- Junta Nakai is the VP and global head of financial services and sustainability at Databricks, a $38 billion big data startup.
- He argues inflation makes operational efficiency a core priority for companies to preserve margins.
- Companies will become much more discerning on how they spending money, especially on IT.
The window of tolerance for companies that merely talk about AI is closing. In today’s inflationary environment, it is crucial for companies to deliver profits by leveraging data and AI in their operations or in their products and services.
Companies that don’t make the transition to AI quickly will be at a great disadvantage relative to those that do.
The collective global economy is currently experiencing an inflationary environment not seen for decades. In the US inflation hit 8.5% in March of 2022a level of inflation not seen for over 40 years.
In response to the inflationary pressures, central banks around the world are poised to raise interest rates. The
Higher rates slow down the economy because it makes borrowing or raising money (the cost of capital) more expensive. When this happens, every decision to spend money comes under more scrutiny.
Inflationary and high rates environments change corporate decision making in three ways:
- CEOs must protect margins
- When costs of capital are high, the opportunity costs are high
- Time lines are shortened
All of these trends were recently highlighted by Uber CEO Dara Khosrowshahi in an email to employees. “It’s clear that the market is experiencing a seismic shift,” he said, before making several additional points that illustrate the points above.
CEOs must protect margins: “We will be even more hardcore about costs across the board.”
When costs of capital are high, the opportunity costs are high: “They see how big the TAM is, they just don’t understand how that translates into significant profits and free cash flow. We have to show them.”
Timelines are shortened: “Now it’s about free cash flow. We can (and should) get there fast. There will be companies that put their heads in the sand and are slow to pivot. The tough truth is that many of them will not survive.”
Just like how technology lifted us from the depths of Covid, technology will likely prove to be the antidote to any upcoming economic malaise.
As Khosrowshahi mentions, companies that are slow to pivot may not survive a high inflation, high rates, and slower growth economic paradigm.
But agile companies will likely survive this economic landscape, so what makes a company agile?
Leadership, culture and talent undoubtedly play a big role, but Agile companies aren’t solely created through organizational excellence — technology plays a critical role. This is where digitally native companies like Uber have a massive advantage versus legacy organizations.
Digitally native companies have spent years building and perfecting cloud native data platforms that enable them to make smart, data-driven business decisions in changing economic times.
The rest have not and now must make the decision to either build it themselves or to buy a platform that afford them the kind of capabilities that digitally native companies possess.
As timelines shorten, CEOs must make the buy or build decision today.
Innovations like cloud, open source, and AI will streamline costs
While a growing chorus of economists and pundits worry about 1970s-style stagflation, the world today is in a very different place thanks to the innovations in cloud computing, open source software, and Data analytics/AI.
These three innovations can become invaluable tools to protect margins and drive growth even in unfavorable economic conditions.
First, for most companies, leveraging cloud service providers like Azure, AWS and GCP will prove cheaper than owning and managing their own data centers. Leveraging cloud services means you don’t have to build, manage and update your own IT infrastructure. Cloud enables companies to pay for what they use, which means most businesses find cost savings in the cloud especially during times of economic
Second, open source software means companies don’t have to spend money solving common challenges. Today, there are open source consortiums in many sectors where companies come together to collaborate. For example, OHDSI (Observational Health Data Sciences Informatics) is an organization that open sources health data solutions built to address common challenges faced by
. This means hospital systems, pharmaceutical companies and health insurers can focus on promoting better health decisions rather than recreating the wheel.
Finally, data analytics/AI can automate manual workloads and drive efficiencies required to quickly achieve optimal cost structures. For example, incorporating AI into call centers by using Natural Language Processing (NLP) chatbots can help reduce customer service costs by up to 30%. This single AI use-case can potentially save companies billions given businesses spend approximately $1 trillion a year on call centers.
Data analytics and AI also spurs innovation, which can drive new revenue streams in a slower growth backdrop. For example, Frito-Lay leveraged data analytics and AI during the pandemic and was able to deliver a new direct-to-customer service within 30 dayscreating a new revenue stream for the company in uncertain times.
AI is critical for CEOs who want the upper hand
For CEOs that need to protect margins, make tough decisions on where to spend, and operate within shorter timelines, technology decisions on cloud, open source, and AI will take on critical importance.
Ultimately, whether or not a company possesses these capabilities could be a key source of competitive advantage in a vastly different economic paradigm. CEOs must make strategic technology decisions that enable data analytics and AI quickly across the enterprise.
If the period of low rates and high growth that characterized the last decade are truly gone, simply put, cloud, open source, and AI become “must haves,” no longer just “nice to haves.”
Junta Nakai is VP, Global Head of Financial Services and Sustainability at Databricks, a $38 billion big data startup.