Tag Archives: sparklines

Advanced Analytics, Part IV

This post is a next on in the series on Advanced Analytics. Check out previous introduction, ruminations on conveying information, modern concepts on information and data for executives.

Dashboard or not Dashboard?

There is nothing wrong about dashboard, except it’s puts a stereotype on your consciousness and that defines your further expectations. In general dashboards are good, check out this definition from Wikipedia: “An easy to read, often single page, real-time user interface, showing a graphical presentation of the current status (snapshot) and historical trends of an organization’s key performance indicators (KPIs) to enable instantaneous and informed decisions to be made at a glance.”

Easy to read sounds exciting, at last executive or operating information will be friendly and easy to read! Single page is resonating with my description of A4 or letter size [What to communicate?] due to anthropological sizes of our bodies and body parts, and the context of information consumption, usability. Real-time user interface could be even improved with real-time or near-real-time data delivery to the user. Visualization as a graphical reps for the current status – snapshot – and dynamics/trend of the indicator is resonating with ‘All Data’. Enablement of instantaneous and informed decisions is resonating with Vital Signs.

So the conclusion is to dashboard. The open question is how to dashboard? Is there are standard for dashboard? What are the best practices? What are known pitfalls? How modern dashboards will look like? Let’s start with what are known problems, so that we know what ti overcome to make dashboarding more usable and valuable.

Gauges suck!

Dashboard gauges and dials do suck. It is wrong way to visualize information. What is a gauge? From Wikipedia: “In engineering, a gauge is a device used to make measurements or in order to display certain information, like time.” Primary task of the gauge is to perform measurement, secondary task is to display it. Furthermore, the gauge must use special principle of measurement, because same things could be measured via multiple different principles (e.g. temperature could be measured with mercury thermometer, infrared radiation, resistance thermometer and other ways). What “dashboard gauges” do? Gauges do not measure anything at all, while they do display almost everything. That’s a root of the problem. To be specific the problem lays in the ill application of the principle of analogy [skeumorphism].

What are other problems of the dials/gauges?

  • They “say little and do so poorly”. By Stephen Few.
  • They might look cute, but like empty calories they give little information for the amount of space they consume. By Aeternus Consulting.
  • Retro design is crippling innovation. By Wired. Skeuomorphs aren’t always bad; the Kindle is easy to use precisely because it behaves so much like a traditional print book.
  • Do you know how much research went into determining that idiot lights and gauges that look just like those in our cars are the best way to display information on a dashboard for monitoring your organization’s performance? The answer is zilch; none whatsoever. Back in the beginning when we started calling computer-based monitoring displays dashboards, someone had the bright idea of making display widgets that looked like those in cars. This is an example of taking a metaphor too literally. By Stephen Few, Perceptual Edge. Hence don’t be fooled by the illusion of control instead of real control.
  • And several more arguments of why dashboard dials and gauges are useless for KPIs. I will devote entire next section to those details. Keep reading.

Gauges are bad for KPIs

This section extends and continues the previous one, with more dedication to the visualization of KPIs. What are KPIs? From Wikipedia: “A key performance indicator (aka KPI) is a type of performance measurement. An organization may use KPIs to evaluate its success, or to evaluate the success of a particular activity in which it is engaged. Sometimes success is defined in terms of making progress toward strategic goals, but often success is simply the repeated, periodic achievement of some level of operational goal (e.g. zero defects, 10/10 customer satisfaction, etc.)” Just read aloud and listen to your words – activity, performance, progress, repeated, periodic. All those words mean duration in time. But what we have on the gauge? Nothing. The gauge clips and ignores everything except current value. That’s poor. This and other problems are listed below, they are partially reused for your convenience from Stacey Barr blog:

  • The purpose of performance measures is to track change toward a target through time. Performance doesn’t improve immediately – you need to allow time to change your processes so they become capable of operating at that targeted level. Performance measurement involves monitoring change over time, and looking for signals about whether it’s moving close enough and fast enough toward the target.
  • Dials and gauges don’t show change over time at all. You are flying blind. You need this [dynamic] context in your performance measures to help you priorities. Because Dials and gauges don’t use this context, they are also incapable of showing you true signals in your measures.
  • Dials and gauges highlight false signals. Dials and gauges have you knee-jerk reacting to routine variation. Check out Stacey Barr post on routine variation and other stats tips for KPIs.
  • There is a better way to show performance measures on dashboards than dials or gauges. We can provide historical context and valid rules for signals of change. Check out smartlines. You will be surprised by seeing there names of Tufte, Few and sparklines. Besides that there are other ideas.

