Smart Data Says What? How to Update Your Digital Strategy Roadmap with AI.

Co-Authored by Jamie Jurgaitis and Doug Longenecker

If everything is AI’d AF right now, what about your company’s data? Shouldn’t you be AI-ing that too?

To that, we enthusiastically say, “YES." It’s an imperative that will create a strategic and competitive advantage for your organization.

But, not so fast.

Why? Because your organization's data lakes are not something you should be jumping into with both feet, just for the sake of bolting on AI. No. Uh-uh. Take a beat and pause.

We recommend a measured, purposeful approach to integrate AI with your company and customer data. The goal is to make sure AI applications for your data are properly identified, prioritized and implemented to achieve strategic goals for the business.

Where and How to Get Started

For a lot of companies, the first step in this process can pose a number of internal and external challenges that make it difficult – even daunting to actually get started.

Here is a quick list of eight key questions you and your team need to talk about, thoughtfully consider and agree on as you prepare for a successful AI/Data integration program:

//         Who “owns” your data, data program? (this is critical to understand and agree on)

//         What is your data governance policy? (Who internally can access your data?)

Use your data to provide context, find correlations and establish causation.

//         What are the privacy regulations based on your industry?

//         How is your data collected and organized? (map out the data pipeline)

//         How is your data stored, protected, secured? (stored on-premise, in the cloud, or a hybrid approach)

//         What’s the quality of your data and when is the data updated?

//         Are their any gaps in the data, poor,

incomplete or biases?

//         How long do you store data? When is the data to old to keep storing?

Making sure everyone knows and understands how your company’s data is procured, curated and being used to improve the business is a critical first step. How these questions are addressed by your team will show where you need to focus attention.  

Be sure to keep this critical point in mind throughout the process, unreliable data used on the front end will create unreliable results. Those very results are what you intend to use to help you make smarter, better, faster business decisions.

Leveraging Your Data with AI

With the tough, initial data conversations and potential issues all worked out, now is the time to get into a deeper data dive. This next step is all about discovering how to make your data work for you, your employees and your customers.

One of the first things you will want to do is determine the problem(s) you need to solve and then prioritizing.

Depending on the size of your organization you may want to start at a micro or macro level. It all depends what will work best for the needs of your business and to some degree your corporate culture. It’s up to you and your team.

Either way, here are the things you need to consider next:

//         What’s the problem you are trying to eliminate?

//         What do we expect? What are the benefits? What can AI do and not do?

//         Who is responsible for developing/continually monitoring the solution?

Data is simply data, until you know and understand how to use it to make better decision.

//         Does your team have a full grasp of the context? (Skills and expertise)

//         Can you find data to show correlation and establish causation? (be careful and mind the gap)

//         What will metrics of success be? Can they be measured? How will you optimize?

//         How does the solution impact employees and customers?

//         Do you have the right AI tools and partners?

//         How will you foster an AI-centric culture?

//         Are there any ethical considerations, including privacy, transparency and bias?

//         How will the team check and verify AI? (Continually learn and evaluate the AI solution)

As you work through this process with your team, we are sure you will develop additional questions that need to be answered. That’s to be expected. Every company is different. Each problem has many possible solutions.

Now You’re Ready to Integrate AI with Your Data

Remember, the job of data is to find correlations and prove causation that improve decision making. The job of AI is to help your data do that better and faster. Your job is to work the process and use the data to determine the best way for your organization to operate more effectively and efficiently. 

It’s not rocket science, but to be honest, most organizations taking this journey find some areas and topics more complicated than others.

As you and your team begin to dip your toes into your data lake feel free to let us know how it’s going. Or feel free to reach out with questions as they come up. We’re always happy to jump on a quick call to help clarify specific situations you may run into.

Get ready for the deep dive into your company’s data.

You’re on your way…