Mandy Steinhardt
A Path to ROI for AI
Mandy Steinhardt
October 18, 2017

A Path to ROI for AI

Consultants evaluating the current state of AI and projecting into the future agree that those who jump most wholeheartedly into cognitive and AI are the companies who reap the most benefits. But how can you champion an AI project, when the risks seem so high and the path to value is unclear?

At PointSource, we engage in a number of steps in order to engage in an AI project. The first two steps are Problem Framing and Data Understanding and Processing. Problem Framing is key to developing a case for ROI and for understanding what depth of impact this project can have on the business.

Problem Framing

While there are a number of approaches you can take to get to a problem statement, such as strategic workshops, customer research and multi-functional brainstorms, here are questions to consider:

  • Do I fully understand the customer (or user/employee) journey for the business? How will my users interact with this technology?
  • What areas of my business or operations suffer from a bottleneck, If relieved could it unlock revenue and potential?
  • Are there aspects of the business that have become increasingly overwhelming for employees to manage?
  • Do we have repositories of data that could provide insights if we had time to examine them? Disparate legacy systems, or a single connected data architecture?
  • How is the industry, the customer and the workforce changing in the next ten years? An increasingly temporary, global and independent workforce.

Heart of the Business

Don’t limit yourself to thinking about chatbots and voice commands. According to McKinsey in their report “Artificial intelligence: The next digital frontier?”, AI early adopters have found the most success when applying it to operations that lie close to the heart of the business. Innovating close to the core results in transformations that impact not only automation and efficiency but total productivity and revenue. To find those opportunities, you need to examine the journeys of both your customers and employees to uncover areas where interactions and processes can be improved, reinvented or increased in scale. Early adopters implemented multiple different types of AI tools across multiple departments.

Alignment and Culture

In order to get started with AI you need some internal alignment, but in order to fully succeed, you need complete alignment across the entire C-suite. Each functional group must be on board and ready to examine how these capabilities can impact the way that they do business. These leaders also must be expected to champion the education of teams on what cognitive will mean for your business and how they can welcome rather than fear the resulting changes in how they work.

With centralized impact on your business, you’ll experience a ripple effect through your key processes and internal culture. Will your employees excitedly accept decision support services, or will they look upon this concept with distrust? We can hardly blame someone for regarding a machine suspiciously that is attempting to do what people have been working independently on their whole careers. However, the better your leaders can envision how this technology may impact the shape of your organization, the better you can plan to transform your team’s work and develop proactive AI strategies.

Multi-Year ROI

The AI projects that truly aim to transform the nature of your business and industry require a full-scale investment and time to mature into transformative profits. But you can make the case for a tiered return on investment in stages. Phase 1, proof of concept and data gathering, could entail discovery, implementing proof of concept and tracking material improvements during the first six months to a year. Phase 2 you can expect improvements in your modeling, efficiencies in execution. Phase 3 you then expect multiplicative return on investment as processes have fully changed to leverage the new technologies.

Moving Forward

When you have successfully identified good opportunities to incorporate AI technology, you can evaluate them against your company’s vision and business goals to determine a good ROI forecast. You’ll know how this technology can aid each impacted team, how it can impact the company’s trajectory, and how soon you can expect impact to productivity, operational throughput and revenue. And, you will understand the costs of different methods of employing the technology and readying your workforce to take advantage of the changes.


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