Criteria for KPI visualization

There is a list of criteria for proper tracking, analysis and visualziation of KPIs. Having understood them it will be obvious why gauges and dials should be put into archive as weak use of skeumorphism. Proper approach would be capable to convey both detection and representation on UI of this list:

  • Chaos in performance. First as deviation from predictability, then true chaos.
  • Worsening performance. E.g. degrading productivity or quality or value.
  • Flat plateau. Everything stable and not changing, while change towards growing revenue or growing happiness expected.
  • Wrong pace. We are improving but not fast enough. The target remains out of reach.
  • Right pace. We will reach the strategic target in time.
  • We are there. We have reached the target already.
  • We exceeded expectations. The target is exceeded.

Check out for more comments and details on “The 7 Performance Signals to Look For in Your KPIs” by Stacey Barr.

Conclusion

The concept of dashboard is up to date, powerful and suitable for modernization. The previous posts confirm that with majority of arguments. But the use of dials or gauges is not right design solution for visualization on dashboard. Line charts, control charts, ‘All Data’ charts, smartlines, sparklines, logarithmic charts and other types of graphical representations are still elegant and powerful to conform to seven criteria for KPI visualization. On the other hand they conform to the high-level executive friendly information (see section What exactly to communicate).

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Advanced Analytics, Part III

This post is also about the front-end part, as a conduit for information delivery to the decision maker. Previous two posts are available, it’s recommended to check out the Introduction into the Big Picture and Ruminations on Conveying, Organization and Segmentation of Information for Executives as users.

Big Data? All Data!

It’s time to pay attention to all data available. Personally I see no reasons to limit to big data. All data matters, most recent data matters more, oldest data matters less. It is possible to visualize plenty of data on relatively small space, which is convenient for delivery onto smartphones and wrist-sized gadgets. The rationale is to depict firm details on the most recent/relevant data, the relevancy is determined by the adopted processes. In SDLC it could be a sprint or iteration; in healthcare it could be a period since current admission. The latest measured value matters a lot, hence must be clearly distinguished on top of the other values within the period. The dynamics during the period also matters, hence should be visualized to convey the dynamics.

Previous periods/cycles do matter, especially for comparison and benchmarking to enable better strategic planning. The firm details on dynamics during past cycles are not so valuable, while deviations into both positive and negative directions are very informative. Decision maker knows how to classify the current cycle exceptions, whether something brand new happened or whether business experienced even more severe deviations in the past, and recall how.

Being inspired some time ago by medical patient summaries by Tufte and Powsner I’ve tried to generalize the concept to be applicable to other non-healthcare industries. So far it fits perfectly, allows customization and flexibility, especially for the optimization of the processes, where people usually use control charts on dashboards. Below is a generalized version of the ‘All Data’ chart as a concept.

all_data

Inverted Pyramid

The principle of Inverted pyramid is partially present there, the pyramid is rotated by 90 degrees. Most important information is within the biggest part of the chart, in the center and on the right. It is rather information than data, because id conveys latest value, dynamics during recent cycle, benchmarking against the normal range, indication of deviations (in qualitative way, using only two categories: somewhat and significant). It’s rationale to stay in the range of 10 with the measurements so that they are remember-able relatively easy.

