Why Dashboard Dials and Gauges Are Useless for KPIs

Stephen Few’s arguments about dashboard gauges and dials can be summed up nicely in his own words: they “say little and do so poorly”. Agreed. But there’s one specific reason that gauges and dials totally suck when it comes to KPIs.

Performance measures, or KPIs as they are often nicknamed, are a very special type of quantitative information.

While you might have more than just performance measures on your dashboard, you need to display your performance measures in a very specific way or they will fall far short of their purpose.

The purpose of performance measures is to track change toward a target through time.

Just because you set a target doesn’t mean it’s sensible to compare every week or every month to that target. You have a target because you want performance to improve. Performance doesn’t improve immediately – you need to allow time to change your processes so they become capable of operating at that targeted level.

So performance measurement involves monitoring change over time, and looking for signals about whether it’s moving close enough and fast enough toward the target.

WARNING: Dials and gauges don’t show change over time!

Dials and gauges only show a snapshot of performance. They show this month compared to target, for example. They don’t show if performance is increasing toward target, or if it’s moving away from target, or if it’s refusing to change at all.

You need this context in your performance measures to help you prioritise how much attention you need to give to the initiatives that are supposed to be closing the gap between your starting level of performance and your targeted level of performance.

And because Dials and gauges don’t use this context, they are also incapable of showing you true signals in your measures.

WARNING: Dials and gauges highlight false signals!

The size of the gap between this month’s performance and the target is NOT a measure of how far away from target your performance is. This method of assessing performance completely ignores the fact of natural, routine variation.

Dials and gauges have you knee-jerk reacting to routine variation in your measures, and fail to tell you when there is a true signal of change toward or away from your target.

There is a smart way to show performance measures on dashboards.

The best way of presenting your performance measures in dashboards, which will both provide historical context and valid rules for signals of change, isn’t currently available. It’s what I call a smartline. But these are not available yet in any dashboard application I know of.

If only our dashboard vendors knew more about what dashboards are used for.

JOIN THE DISCUSSION:

Do you agree that discrete measures are as useful as continuous measures? What’s your reasoning? Share your suggestions on the blog.

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Comments

  1. Kevin Ryan says:

    Hi Stacey,

    Regarding why Tableau have added gauges probably has to do with their IPO. Forget customers, give shareholders what they think they need!

  2. boris says:

    Performance has to be measured and predicted (for next measuring cycle) continuously. At the same time all parameters influencing targets (objectives) have to be monitored as well. Changing (adjusting) targets when it makes sense is part of clever management.

    • Stacey Barr says:

      Boris, I am not sure if what you are suggesting is an argument FOR gauges or AGAINST. Continuous monitoring is certainly essential, like you say, and so it adjusting targets when it’s sensible to do so. Using smart charts is definitely the better way to facilitate this. Gauges mask the movement through time that is so critical for interpreting trends and shifts. Thanks for commenting!

  3. Clive says:

    Hi Stacey,
    It would be very difficult to argue that dials and gauges provide useful information in isolation. However as part of the overall story they can provide a purpose. By combining a snap-shot gauge with historical information/data, a trend view and a target view you can provide a very powerful information graphic. The gauge can provide an alert for an anomaly e.g. if there is a fall into the ‘red-zone’ and the historic data and trend-line can give you the history and potential future view. This way you can see unusual changes, quickly look at some evidence and not make an incorrect judgement. If you would like to see this in action take a look at the software recommended by the Balanced Scorecard Institute, QuickScore, it provided exactly this and a whole lot more. Great blog by the way, always find these discussions interesting!

    • Stacey Barr says:

      Clive thanks for the comment!

      I still believe that all those things you’re looking for can be accomplished by one graphic – the XmR chart or what I call a smart chart. The problem I have with gauges and dials is that the needles usually represent the current month’s performance and the zones represent some target range. This encourages a point to point comparison, which ignores the routine variation that every measure will have. The signals of change come from patterns in the measures, not from a point of the measure. Just because reputable organisations use them doesn’t make them right!!

      Clive, have you read about XmR charts, or my little invention the Smartline? There are links in the article above to both.

  4. Osamudiamen osagie says:

    i have a challenge. how can i develop a performance measure that synchronizes with recruitment and selection such that one who scales through the recruitment and selection process will automatically be a high performer. any hints?

    • Stacey Barr says:

      Osamudiamen, my hint is to map out the flow of RESULTS that you want along the journey of an employee from job applicant to high performer. These results will be in a cause-effect chain, and that’s how you can get the synchronisation. For example, a result at the job applicant stage might be “New job applicants are perfectly suited to the positions”. A result at the selection stage might be “The best job applicant accepts the position”. And so on.

