Machine Learning is getting a lot of buzz. I hear questions from our clients as we have successfully implemented it in our trading surveillance tool. We use machine learning to score the likelihood that trading activity is similar to known cases of spoofing, or layering.

Did you catch that? We use Machine Learning for a specific business purpose.

We all read Twitter feeds, blogs, and stories about other applications, tools, and techniques. These include discussions on BlockChain, Algorithmic Trading, Cloud Computing, Agile, and Continuous Delivery to name just a few. Yet, when looking at many of these discussions one sees that the tool or technique will “transform” or “revolutionize” or deliver on some vague all encompassing promise.

All these tools and techniques do have promise. They all have great applications that will meet a business need, however applying them blindly, without forethought is foolish. After all, we know that a fool with a tool is still a fool.

So let’s all take a deep breath and step back to our business analysis side. Here are the foundational questions we should ask before choosing the tools and techniques:

• What is working well with the current solution?

• What can be done better with the current solution?

• Does the tool or technique that we are using still make sense?

• Can we do better with a new tool or technique?

• Will the investment in change bring rewards to the business?

• Will our clients benefit from the change?

• How will we measure the effects of the change?

• What obligations do we need to meet with our risk, security, and compliance teams?

• What mistakes have others made in their implementation that we need to avoid?

Please don’t misconstrue the message here. I love the application of new technology and new techniques. Innovation is often accelerated by new technology and approaches. I have seen huge benefits from innovative technology and methodologies. These tools have helped us achieve business value for our company and our clients.

New tools and techniques need to be applied with forethought. Know your business value and goals first.

New technology or methodologies should not be used simply because they are currently “hot”. My hope is that the application of change is not simply someone being foolish with a new toy.