7 min read

52% of companies report return on investment (ROI) from Analytics and AI

I’ve been observing the landscape of the AI area for some time, and I can clearly say that technology has entered our daily business and opened up entirely new development opportunities. If organizations are ready to embed a culture of innovation and dynamism in their actions, they will win. That means making data-driven decisions based on more than just historical data sets. Simulating what-if scenarios and investing in new data and analytics tools should become a natural step in progress. Analytics and Artificial Intelligence (AI) change how we work, interpret things, make decisions, rebuild and develop.

And I’m not making empty promises. There is a number of reports which will confirm my thesis.

According to Deloitte’s annual Insight Driven Organisation (IDO) Survey 2020/2021, more than half of businesses feel confident that new analytics and AI solutions provide a high or exceptionally high return on investments.

The survey was performed globally, but most (58%) of respondents operate in Europe and represent medium and large companies, with two-thirds of them generating annual revenues of USD 100 million or more.

McKinsey proves the same trend in their McKinsey Global Survey from 2019. They show that most executives whose companies have adopted AI report that these solutions have reduced costs (in the areas where they were used) by 44%.

Overall rank from McKinsey’s report shows that 63% of respondents reported revenue increases from AI adoption in the business lines where their companies use AI.

Which business capabilities were the most affected by the positive impact of AI? Mostly marketing and sales, product and service development, and supply-chain management.

How do businesses understand the value of Analytics and AI?

Deloitte survey shows a couple of interesting facts and depicts the change in the companies approach. First, it appears that more and more companies build their success based on analyses supported by artificial intelligence, create strategies that consider such solutions and treat this area as a priority.

  • 32% of all respondents consider analytics and artificial intelligence to be the key to the success of their business.
  • 65% have a formal strategy, although this is not always the case for all business units.
  • 3% believe that analytics and artificial intelligence are not of strategic importance to them or do not know the importance of the strategy.
  • 25% of respondents would prioritize improving data, analysis and AI capabilities over all other competing priorities.

Also, BCG Gamma shows some interesting points of view. For example, according to their knowledge, the ability to learn as an organization, combining together humans and the logic of machines, can give companies a 73% chance to gain financial benefits from AI implementation.

Do companies measure ROI from Analytics and AI?

52% of respondents declared that new analytics and AI initiatives provided a high (40%) or exceptionally high (12%) return on investment, while 30% stayed neutral. So is it a good result or not?

It turns out that companies have a hard time tracking and measuring results. The problem starts at defining measures and then their regular and consistent checking. The vast majority of organizations tend to think and measure analytical performance only as a part of broader solutions and functions to which they contribute, instead of having specific metrics and methods used to measure the analytical return on investment. The survey shows that companies see the problem clearly and point it out as the biggest challenge.

Why does it happen?

The study authors found three main reasons for the inability to demonstrate ROI:

  • The project is not in line with business needs.
  • The project is well-executed, but there is no further adoption in BAU.
  • The project has unrealistic expectations (terms of results, timelines, outputs, user experience).

How to succeed in Analytics and AI?

Advanced analytics and AI are a milestone in making better business decisions. However, that can only happen if organizations

  • make analytics and artificial intelligence a strategic priority,
  • educate employees to understand the tools,
  • promote data as a shared resource across the company,
  • provide the right teams across the company to deliver a solution
  • and have leaders who support, monitor and measure changes to ensure ROI.

BCG Gamma, in their study on AI, also underline necessary steps (below) that organizations should take to win with AI5

According to McKinsey Global Survey, respondents at AI high performers are far more likely than others to say their organizations apply good practices to implement even more AI solutions. So, it’s still a lot to be done among other companies starting their journey with Artificial Intelligence. The above tips may be handy.

Gartner’s insight showing what key benefits organizations can achieve by implementing advanced AI solutions can also be convincing for those wondering whether they should or should not start with AI. So it’s also worth taking a closer look at them:

Final thoughts

Organizations understand the importance of data and analysis. The next step is to understand the barriers and challenges, especially in AI, and to adapt to gain the expected return on investment.

Let’s support this summary with the hint from Gartner’s who pinpoint that by 2024, 50% of AI investments will be quantified and linked to specific key performance indicators (KPIs) to measure return on investment.

It’s not such a distant future – I hope companies mindsets will change, and they will be more willing to organize their businesses for AI investments.

And you? Have you already benefit from introducing analytics and AI initiatives to your business?



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