Tag Archives: BI

Advanced Analytics, Part V

This post is related to the details of visualization of information for executives and operational managers on the mobile front-end. What is descriptive, what is predictive, what is prescriptive, how it looks like, and why. The scope of this post is a cap of the information pyramid. Even if I start about smth detailed I still remain at the very top, at the level of most important information without details on the underlying data. Previous posts contains introduction (Part I) and pathway (Part II) of the information to the user, especially executives.

Perception pipeline

The user’s perception pipeline is: RECOGNITION –> QUALIFICATION –> QUANTIFICATION –> OPTIMIZATION. During recognition the user just grasps the entire thing, starts to take it as a whole, in the ideal we should deliver personal experience, hence information will be valuable but probably delivered slightly different from the previous context. More on personal experience  in next chapter below. So as soon as user grasps/recognizes she is capable to classify or qualify by commonality. User operates with categories and scores within those categories. The scores are qualitative and very friendly for understanding, such as poor, so-so, good, great. Then user is ready to reduce subjectivity and turn to the numeric measurements/scoring. It’s quantification, converting good & great into numbers (absolute and relative). As soon as user all set with numeric measurements, she is capable to improve/optimize the biz or process or whatever the subject is.

Default screen

What should be rendered on the default screen? I bet it is combination of the descriptive, predictive and prescriptive, with large portion of space dedicated to descriptive. Why descriptive is so important? Because until we build AI the trust and confidence to those computer generated suggestions is not at the level. That’s why we have to show ‘AS IS’ picture, to deliver how everything works and what happens without any decorations or translations. If we deliver such snapshot of the business/process/unit/etc. the issue of trust between human and machine might be resolved. We used to believe that machines are pretty good at tracking tons of measurements, so let them track it and visualize it.

There must be an attempt from the machines to try to advice the human user. It’s could be done in the form of the personalized sentence, on the same screen, along with descriptive analytics. So putting some TODOs are absolutely OK. While believing that user will trust them and follow them is naive. The user will definitely dig into the details why such prescription is proposed. It’s normal that user is curious on root-cause chain. Hence be ready to provide almost the same information with additional details on the reasons/roots, trends/predictions, classifications & patterns recognition within KPI control charts, and additional details on prescriptions. If we visualize [on top of the inverted pyramid] with text message and stack of vital signs, then we have to prepare additional screen to answer that list of mentioned details. We will still remain on top of the pyramid.

default_screen

 

Next screen

If we got ‘AS IS’ then there must be ‘TO BE’, at least for the symmetry:) User starts on default screen (recognition and qualification) and continues to the next screen (qualification and quantification). Next screen should have more details. What kind of information would be logically relevant for the user who got default screen and looks for more? Or it’s better to say – looks for ‘why’? May be it’s time to list them as bullets for more clarity:

  • dynamic pattern recognition (with highlight on the corresponding chart or charts) what is going on; it could be one from seven performance signals, it should be three essential signals
  • highlight the area of the significant event [dynamic pattern/signal] to the other charts to juxtapose what is going on there, to foster thinking on potential relations; it’s still human who thinks, while machine assists
  • parameters & decorations for the same control charts, such as min/max/avg values, identifications of the quarters or months or sprints or weeks or so
  • normal range (also applicable to the default screen) or even ranges, because they could be different for different quarters or years
  • trend line, using most applicable method for approximation/prediction of future values; e.g. release forecast
  • its parts should be clickable for digging from relative values/charts into the absolute values/charts for even more detailed analysis; from qualitative to quantitative
  • your ideas here

signal

Recognition of signals as dynamic patterns is identification of the roots/reasons for smth. Predictions and prescriptions could be driven by those signals. Prescriptions could be generic, but it’s better to make personalized prescriptions. Explanations could be designed for the personal needs/perception/experience.

 

Personal experience

We consume information in various contexts. If it is release of the project or product then the context is different from the start of the zero sprint. If it’s merger & acquisition then expected information is different from the quarterly review. It all depends on the user (from CEO to CxOs to VPs to middle management to team management and leadership), on the activity, on the device (Moto 360 or iPhone or iPad or car or TV or laptop). It matters where the user is physically, location does matter. Empathy does matter. But how to reach it?

We could build users interests from social networks and from the interaction with other services. Interests are relatively static in time. It is possible to figure out intentions. Intentions are dynamic and useful only when they are hot. Business intentions are observable from business comms. We could sense the intensity of communication between the user and CFO and classify it as a context related to the budgeting or budget review. If we use sensors on corporate mail system (or mail clients), combine with GPS or Wi-Fi location sensors/services, or with manual check-in somewhere, we could figure out that the user indeed intensified comms with CFO and worked together face-to-face. Having such dynamic context we are capable to deliver the information in that context.

The concept of personal experience (or personal UX) is similar to the braid (type of hairstyle). Each graph of data helps to filter relevant data. Together those graphs allows to locate the real-time context. Having such personal context we could build and deliver most valuable information to the user. More details how to handle interest graph, intention graph, mobile graph, social graph and which sensors could bring the modern new data available in my older posts. So far I propose to personalize the text message for default screen and next screen, because it’s easier than vital signs, and it’s fittable into wrist sized gadgets like Moto 360.

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The Power of Paper

Here are ruminations on the real power of the paper and other “two dimensional” surfaces we use to present data or information. Inspired by respectful scientists of visualization since 1960s…

Typical answer from many (all?) of you about dimensions of the paper is 2 (two). Not a big surprise.

Paper sheet, two dimensions

Paper sheet, two dimensions

You see vertical and horizontal axis, what is called width and height. Below is a typical sheet to confirm you are right.

Width, Height

Width, Height

Let’s look at the same sheet more carefully. There is a gradient light/shadow on it. Consider the strength of the light or shadow as a value. It is true third dimension. We’ve got the sheet with three dimensions: width, height and value.

Width, Height, Value

Width, Height, Value

Well, so what? We squeezed three dimensions. What else?
Of course there is opportunity for fourth dimension:) Let’s pay attention to the surface of the paper, represent it as a texture, thus make it applicable for digital visualizations. Texture could be different. Don’t mix it with the pattern. Same texture could be scaled in and out, but it is still same texture. Below is a same sheet with texture as fourth dimension.

Width, Height, Value, Texture

Width, Height, Value, Texture

What else? Is our piece of paper done? No! There is fifth dimension – color. Code something into color and you use five dimensions. Don’t mess up value and color, they are different things. Hence, below is a same sheet with five dimensions.

Width, Height, Value, Texture, Color

Width, Height, Value, Texture, Color

At this point I am sure you are confident that we are still able to use even more dimensions. Here is 6th. Size. The sheet could be of different size. Smaller, bigger. Size also encodes, size does matter.

6 dimensions

6 dimensions

Very good. What else on that piece of paper (or digital picture) is capable to encode? The shape. Different shapes encode different things. Below are samples of the shapes, all with 6 dimensions. Together with shape encoding we are getting 7 dimensions.

7 dimensions

7 dimensions

OK, we are not finished yet. There is still a dimension to use. Guess what? Orientation. The sheet (and digital image) could be oriented differently. Independent of shape or size. Below is example.

8 dimensions

8 dimensions

So here you go – 8 dimensions to use during information visualization. All 8 are applicable for paper and digital designs. Very important for efficient BI designs. How to fit Big Data into single widget? Make information from data. But what if information is big too? Use efficient information modeling to get much much more from the same piece of space. This is design wisdom. Use it. Start from 4-5 dimensions. Continue to 8.

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