Dollars From Data: The Value of Emerging Tech
The Fourth Industrial Revolution is here. Disruptive technologies such as blockchain, robotics, and artificial intelligence are opening up countless new opportunities for organizations. This new economy is powered by data – the countless transaction records, customer details, and factory performance information that companies collect via internet-connected devices – so the race is on to use emerging technologies to harness data and identify new business opportunities.
Consider that just last year, more than $15.2 billion in tech investment was directed at artificial intelligence (AI) alone. And companies across industries and geographies are racing to integrate technology solutions into their operations.
Leading companies aren’t looking at technology in a silo. Instead of finding a single use for the tech, they are viewing the Fourth Industrial Revolution as an integral component of business strategy. The payoff can be significant for companies that get it right.
Aon’s Anthony Tennyson, Financial Institutions Practice Group Lead, Risk Consulting, works with organizations on blockchain and explains: “When it comes to game-changing technologies such as blockchain, the greatest reward occurs when the entire business network is transformed. This requires more buy-in, more culture change, and agreement to standards and consensus outside of an organization’s walls.”
Nonetheless, executives can struggle to make sense of what they should be doing right now to position themselves for the next wave of tech-driven innovation. A look at how some companies are deploying these technologies can help light the way forward.
Various factors have fueled the development of emerging technologies – including increases in computing power and consumer adoption. While every business now has access to new technologies, gaining a competitive advantage requires a 360-degree view of how solutions can support – and perhaps even redirect – business strategy.
Embracing Technology and Creating a Data-Driven Organization
Companies across industries are generating huge volumes of data: Sensors on machinery give unprecedented detail on performance. RFID tags and tracking software allow companies to monitor products at every step in the supply chain. And each purchase and customer interaction enable companies to craft more impactful consumer engagement strategies.
Translating this data into business insights requires analysis of huge volumes of data. To truly extract actionable insights at scale, technologies such as artificial intelligence (AI) will be required.
Jeffrey Ma, Former Vice President, Analytics/Data Science, Twitter, explains, “There’s simply more data available than humans can possibly process.”
Before simply deploying AI and robotics within an organization, Ma suggests that data – and the technology needed to harness it – should be integral parts of the company’s culture from day one. Making data the lifeblood of your organization requires a shift in strategy and mind-set. To discover new opportunities, data itself must be embraced. Ma recommends that companies prioritize three areas:
1) Leadership Buy-In.
Insights are only valuable if the enterprise integrates data into its decision-making processes, an exercise that depends on enterprise-wide engagement. Establishing a data-driven culture starts with the C-suite demonstrating a commitment to embracing data and its uses. According to Ma, “The best thing senior management can do is bring in an executive at the C-level and really empower him or her to lead in the space.”
2) Prioritize Problem Solving Over Technology.
If companies buy a new software tool without first determining how it can best serve the business, that investment will likely fall short of the desired impact. Instead, executives must understand the problem first and then determine the specific ways in which technology can help. Ma states, “Technology is not a silver bullet. Business leaders need to understand the problem that is being solved and how technology can help accelerate the process.”
3) Investing in the Right Talent.
So if understanding the business problem comes first, Ma says the second step is “talenting up.” When you have a clear issue you are looking to address or an opportunity to seize, looking at your team and placing those in the right roles to get you there is essential. Understanding who you need but don’t have, however, could be even more important, he adds. For example, analyzing data requires different skills than those who manage the business might have. Having a data scientist work with a business leader, especially in more traditional industries such as construction, manufacturing, and insurance, can help accelerate that organization’s view of data.
Blockchain and Beyond: Identifying Applications for Emerging Technologies
The technologies of the Fourth Industrial Revolution have captured the imagination of executives as well as headlines. For example, the hype around blockchain reached a fever pitch in late 2017. Investors were searching for rising stars, and some companies looked to cash in on the craze.
Although the furor has died down somewhat, understanding how these technologies work as well as their potential applications can provide a much-needed dose of reality.
According to Stephen Mildenhall, an assistant professor at St. John’s University in New York and former global CEO of Analytics for Aon, understanding the purpose of a technology and its possible use cases is critical in making it work for the organization. Take blockchain, which Mildenhall boils down to its simplest form: blockchain is a database able to be accessed by multiple users. What makes blockchain a potentially game-changing technology is its ability to address three key issues: data integrity, validity, and security.
As more data is produced and data security and privacy concerns continue to make headlines, Mildenhall considers blockchain a possible solution: “This technology offers innovations to address integrity, validity, and security concerns.
Looking at the insurance industry in particular, Tennyson notes that from consumer to carrier, each member of the network could update data in real time. Before such widespread adoption is possible, however, he notes the importance of proofs of concept within an organization. “When scaling something with the opportunity to change an entire business network such as insurance, small wins within an organization are important to secure resources that allow the technology to move outside an organization’s walls.”
Scaling Technology Across an Organization
When bringing new technology into an organization, Tennyson points out that it’s not just IT’s responsibility. Leading organizations prioritize cultural change and ensure that pilots include the entire business. “For executives, the hardest part is finding the business challenge or the part of the value chain that they want to transform and then coordinating with all participants to develop a solution that meets their needs.”
In Tennyson’s experience, a three-step process can help companies begin to integrate technology into their operations better:
1) Problem-solve first.
Look for specific issues that technology might be able to address.
2) Ensure organizational readiness.
Engage key stakeholders within any value chain looking to be transformed. For technologies such as blockchain, readiness of the entire business network is essential.
3) Act on data.
Enable teams and leaders to make decisions on the data that is being produced and analyzed.
Along with transforming a business, more data can also improve a company’s risk profile. Tennyson explains, “With greater certainty around the data and proper analysis, organizations can make better and more informed decisions.
Since most companies are still in the early stages of adopting emerging technologies, business leaders are only likely to discover the most transformative applications through several more years of testing and experimenting. That doesn’t mean that organizations can take a wait-and-see approach. Rather, all executives – not just the CTO or CIO – would do well to have substantive discussions about their current issues and pain points, their organization’s access to data, and which emerging technologies have the greatest potential to elevate their performance. Such actions can start to bring clarity to a fast-moving, complex business environment.