Predictive Analytics in Business: Why Companies Need to Prioritize Prediction

Drawing from real-world experience, here’s why predictive analytics in business is essential for driving innovation, customer satisfaction, and long-term success.

From my earliest working days as a quant creating predictive models for the currencies and commodities markets to my 20+ years of experience in the broader CX industry, I’ve seen that companies with the greatest longevity have one thing in common: they prioritize being predictive. 

These brands have developed a complete (and continuously updating) picture of their customer experience (CX) and employee experience (EX), which helps them understand what’s happening in their broader industries, and how the larger economy and culture landscape are shaping business around the world.

Not only do they have the right insights and tools at their fingertips, but they’ve built true data-centric cultures across their organizations, embedding data-driven decision-making across the entire enterprise.

In his forthcoming book, Priority Is Prediction: Seven Principles for Better Strategies, Decisions, and Outcomes, Greg Kihlström, best-selling author, creator of The Agile Brand podcast, and CX thought leader, not only explains why organizations need to be predictive to better anticipate shifting customer and market trends, but he also shares a compelling framework for how leaders can become predictive by leveraging the right insights, tools, and organizational approaches to harnessing data.

The top factors accelerating the need for predictive capabilities

Major trends, such as digital transformation, the rise of AI and machine learning, the shift to remote and hybrid work models, the growth of e-commerce, and an increased focus on personalization, sustainability, supply chain resilience, and innovation, have fundamentally transformed the business landscape. There’s never been a more urgent need for companies to invest in predictive capabilities.

Why predictive-capable companies have a competitive advantage

Robust predictive solutions, skills, and practices are essential for navigating today’s rapidly changing business environment. They enable organizations to move with agility and adapt in lockstep with the kinds of disruptive cultural, economic, and consumer shifts that are always unfolding.

By leveraging the growing volumes of data and advancements in technology available, brands can make informed decisions in direct response to evolving market demands faster than ever before. As a result, these companies have the potential to anticipate and react to trends as they’re emerging, capitalize on new opportunities as they’re developing, maximize operational efficiencies, mitigate risks, inspire innovations, elevate customer satisfaction, and, thanks to these efforts, drive sustainable growth and long-term success.

The seven principles of predictive prioritization

Greg’s book lays the foundation for what organizations need to do to embrace the power of prediction throughout the course of doing business. He does this by explaining what he calls “seven fundamental principles of predictive prioritization,” which include building the capacity for prediction, getting wise with data, creating strategies that see around corners, adapting and evolving, choosing resilience over rigidity, balancing risks with boldness, and advancing with agility. 

Fundamental to these approaches Greg recommends is what Medallia helps the best brands in the world do: bring together signals from across sources to shape customer and employee strategies for stronger financial outcomes. The companies we work with are at the forefront of unlocking the potential of bringing together data from disparate sources, including economic, cultural, customer, and employee insights. 

But gathering the right inputs and analyzing them contextually is only the first step. The most successful brands are focused on building the right culture, one that prioritizes data fluency and establishing a disciplined approach to regularly reviewing and applying learnings based on timely insights. 

The risks of not being predictive

Companies that fail to adopt predictive analytics in business and don’t apply data-driven decision-making practices across the organization are more likely to operate with inefficiencies and deliver poor experiences for customers and employees, leading to greater customer and employee dissatisfaction and, ultimately, turnover. 

How Medallia enables companies to be predictive

Over the past 15 years, Medallia has partnered with the world’s leading brands to help them realize the full potential of predictive analytics in business to improve experiences and increase critical KPIs, like customer loyalty and retention. 

Companies at the head of the maturity curve are taking advantage of Medallia’s capabilities to forecast what might happen, rather than look back at what has already happened. Thanks to our platform, they’re able to visualize what’s taking place across their industry in real time, by keeping a pulse on the latest consumer and economic trends, regulatory developments, and customer and employee behavior. 

Be sure to order your copy of Greg Kihlström’s book, Priority is Prediction: Seven Principles for Better Strategies, Decisions, and Outcomes, for step-by-step insights on enabling your organization to become more predictive.