The next narrow part to the left from the sparkline is partially information and partially data. It’s used for comparison and benchmarking, analysis of exceptions, retrospective analysis. It is absolutely logical to fit there 10 times more data, so that if there is a lack of information in the biggest part, the user is able to dig deeper and obtain significantly more facts and reasons, as measurements of the same thing. Hence phase shift means at least 10x growths. With medical patient summaries the ratio was similar: one-two months between admission and discharge vs. one previous year. But 10x is not a hard ratio, it’s more indicative that we need a kind of phase shift to different data, different level of abstraction.

The leftmost narrow part is actually the all and oldest data. It is additional phase shift, relatively to the middle part, hence imagine additional 10x increase and digging to the different level of abstraction again. Only exceptions marked as min/max are comparable between all parts. Everything else constitutes the inverted pyramid of making the information out of raw data.

Cap of the pyramid: Vital Signs

I think the cap of the information pyramid requires special conceptualization. ‘All Data’ is attractive tool to deliver project/process vital signs for executives and other managers (decision makers), they could be compressed even more. Furthermore, the top five-seven measurements could be stacked and consumed all together. That increases the value of the information synergistically, because some indicators are naturally perceived together as juxtaposition of what is going on.

Specific vital signs for business performance and SDLC process optimization were listed in details in my previous post Advanced Analytics, Part II. Here I will only mention them for your convenience: productivity, predictability, value and value-add, innovation in core competency, human factor and emotional intelligence/engagement. Those are ‘the must’ for executives. They could be stacked as vital signs and consumed as integral big picture.

vistal_signs

Of course we can introduce normal range there, ticks for the time tracking, highlight min/max… The drawing represents the idea of stacking and consumption of executive information of SDLC project/process performance in modern manner. You could critisize or improve it, I’ll be thankful for feedback.

There are two dozens of lower level operational indicators and measurements. Some of them could be naturally conveyed via ‘All Data’ concept, others require other concepts. I am going to address them in next posts. Stay tuned.

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Mobile EMR, Part III

This is continuation of previous posts Mobile EMR, Part I and Mobile EMR, Part II

We’ve met with Mr.Tufte and demo’ed this EMR concept. He played with it for a while and suggested list of improvements, from his point of view.

‘All Data’ charts

Edward Tufte insists that sparklines work better than dots. It is OK that sparklines will be of different sizes. It is natural that each measurement has its own normal range. Initially we tried to switch the charts to the lines, but then we rolled back. Seems that we should make this feature configurable, and use sparklines by default. But if some MD wants dots, she can manually switch it in app settings.

Partially our EMR concept has been switched to sparklines – for display of Vital Signs. Below is a snapshot:

Vital Signs

One more thing related to the Vital Signs, we did great by separating on the widget on top, and grouping them together. It adds much value, because they are related to each other. It is important to see what happened to them at each moment. Our approach, based on user testing, appeared to be a winning one!

Space

Current use of the space could be improved even more. First reason is that biggest value of that research was keeping ‘All Information’ on single screen. Human eye recognizes perfectly which type of information is needed. All space is tessellated into multiple locuses of attention. Then human eye locks the desired locus and then focuses within that locus. Second reason is iPad resolution. We can squeeze more from retina resolution without degradation of usability (like size of labels and numbers). It is possible to scale to the newspaper typography on iPad, hence fit more information into the screen estate.

Genogram

This confirms the modern trend to genetics and genetic engineering. Genogram is a special type of diagram, visualizing patient’s family relationships and medical history. In medicine, medical genograms provide a quick and useful context in which to evaluate an individual’s health risks. Many new treatments are tailored by genotype of the patients. E.g. Steve Jobs’s cancer was periodically sequenced and brand new proteins where applied, to prevent disease spread. All cells are built from the proteins, reading other proteins as instructions. This is true for the cancer cells. Thus if they read instructions from fake proteins, then they can not build themselves properly. We like this idea immediately, because its value is instant and big, its importance is as high as allergy. Below is sample genogram, using special markers for genetically influenced diseases.

Sample Genogram

There are other cosmetic observations which will be improved shortly. We continue usability testing with medical doctors. More to come. It could be Mobile EMR on iPhone. Stay tuned.

UPDATE: Continued on Mobile EMR, Part IV.

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