The start of a new year is often accompanied by commitments for change and improvement, both business and personal. We’re all striving to innovate, “to introduce something new; make changes in anything established”. In business, this often involves technology. How you approach the introduction of technology could be the difference between realizing true innovation or ending up with a “Dishwashing Robot”.
A friend introduced me to the expression “Dishwashing Robot” as a way of describing what happens when you apply new technology to an old way of doing things. It seems innovative on the surface, but it doesn’t bring true, impactful change to an organization. “Innovation” (e.g. a dishwasher) occurs when you leverage the full potential of new technology to change a process and realize optimal benefits. So my challenge to you, and myself, is to consider how we can change processes in our organizations to maximize the benefits of any new technologies we introduce.
I have to admit right from the start: I am not what anyone would call a neutral observer on this topic. After all, I run a company that builds and sells visual analytics software. I’ve done so for over a decade. It’s in my interest that someone – you, perhaps – be interested in buying that software. I come to these biases honestly and I state them upfront.
Like many senior leaders and executives out there, I’m also trying to do more with less. I want to achieve my business goals with only the most calculated investments. I’m trying to deliver value as quickly as possible and make sustainable choices that will serve my company, and my clients, well over the years to come.
The last week of September had me doing three industry presentations that all shared a common theme, “uncertainty”. Today’s blog will focus on the presentation Uncertainty Considerations for Development Planning Type Curves.
Uncertainty extends through the reservoir, drilling, completions & operations and is compounded by commodity prices. What is certain is that shareholders have little tolerance for production shortfalls. The following image show the reduction in stock price of 8 companies in 2017 that occurred following the announcement of production shortfalls.
Figure 1: Stock price reactions to production shortfalls
I could have easily showed you several companies who hit their production targets and maintained or increased their stock price. While it’s not important to know who these companies are, it is important to know that there are best practices that can help protect you from targeting statistically unachievable results and falling short of your production promises.
I recently read the article Same Stats, Different Graphs which spoke about Anscome’s Quartet, four highly varied datasets that are identical when examined using summary statistics, then took it to the next level with the Datasaurus Dozen by demonstrating how highly varied datasets could produce the same summary statistics.
Datasaurus Datasource: Alberta Cairo