How CEOs Can Stay Relevant in the Age of AI

PG

Peter Guagenti

CMO

How CEOs Can Stay Relevant in the Age of AI

The most important new skills for business leaders are not what you might think.

You’ve read the headlines. Data is the new oil; it’s the new currency; data capital can create competitive advantage. We also hear, over and over again, that machine learning (ML) and artificial intelligence (AI) are the future.

Few will dispute that these things are true, but the trite language masks a deeper challenge.

Data must be collected, analyzed, and acted upon in the right way and at the right time for a business to create value from it. ML and AI are only as powerful as the data that drive them.

In this world, big companies – which may throw away as much data in a day as a startup will generate in a year – should have a significant competitive advantage. However, new approaches are needed to move forward effectively in the age of ML and AI. And the new approaches all start with the data itself.

To build and maintain a successful business in today’s insight-driven economy, business leaders need to develop a new set of skills. We outline what we believe those skills are below.

skill-1-a-drive-to-find-key-data-and-make-it-usefulSkill #1: A Drive to Find Key Data and Make it Useful

Business leaders need to be on a mission to collect and (more importantly) expose to their organizations all of the data that might create a competitive advantage.

We don’t always know exactly what data or insights might be the ones that will allow us to break away from the pack until after we have analyzed and acted on that data, then measured the results and repeated the cycle, over and over.

Business leaders need to encourage collecting as much data as possible in the day-to-day operations of the business, with a particular eye towards where your organization has advantages or challenges. Make sure that the data is not simply collected, but stored in such a way that your teams can easily access, understand, and analyze it.

“Big data” was a great start to enabling the future of our businesses, but what we need today instead is “fast data” – data made available to everyone, to drive fast insight.

skill-2-the-ability-to-create-a-culture-of-constant-analysis-and-actionSkill #2: The Ability to Create a Culture of Constant Analysis and Action

As the French writer Antoine de Saint-Exupéry stated, “If you want to build a ship, don’t drum up people together to collect wood and don’t assign them tasks and work, but rather teach them to long for the vast and endless sea.”

This adage applies to becoming an insight-driven business. Data is not insight, and insights are not outcomes.

What we seek in collecting and analyzing data is to identify and carry out the actions that will accelerate and transform our business. The best way to leverage data for creating competitive advantage is to encourage a culture of inquisitiveness, of always asking “the 5 Whys” – a series of “why” questions that take us to the root of what’s important, and why.

Compel your teams to constantly look for ways to not just gather and share insights, but to look for ways to turn insights into immediate actions that add value to the business. Innovations such as ecommerce product recommendations, dynamic pricing based on demand, or sensor-based maintenance are all insight-driven innovations that have arisen in the last decade or so and that have generated dramatic competitive advantage.

ML and deep learning – the most practical form of AI currently available to business – accelerate this process. You can use them together to test multivariate alternatives, to vary assumptions and audiences around your current performance, to help you maximize the value of the insights that you find and implement today, and then to help you take your insights to another higher level.

skill-3-the-insight-to-choose-the-right-tools-and-technologiesSkill #3: The Insight to Choose the Right Tools and Technologies

The agile movement does not get nearly enough credit for the transformative effect it’s had, and continues to have, on business. But a business can only be agile with the right tools and technologies, and the ability to use them to drive action and change.

It’s no surprise that, up to this point, most of the companies and leaders that are making the best use of data to drive their businesses are digital natives – think Google, Facebook, Uber, Airbnb, et al. They have done this by applying the agile mindset of software development to data architecture, data engineering, and data-driven decisioning.

While the large digital players may have leapt to the forefront in the last 10 years, the traditional enterprise can use its long operational history, its existing volumes of data, and its ability to generate fresh, useful data, to level the playing field and compete effectively in the modern economy.

In order to maximize and utilize these resources, business leaders need to lead the decision making around data infrastructure. The insight-driven enterprise needs the best possible tools and technology to enable fast, flexible, and efficient use of the company’s data. This means shifting the traditional IT mindset from maintaining legacy data infrastructure, overly strict controls, and inflexibility, to one that puts agility first.

Analysts, data scientists, and application developers need access to real-time or near-real-time data sources. And they, and the businesspeople who work with them most closely, need to be empowered to act on that data – be it for rapid decision making or to create insight-driven, dynamic experiences for customers and employees.

This shift requires a new set of tools, processes, and culture that is so critical to the future of the business that business leaders – all the way up to the CEO – needs to ensure that agility is the primary order of the day.

Peter Guagenti is CMO at SingleStore, and is an advisor and a board member for several AI-focused companies. Peter spent more than a decade helping Fortune 500 companies to embrace digital transformation and to use real-time and predictive decisions to improve their businesses.


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