Trust me – it’s not you. Our world really is more unpredictable than ever. Even the best-laid strategies are being disrupted, whether they are focused on the workplace’s culture, technical environment, market dynamics, customer behavior, or business processes. But central to these uncertainties is one constant: an algorithm guiding every step along the evolutionary trail to digital transformation.
“Each company has a predictable algorithm that’s driving its business model,” said Sathya Narasimhan, senior director for Partner Business Development at SAP, on a live episode of Coffee Break with Game Changers Radio, presented by SAP and produced and moderated by SAP’s Bonnie D. Graham. “When we understand how data affects outcomes and bring sensor data online, it’s easier for the infrastructure to process this information to create additional insights,” she explained. Sathya was joined on the program by a panel of thought leaders featuring Darwin Deano, principal at Deloitte Consulting LLP, and Patricia Florissi, global CTO for Dell EMC Sales.
This observation is very telling of the predictive power of algorithms. Think about it: Amazon proposes what should be in your shopping cart. Netflix recommends the next movie you should watch. Google is serving up ads that tug at your heart (and wallet). And all of this wouldn’t be possible without an algorithm running in the background that predicts what people want, how they behave, and what will influence their actions.
Digital technology nears a tipping point – toward enlightenment
Smart business leaders know that tomorrow’s competitive edge requires rapid innovation across their organization today. Machine learning, Internet of Things, artificial intelligence, blockchain, analytics, and Big Data – there are so many choices available. And businesses have a great opportunity now to begin figuring out how to harness and invest in them.
Patricia believes that this reality may soon reach a tipping point as data volumes continue to swell. “We are entering an enlightened age where there is so much data and computing and processing power that we can infer that our quality of life will fundamentally improve,” she observed.
Recent disruption in agriculture certainly proves Patricia’s point. Although the Internet of Things has been around for 20 years, farmers and their suppliers are just starting to capitalize on the generated data because the power needed to process and analyze it has finally arrived. Now, farmers are collecting and analyzing data generated from GPS and sensors buried in the field soil and embedded in farming equipment to improve crop yields and resource use. This is a significant advancement as farmers find new ways to increase food production – possibly by as much as 70% – to keep pace with a global population that is projected to grow from 7.6 billion today to 9 billion by 2050.
Darwin added that technology is now so affordable that the digital landscape is “starting to see patterns emerge, where some archetypes are beginning to develop as the technology matures.”
The predictive power of algorithms and humans drives business outcomes
One of the best examples of the maturing landscape of technology and algorithms is the current state of artificial intelligence and deep learning.
“Artificial intelligence has evolved, especially with deep learning, to teach computers or to help computers automatically learn how we do things and what we do without being told the rules,” Patricia commented. “The more data being observed, the more patterns can be detected and the more accurate the generalization.”
However, Darwin cautioned against heavy reliance on this technology. “We need to protect ourselves against the erosion of basic cognitive skills, which can be an unintended side effect,” he warned. With cognitive technology, people must have rapid interpretation and response, and algorithms may not always be able to satisfy that need. Humans must maintain the cognitive skills required to do this themselves.
Whether employees have the processing speed and full insight they need to make decisions boils down to a company’s willingness to invest in capabilities required to get work done effectively. “I have realized, after spending the last six years assessing developing strategies for various companies, that businesses gain market share and grow faster because of the investments they make to improve the predictive power of their algorithms,” mentioned Sathya.
The future of algorithms: blockchain, humanity, and ecosystems
As technology and processing power become more mature and powerful, new opportunities for digital innovation will inevitably emerge in the near future.
For Sathya, this future hinges on the arrival of blockchain as a mainstream technology. “We are likely entering an environment where we are relying on fewer regulations and less government interference in how businesses work. To ensure that this new paradigm does not undermine the standard of living of people and the society they live in, multiple parties – such as manufacturers, suppliers, financial services, customers, and government – will need to work together in a way that is less intrusive, more efficient and transparent, and trusted and secure.”
Darwin believes that this change will bring about a new renaissance. “We’re talking about humans being replaced by artificial intelligence, machine learning, and the Internet of Things. However, technology automated to the nth degree will actually free us from acting like technology zombies always engaged with smartphones.”
Patricia anticipates that Sathya’s and Darwin’s predictions will eventually bring about an era of optimized ecosystems and innovative models. “Companies that learn how to nurture, cultivate, and enable vibrant ecosystems, platforms, and new business models will be the digital beginners,” she said. “They are redefining how transactions are conducted and the currency used. Ultimately, the ecosystem, cross-education, and cross-pollination will be key to their transformation.”
Listen to the SAP Radio show “Future-Proof Your Business: Digital Solutions Now!” on demand.