Are your AI and ML efforts paying off? If not, sharpen your axe.
08/03/2021 by Drew Fergus Machine Learning
Yes. There is a lot of buzz around Artificial Intelligence (AI) and Machine Learning (ML), but where is the return on investment (ROI)? No one wants to waste time and money with no benefit, and more importantly, no one wants to do nothing and end up like Sears or Blockbuster! This blog post is intended for those interested in solving real-world problems with emerging tools and technologies but want to avoid the pitfalls of just jumping on the AI and ML bandwagon.
You don’t need a degree in advanced analytics or economics to read and understand this post. Its purpose is to highlight the need for strategic thinking and to ensure you have the right resources in place to make AI and ML work for you. Let me be clear, don’t avoid AI and ML because others are failing. Instead, learn from their mistakes and join those who are thriving from their data-driven, analytical investment.
“There are three kinds of lies: lies, damned lies, and statistics.” That quote is not by Mark Twain, although it has often been attributed to him. Original author aside, it is still a salient point that a wrong conclusion can look very plausible when underpinned by poor analytics.
Unfortunately, wrong conclusions and missed opportunities are commonplace even with all the technical prowess and proliferation of decision-making assets readily available to today’s AI and ML workforce. In fact, it has been estimated that only 10 percent of companies will see an ROI from their analytical efforts.
Oh yeah. Big Time. The companies that are strategic and implement the right resources benefit their shareholders and position themselves for future growth. So how do you avoid the pitfalls and make it into the elite group of companies seeing huge gains from AI and ML?
“Give me six hours to chop down a tree and I will spend the first four sharpening the axe.” Abraham Lincoln- dropping knowledge! Doing analytics right is like a host of other pursuits where investing the time to ask the right questions will lead to a better outcome. Maybe I should clarify, giving the right questions the appropriate amount of time upfront, and giving them an honest and thoughtful response will lead to a better outcome. People aren’t always aware that they are cutting corners during this process but this lack of time and attention in the beginning often leads to AI and ML projects that don’t pay off.
All of your analytic endeavors break down into three main components that all need equal attention, well almost. Your three prong focus should be on the Problem, the Data and the People (PDP). People are always the most important factor for success and always get more attention. Cliché but true, failure here means failure everywhere.
As a starting point, here are a few questions to consider that can make or break your ROI for AI and ML endeavors. Just like sharpening an axe, the nature of this exercise isn’t necessarily difficult or exciting, but the lack of development and commitment here is the biggest pitfall of all.
For a larger look at what to consider first, check out our AI and ML Planning Kick-Starter.
If you are still on the fence about making the transition to a data-driven approach or you are not seeing the ROI you expected, you may need the right trusted partner to get you on the path to success.
Zencos has been delivering data-driven solutions to customers for over 20 years. We are the partner that will help you succeed in the world of AI and ML.