Monday, October 26, 2015

Fundamentals of Pragmatic Data Visualization


Data Visualization (or DataViz as some people call it) is another of the catch phrases people use when talking about business intelligence. However, do you know what it is all about? What does it mean to visualize data? Why do you want to do it in the first place?


Let's take it down to the basics. In today's technology rich world, we are surrounded by data. To make sense of what is around us, we deal with data every minute. Whether it is the traffic lights while driving or a scatter plot showing the relation between profit and revenue; it is all about data. I talked about that in my earlier post "Data Data Everywhere... But Not a Byte of Information". 

So what is data visualization? Well, I define it as "The practice of showing data in a manner which highlights the message and leads to actionable decisions."

Let's dig deeper and identify the key building blocks or data visualization.
 

1. Showing data:
The first obvious step is to decide what data you are going to show and how. The decision can be as easy it as showing it as a table or a complex chart. There are while books written on just this topic, but the crux of all of them is to aggregate your data and show what is relevant to the other building blocks. Adding too much data will muddy the waters and take away from the actionable decision. We will talk more about this in a later post. 

2. Highlighting a message:
The purpose of sharing data is to tell the audience something. Give them a message, tell them about something they did not know... Or knew but did not want to acknowledge... (You know who among the audience are those types, we have all come across those types.) So when you are showing your data you have to keep in mind the message you want to give to the audience and highlight it so it is unmistakeable and clear. Again, keep the message simple... Try to give one message with one visualization... That works the best in most cases. 

3. The actionable decision:
The decision is what you are aiming for from showing your data and highlighting the message. It may not always be the case that each visualization or message will lead to a single decision, so you need to think about collaboration among your visualizations to achieve the final goal

Let's think back at the traffic lights example I shared at the beginning. The lights turn red telling us that there will be traffic from the other side in the intersection (the data). It highlights the data using colors, and we make an immediate decision to stop the car and wait. We all know what might happen if we don't make that decision. Thus the traffic lights are the most basic form of visualization that we see everyday. 

Think about it and use these fundamentals in your next visualization project. Make them truly beautiful works and not just a nice looking painting. And don't forget to write in and share them here. 


Tuesday, March 17, 2015

Why do customers do what they do?

Recently, I was reminded of a passage from The Hitchhikers Guide To The Galaxy. The answer to the question of life and everything is: 42. That in itself is the source of a plethora of questions... but that is another story in itself. 

This got me thinking though about the golden question about customers... "Why do customers do what they do?". Like the age old question about "life and everything", this one also does not have a clear and finite answer. You can pick up a number or a reason from the air, so to speak, and try to explain customer situations to those numbers. I say "try", because they will not always be explainable... many times you will attribute them as "outliers" or "special conditions". 

Bottom line is that, the customer psychology is a very complex being and not something you can define in terms of mathematics or logic. There is a lot of emotion attached to any action that a customer takes. 

Wednesday, June 25, 2014

Traffic Jammed Customer Service

How many of us have endured endless wait times when calling customer service numbers? Or suffered through long lines at a POS counter? Or even waiting for a website to load and log you in for online self service. All of these are cases of "traffic jams" in the customer services of an organization.

Tuesday, June 17, 2014

Data Data Everywhere... But Not a Byte of Information

Someone once said to me that we are generating data from the time we are born. In the life of a person, so much data is generated. Whether it is demographic data or transactional data or analytical data, there is so much of it that we generate every day. Really! You are generating data right now while reading this article. The site has registered you as a visitor... anonymous or recognized, that is upto you really, but the visit is registered into a datastore none-the-less. Depending on which site you visit, there may be information about advertisements and click actions that you perform. Now, I don't want to say that we are all being tracked and this is a conspiracy... it is a fact of life in these times. 

But what happens with this data?

In high school my physics teacher defined data as the "raw form" of information. He said, "Information is useful, but data on its own can't get you anywhere." These words ring so true with the large amounts of data that we encounter every day. 

How do we transform this data to generate actionable information? (or do we?). Well, that depends on the type of data that you are looking at and more importantly, the type of information you want to get. This second one is tricky and I will talk about it in a later post.