      When you have these results articulated clearly and specifically, it’s much easier to measure the degree to which they are actually happening.

      This takes practice. But it’s the essential first step to developing great performance measures (actually it’s the second step in the PuMP Blueprint, the first step is engaging people who will develop the measures).

  5. Stacey,

    Continuous measures are the right way to asses progress overtime. When I first started to do online marketing for a client, I was using gauges to track his website position in two major search engines against the number of total online interactions. Of course this was a terrible way to measure either of these indicators, because as you point “purpose of performance measures is to track change toward a target through time.” I won’t get into why I decided to measure these metrics this way, but suffice it to say that soon enough I recognized this was useless. Now I use time-series, which also allows me to mark important events and/or set goals. Through this type of charts it is easy for me to see tipping points, events that have significant impact in performance, and whenever I’ve reached I goal.

    I think gauges and dials may be good to illustrate correlation of variables.

    Thank you for insights

  6. Marcelo says:

    Hi Stacey.

    You argued about the sparkline that “these are not available yet in any dashboard application I know of.”

    QlikView does. I tried to post an example here but it’s not accepting URLs.

    I use this funcionality on the Dashboard I’ve developed with QlikView.

    Best!
    Marcelo

  7. Rick says:

    I really liked reading this post if not only to start a very interesting discussing. I do agree with you on most parts, but I agree with prior respondents very much as well. When Time and Targets are involved I’d say that the Smartlines as you call them give much better insight. However: When it comes to KPI’s that are not time related gauges still can give fast insights to performance. In the picture you show a gasoline meter which is quiet a good example of a non-time-related gauge. All you are interested in is how the meter is reading now. In performance measurement of business processes examples of these are for instance Sick Leave. You can measure your current percentage and compare it with a target, which is not time-related. In our line of business we also offer solutions for Trading Companies, which are highly interested in their (long-term) risk position. They want to know if it’s good any given moment in time, and not compared to previous of upcoming periods.
    When it comes to the Smartline visualisation I can tell that the current version of Oracle Business Intelligence has a feature for this called Trellis Graphs which can do exactly that.

  8. Ashok Singh says:

    In some cases Dial does make sense where historical data is not important .

    Information is presented in Dial some user will have rejection for Dial because of long legacy of using previous conventional method.

  9. Rich Torr says:

    Rotational gauges are poor visualisations for all the reasons given by Stephen Few; we find it hard to read rotational angles, comparisons aren’t possible, they take up too much space, they employ non-data ‘speedo’ decoration etc… Anyone putting the case for rotational gauges might want to seek out his guidance on why bullet chart types are always better. The most important point though seems to be whether snapshots alone can ever offer better insights than time series (and XmR) charts. Some contexts might use both simultaneously to communicate the richest possible story for a measure, eg a bullet chart and a Sparkline, a Smartline (mini-XmR) with a pareto. If you can only use one viz then I vote for the Smartline.

  10. Mike says:

    With all due respect, I disagree completely. There is a difference between snap shot performance indicators and those that show trends and they are to be used for two completely different things. When driving, I want to quickly see how much gasoline I have left……………and only want to see the trends when analyzing the perfomance of my car. I don’t want to know that I have 10.4 gallons of gas left, I want to know the trends of my gas usage when analyzing the perfomance of my car.

    Too often in manufacturing, there is a tendancy to “make charts not parts”. Use the tools appropriately and don’t get infatuated with OCD data when you don’t need it.

    • Stacey Barr says:

      Mike, your distinction is a good one.

      Using measures as snapshots is to me about working IN the process, to help make operational decisions. Adjusting the pressure of my foot on the accelerator.

      Using measures to monitor performance over time is about working ON the process, to make more strategic decisions about whether processes need to change or not. Deciding if I need to go to driving school to learn to drive more fuel-efficiently to bring down my consumption rate.

  11. Oriol Llobet says:

    As said by other readers, the dials are designed to give a quick look at puntual data, so for the assessment of the time series there are other more appropriate visual aids (graphic lines monthly, monthly bars …), which in the best case should be fixed at least in previous 11 months (‘n’ number of weeks).
    A good dial, representing the degree of timely progress on the objective stated in a given month (period) gives a shocking first visual input that does not give a bar/line graph. Everything serves its objectives. The central issue is to be clear which tool is best suited to what purpose.
    I use this type of dials to present visual information of the moment, and then I always put in the time series analysis in next sheets.
    The criticism made is so out of place as if it is to make a dynamic financial analysis with information from a single accounting period, rather than taking three to five previous periods at least.

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