure value with last month, or with a target or standard. If this month (or week or quarter) is worse, they go digging for the cause. Trouble is, they don’t find that cause.

I’m a novice mountain bike rider, still striving to get stronger on hills and more skilful through the technical single-track trails I just love to ride. I’ve noticed when riding my mountain bike, if I look too close in front of me, about a metre or two, every rock, log, rut, and patch of loose pebbles looks like something I need to correct for.

Paying so much attention to these short-term obstacles makes me try too hard to control where my front wheel goes, and I end up correcting so much that I can get the wobbles and down I go.

But if I instead look further ahead, paying attention to the bigger picture at least 10 to 30m in front of me, the bike tracks more smoothly. When it hits one of those rocks or ruts or patches of loose pebbles, it’s no big deal. We just move through them, and keep going forward.

Continuing like this, and as my riding skill increases and my fitness improves, I can absorb more of these obstacles in my process and they have less affect on my control of the bike. Overall, my mountain bike riding experience moves to a higher level of performance, and interestingly, with less effort. I can more easily pinpoint specific skills or behaviours or bike set-up attributes that I can sharpen and hone.

My new clients haven’t found the causes of their so-called performance dips because the causes don’t exist. They might blame things akin to rocks or logs or ruts or patches of loose pebbles. Performance isn’t actually getting worse; there are always rocks and logs and ruts and patches of loose pebbles that make our ride less than perfectly smooth and predictable. Most of the time, when I do a proper time series analysis of their performance measure values, it proves that overall nothing has really changed at all. Not in a long time.

Here’s the real problem: When we look only at the short term, we end up over-correcting and tampering, making variability worse. Just like I do when I focus on the obstacles immediately in my path on my mountain bike. Over-correcting causes the month-to-month or week-to-week or quarter-to-quarter variation in performance to increase. Increased variation is the enemy of high performance.

The entire field of quality and process improvement – which has revolutionised many industries over the last 60 or so years – centres on the endeavour to manage the factors that cause controllable variation in performance, so we can get more control (or at least influence) over that performance.

We need to look longer term and understand the natural variation in our business processes (those work flows that produce the results we measure), and learn about the factors that have the most impact on the variation’s size. We need to keep our eyes on the big picture.

TAKE ACTION:

Abandon point-to-point comparisons when you look at your performance measures. You’ll just end up over-correcting. Look instead at a longer timeframe, and pay attention to patterns in variation and changes in those patterns. It’s the patterns, not the points, that hold the potential for improving performance.

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  1. Zoe Routh says:

    This sums it up for me: “It’s the patterns, not the points, that hold the potential for improving performance.” Such great advice. I’ve been obsessing with my own ‘points’ rocks, dips, bumps – and gently trying to remind myself, “play the long game”. Great article! Love the mountain biking metaphor!

  2. Steve T says:

    I absolutely love the analogy Stacey. Well done. By the way, how is that new book coming along. Looking forward to securing a copy.

    Cheers

    • Stacey Barr says:

      Ta, Steve. The book is in final prep for the printer. I’ll be hosting a ‘launch webinar’ to announce the book in August. Stay tuned – the details will come out in an upcoming issue of Measure Up.

  3. Cheryl Welch says:

    Spot on, Stacey! What a great analogy. I can see myself using that to explain the value of long term thinking to those at my own organization. Thanks for sharing these bits of your own life that we can all relate to!

    • Stacey Barr says:

      Does that mean you’re a mountain-biker too, Cheryl? 😉

      Everyday analogies are so helpful in explaining dry concepts like those to do with performance measurement. I’ll keep practicing and coming up with new ones!

  4. Stacey, I have liked this post so much that I felt compelled to translate it into Spanish and publish it in my blog. What you say here is obvious to anybody with some knowledge of SPC, but the metaphor you have used is excellent to explain these concepts to top management.
    I agree that you have to ‘play the long game’, but after you have for some time (25 to 30 periods?) then you can calculate upper and lower limits and also watch individual measures, because maybe it could be a ‘special cause’ and you could try to find and eliminate it as soon as possible.

    Best wishes for your new book.

    Tom P.

    • Stacey Barr says:

      Tom, can you send me the link where you posted it in Spanish? I have a few Spanish readers who might appreciate that, and share it with their colleagues too. Thanks so much for your support in sharing these ideas.

  5. Indy says:

    Terrific article Stacey. One of many you publish of course. Amazing how quickly we can lose focus of the end goal, and get caught up on odds and ends that, overall, don’t change the journey, simply delay it. Great analogy.

    • Stacey Barr says:

      Indy, because of the very point you make, I think that’s why performance measurement is always a ‘practice’ and never a ‘state’ we definitively reach. Heck, I specialise in this field and I’m still reviewing my measures and throwing some away, adding better ones, changing others, etc…

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