I like to divide data into these buckets as it helps to understand where this data can be used and what type of information can be derived from it.

Descriptive (Adjective) Data:
This type is data collected about someone or something. This is like the "adjective" in a sentence. It describes a noun. This would include data like: Name, Address, Phone, Email, Height, Weight, etc about a person. If we were talking a product or service, this data would describe the product or service. For example, the photo of a product can be Descriptive Data. 

This data is a great source for Category Information. It is great to use when we are segmenting information or trying to find relations between many sets of data.

Transactional/Operational (Action) Data:
Like the name says, this data is about an action or transaction. This can be from an documented operation or from ad hoc transactions. Some examples of this data are: sales transactions, website visits, financial investments, etc. Since these examples about the "what happened" aspects, there is a lot of this type of data out there. While the Descriptive Data does not change a lot, Transactional Data gets created and changed very frequently

This data usually ends up as Measures in reports. Because there is so much of this data, there are different ways to work with it. But that is a story for another post. From the perspective of information creation, this type of data plays the part of describing the action. This data is usually summarized in some way during the information creation process.

Analytic (Strategic) Data:
Analytic Data is the twilight between data and information. It is so close to information that many people use just the analytic data as the definition of information. The fact we call it data means that it is still in its raw form. I like to explain this type as data about the relation between descriptive and transactional data. A very basic example of this would be the something like "teenagers spend more than 60% of their time in front of computers". You can see how this can easily be confused as information. In some way, it is information if you are looking for only this level of transformation. 

However, to become truly strategic, analytic data talks again in "aggregations" of relations. We talk about relation between categories (from descriptive data) and measures (from transactional data, or sometimes descriptive data as well). The true information is derived from transforming these relations to real-world trends which can help make decisions. Now, you can make a decision based on the example I gave above as well... but strategic decisions are often not that straight forward. So I term this still as data rather than "information".

Predictive (Potential Action) Data:
Now, Predictive Data is unique in the sense that it is about transactions that "may" happen. This data is not yet a "fact" it is still a "theory" of an action that can happen. Given the human nature of wanting to know the future, this is the type of data that is most sought after. Again, this can be easily be confused with information as you could possibly make decisions based on this data. 

Technology today has come a long way and quite accurate algorithms can be found that can predict actions based on trends in the market. 

It is quite evident that there is a lot of data that is generated these days (a phenomenon that some have come to call "Big Data"). However, the challenge that I see today is the transformation of this data into actionable information. Until you sit down and sieve through the data and transform it, all that data is useless. It is like sitting in rubber boat in an ocean without a drop of water to drink, hence the title of this post. 

Any reporting or data visualization initiative should always focus on transformation of the data into information that can be consumed and is relevant. Get rid of all the clutter and noise, data is the most important part of any piece of information.

Think about it... and share your thoughts... I would love to hear them. 

Thursday, April 17, 2014

Customers Are Like Children... Really?

My oldest turned 3 a few months ago. I was reflecting on how she has grown and her behavior changed over the years. Well, lets say that parenting has become challenging as years go by. As I pondered over the principles of parenting that are commonly known, I came across the notion of thinking of a customer in the same light as your "child".

Before I start, let me say I am not in any way talking about customers being children and thus being treated like them. What I am indicating is that there are stark similarities between parenting strategies and what we can apply to customer management.

First, lets look at the similarities in customer behavior and children (those of you who are parents should be nodding your heads as you read on. )

Thursday, November 14, 2013

Value is in the Eyes of the Customer

The Subjective Theory of Value states that value of a product or service is based on the subjective importance of it to an individual. You can read more about the details and economic theory behind this on the link here.

Lets look at this theory in the light of customer relationships. There is evidence all around us that the value of certain relationships is different from customer to customer. Where one will value a social network presence of an organization more than visiting their physical office, others will have a different opinion.

Tuesday, November 5, 2013

Making Customers Smile

A lot of us know that we do our best work when we are happy. If there is stress or tension, we generally either try to avoid the situation or choose the least challenging avenues to get the work done. Those are not always the best pieces of work, they are generally just mediocre.