A new report by Chicago-based consulting firm West Monroe shows that 69% of C-suite executives are investing in more technology during the current pandemic. The company’s quarterly pulse survey of 150 executives also found that data and analytics platforms are the most common technology to be adopted, with 57% of survey respondents trying the tech in the past six months. A further 21% reported trying artificial intelligence and machine learning.
While the findings may not be surprising given the importance data plays in the digital workplace, it is still not clear what organizations are using the analytics for. Data analytics platforms have always been a key part of the enterprise technology stack and with workers forced to work from home they are even more so now. Here is what's happened since the emergence of COVID-19.
Analytics Are Essential to the Management Toolkit
The speed and level of disruption caused in recent months caught many executive teams on the wrong foot, said Mark McGregor, director of process intelligence for Milpitas, Calif.-based ABBYY. They were forced to make significant business decisions without the data they needed. Furthermore, they realized that traditional business reporting was not providing the insights into how their operations were running.
With staff working from home and customers buying or not buying through their usual channels, the need for better digital intelligence became urgent. Data and process analytics that provide richer information are no longer nice to have. They are essential tools in the management toolkit. "Whether they are seeking to improve operations, remain compliant when working remotely, considering new automation platforms or deploying robots to support staff, they are discovering that digital intelligence helps address all their key pain points as they seek to navigate these uncharted waters," McGregor said.
This renewed interest in analytics is not limited to a traditional business intelligence approach, but based on new approaches that provide real-time insights into operational processes and the underlying structured and unstructured content that supports them.
Related Article: The Growing Importance of Data Management in the Digital Workplace
Get 'Pre-Active:' The Need for Enhanced Business Continuity Planning
Industry-wide indicators such as the major supply chain issues experienced early in the year demonstrated the perils of making business decisions based on incomplete data or data that is not near real-time, said Poornima Ramaswamy, executive vice president of strategic clients at King of Prussia, Pa.-based Qlik, a data analytics company.
"Never has the entire world been impacted at the same time in the same way that required a near 100% business continuity planning (BCP) to kick in across enterprises," she said. "Also, organizations never planned for all their sites to be in BCP at the same time."
More to the point, there is no experience to lean on for such scenarios, especially in such an interdependent, interconnected world. As a result, the only stabilizing asset that organizations and their employees could turn to was data.
To keep up, companies had to modernize information flows, infrastructure and applications. Up-to-date, accessible and accurate data was and still is mission critical. While some business leaders learned firsthand through failure, others observed the challenges and took the “fast follower” route, quickly pivoting to implement comprehensive data strategies of their own.
As many started using data to drive real-time operational and tactical decisions around the supply chain of people, assets and material, organization leaders realized there was a need to create a sustainable platform for the long term. This platform would serve to address ongoing uncertainty and help business adjust as they settle into a more proactive than reactive mode.
“We saw a definite uptick in the reliance on data and analytics programs as many of our customers pivoted to fully embrace a data strategy,” Ramaswamy said. "But we also uncovered an unprecedented level of sharing, collaboration and openness among customers as we all responded to the COVID-19 pandemic."
Companies can better handle future events like a natural disaster or pandemic by being “pre-active” — that is, to both prepare and act. This means preparing scenarios and options and having up-to-date data with triggers acting at the speed of business.
Related Article: Is It Time to Revise Your Business Continuity Plan?
Doing Business With Data Analytics
Digging into how enterprise analytics are being used shows these platforms tell businesses what parts of their website or app customers are spending the most time on, what they are ignoring and which features they are interacting with, said Pieter VanIperen managing partner and founder of New York City-based PWV Consultants.
This information helps businesses cater to customers’ needs by supporting the most used areas first. Data and analytics also help inform business leaders about where their customers are located and demographics which may help tailor features and services.
"Data and analytics platforms can give businesses a ton of information," he said. "Filtering that data is important, ensuring that data is high quality is important, metrics are important, knowing where your data lives is important. The platforms, especially during a time when everything is online, can give businesses more insight and aid in developing or updating systems and processes, features and products that customers and employees both find beneficial."
Technology growth has escalated across all industries during the pandemic. In health care and life sciences specifically, emerging tech and digitalization have increasingly shaped innovation and the pace of change, said Mark Lambrecht, director of the global health and life sciences practice at Cary, NC-based SAS.
The coronavirus pandemic is accelerating technology adoption as health care systems and governments work to slow its spread. Health care providers seek to care for patients safely, researchers work to keep clinical trials on track, and pharmaceutical manufacturers seek to maintain the global supply of life-changing therapies and bring vaccines and treatments for COVID-19 to patients.
AI and advanced analytics play a critical role in helping maximize investments in new tech and mining the most insights from data, wherever an organization is on its digitalization journey. At the STAT Health Tech Summit in September, virtual attendees were asked what technology has been most useful to their organization during the pandemic:
- 23 percent responded “analytics to forecast the pandemic”
- 30 percent reported digital-first communication
"In the coming months and years, we will see the lasting effects of technology innovation born from the challenges of the pandemic,” Lambrecht said.
Related Article: The Role of the CIO in Driving Enterprise Analytics
Augmenting Human Capabilities With AI and Analytics
Now, more than ever, the ability for business users across an organization to discover the hidden stories within the data is every company’s secret weapon. Once the data is in hand, it is up to the user to consider it in a greater context, said Derek Wang, CEO of Charlotte, N.C.-based Stratifyd. At the heart of this approach is a foundation rooted in data, augmented by someone who has interpreted the data within the current economic climate to help shift the narrative.
The ideal is not just injecting artificial intelligence but augmenting human intelligence with the processing power and visualization capabilities that computational analysis tools can offer. In other words, bring the resources of the data scientist to the domain experts such as the marketing team.
This democratization of the data, Wang said, enables those closest to its source to apply their familiarity and intuition to interpretation. With advanced customer analytics tools, product managers and their associates can drill down into vast sources of information for insights that were once overlooked or even unavailable.
"This trend of more and more sophisticated analytics tools that take on the heavy lifting of data analysis will enable teams to drive the marketing bus without the muscles required of a data scientist before the advent of power steering," he said.
Decision-making is a combination of art and science. If organizations let AI handle the legwork, it makes room for more creative, decision-driven and mission-critical jobs, and lets humans artfully craft solutions to pressing issues. "Human creativity is the key to success," said Wang. "We’re just not efficient when it comes to collecting, storing and processing data.”