How to Create ROI with Advanced Analytics and AI: 5 Steps


Guidance for Data-Driven Teams

Gartner reports that, by 2024, 75% of organizations will shift from piloting to operationalizing artificial intelligence. This is one of many findings reinforcing that the world is barreling toward large-scale implementation of advanced analytics and AI.

While analysts, futurists, and thought leaders readily promote this fact, those of us on the ground floor of implementation know that generalized AI is much easier said than done.

We’ve all seen the VentureBeat stat that 87% of models never make it into production, and while the origins of that statistic are dubious, we also know that the problem does not lie with the models — it lies with the data.

Data infrastructures and ecosystems are extremely complex in nature, and the volume of data continues to grow exponentially, resulting in, well, a bit of a cluster– (no pun intended).

Does Operational AI Even Exist Yet?

When we really dig down into who is efficiently using data and truly operationalizing artificial intelligence and machine learning, it’s essentially Google, Netflix, Amazon, Facebook, Apple, Uber (you know the types) — the companies that have treated data as their most valuable asset — that consider themselves “data” companies at their heart, not applications, software, entertainment, etc.

But even the companies listed above often struggle to productionize new models because their infrastructures are so rigid and complex, data can be so difficult to access, and creating alignment within an organization is tough (office politics, anyone?).

Real-Life Experience in Data, Analytics, and AI

Two of our team members have lived these struggles firsthand — Erica Fowler, PhD, who worked for years as a data analyst and data scientist in enterprise healthcare organizations, and Jamie Pope, a senior technology leader with a broad range of technical knowledge in infrastructure engineering, architecture, consulting, application hosting, design and service delivery.

Erica and Jamie recently led a webinar digging into the 5 keys to success when approaching an advanced analytics or AI project:

How to

 How to Create ROI with Advanced Analytics and AI: 5 Steps

  1. Ensure Business Outcomes are Crystal Clear
  2. Ruthlessly Scope the Project
  3. Keep it Real with Timelines
  4. Staff Appropriately
  5. Understand the Costs – all of them


Continue Learning with these additional resources:


  • Webinar on-Demand: 5 Keys to Creating ROI with AI
    • Watch the webinar on-demand now to learn more about each of these keys and to hear more about the personal experiences our team members have experienced as they’ve led the implementation of advanced analytics and AI initiatives in their previous roles within enterprise organizations.

Watch Now


  • Download White Paper: 5 Keys To Make Your AI Project Successful
    • This White Paper is a master class in artificial intelligence/machine learning implementation that reveals the top 5 strategies for effective AI/ML delivery at any organization.

Download White Paper