Bill Franks's Blog: Analytics Matters

Charts And Graphs Are Like Jokes

Everyone is familiar with the age-old adage that if you must explain a joke after you tell it, then the joke will be a flop. The same principle is true when you put data in front of a live audience, whether with a table, a graph, or a chart. This blog will clarify what seems at-first an unlikely comedic connection.

The Link Between Comedy And Analytics

No matter how funny a joke may be, it will not be funny if someone does not immediately understand what it is that makes the joke funny. Once expla...

An Often-Neglected Data Science Budget Item

It is natural to get excited about the prospect of building and deploying an interesting and high impact new data science process. Unfortunately, you have to also put effort into some less exciting aspects of such an endeavor. One item that is often underestimated and neglected, if not omitted, is ongoing maintenance costs for a new process. This blog discusses why we got away with ignoring process maintenance in the past but also why we can’t get away with it any longer.

Homes And Cars

One of the...

Results Are Not The Biggest Factor In Data Science Success

The most important factor in determining if a given data science project will succeed or fail in a business environment is not the quality of the results. In an ideal world, that would be the case, but unfortunately it isn’t true in the real world that we live in. I know I have some explaining to do with that comment, so read on!

Solid Results Don’t Even Get You Halfway Home

First of all, I’ll make clear that absolutely, positively producing accurate results is crucially important. Every professio...

Embracing Uncertainty: A Lesson From COVID Analytics

We are all painfully aware that there is plenty of uncertainty in the data we analyze and in the results that we generate through data science processes. Most of the time, we focus on removing as much uncertainty as possible in the attempt to provide the single “best” answer to the question we’ve been asked. However, when uncertainty is unusually high, we can serve ourselves and our sponsors better if we embrace the uncertainty instead of trying to fully contain it. In this blog, I’ll provide a ...

Data Science Governance – Don’t Reinvent The Wheel

As data science processes continue to become operationalized and embedded within business processes, the importance of governing those processes continues to rise. While governance has been a major focus for many years when it comes to managing data, governance focused on data science processes is still far less mature. That needs to change. This blog will discuss a couple of distinct areas of governance that organizations should consider.

Governance and Ethics Are Inextricably Linked

When definin...

Struggling With Data Literacy? That’s Great News!

Less than two years ago, data literacy was not something I heard many people in the business world talking about. Recently, it is something that comes up in more conversations than not. In this post, Ill address a few misconceptions about data literacy and then make the case that while it is a challenge, data literacy is actually a great problem to have.

Data Literacy Is About More Than Data

I will start by making clear that the term data literacy is being used in the context of a much broader...

You Often Want Your Models To Be Wrong

A few weeks back, I was in a discussion with some analytics executives when one gentleman made a point that sounded odd at first. He suggested that in many cases we actually want the predictions we make with our models to be wrong, not right. After hearing his explanation, however, I totally agreed with him. This post will explain and illustrate with some examples.

Many Events We Model Target Desired Outcomes

We often think about models in context of trying to achieve something positive and helpin...

Win By Keeping Data Science Simple

Getting too fancy by using complex and layered data science approaches can magnify the issues in data instead of controlling them. This blog will explain why and illustrate with a real-world example that I also discussed in The Analytics Revolution to show that the old rule of keeping it simple fully applies to complex areas like data science.

A Surprising, But Recurring, Pattern

One pattern surprised me when I was first confronted with it. Namely, when building analytical processes that must be ...

The Case For A Chief Data Scientist

The rise of analytics and data science executives has received a lot of attention in recent years. Similarly, there has been substantial focus on the analysts and data scientists who get the work done. Both types of roles are required if success is to be achieved. However, is an important layer missing? I think so and will discuss why and what that layer is in this blog.

Defining the Gap That Exists

In large companies, much focus has been placed at the executive end of the organization. While a C...

97 Things About Ethics Everyone In Data Science Should Know

Every now and then an opportunity comes along that you just can’t pass up. One such opportunity that fell into my lap was when O’Reilly media reached out to me to see if I was interested in partnering on a collaborative book on the ethics that surround data science. For those who know me and follow my work, they have seen me calling for more focus on ethics for several years. I’ve written blogs and papers on the topic, I’ve given many conference presentations on the topic, and I’ve had countless...