To succeed today, executives must be hyper-aware of their organizations, the ever-changing demands of their customers, and the rapid pace of market disruptions and opportunities.DOWNLOAD THE PDF
Analytics is the only way to capture those insights at the speed of digital business. And that trend will only increase as emerging technologies like artificial intelligence, machine learning and predictive modeling add a new dimension to analytics — and redefine business success.
This was highlighted in new research conducted by Forbes Insights and Cisco, that surveyed C-suite leaders at 207 large enterprises in North America and Europe. More than half of those surveyed believe analytics will be a critical resource for maintaining and growing market share in the months ahead.
[Access to near real-time data] gives businesspeople time to maneuver to improve performance, with special promotions or revision to the sales strategy for an upcoming season.
Melia Hotels International is a large enterprise that understands the importance of analytics. A global chain based in Spain, it uses digital dashboards to show business executives the latest sales figures, along with near-term projections for hotels, restaurants and other revenue streams. “This gives businesspeople time to maneuver to improve performance, with special promotions or a revision to the sales strategy for an upcoming season,” says Carlos Lopez, Melia Hotels’ vice president of business intelligence, management control and investor relations.
Ready access to this information has helped the company significantly boost online sales, which surpassed €500 million in 2017 and now account for a third of Melia’s total sales, up from about 20% two years ago. “Our analytics environment is fueling our e-commerce strategy,” Lopez says.
But the Forbes Insights/Cisco research shows there’s a gap between mature analytics practitioners and companies that are struggling to catch up. The research identified a select group of analytics leaders by aggregating the responses of executives who consider their organizations to be analytics pacesetters in their markets. With mature, enterprise-wide analytics strategies in place, these outliers represented only 16% of the total sample. But they are reaping impressive rewards from their efforts (see Figure 1). Over the past year, they’ve seen significant competitive gains that they attribute in part to their more advanced data strategies.
The contrast between the analytics haves and have-nots provides a cautionary tale for all organizations looking to compete in the future. For example, when asked to rate their organization’s current analytics capabilities, only 8% of C-suite executives overall ranked their companies as leading their competitors, while 39% rated their analytics effort as on-par at best. While the latter group of executives likely hoped for a bigger payoff from their investments, these respondents fared better than others. Most telling is the 42% of companies overall that haven’t seen any impact on their competitive position in their respective industries over the last year.
Although the research data shows only correlation, analytics success suggests higher growth. An impressive 60% of analytics leaders reported revenue growth greater than 7%, while more than a quarter of the analytics elite saw revenues rise more than 15%. By contrast, only 18% and 5% of followers logged similar revenue numbers (see Figure 2).
In fact, those that will spend 10% or more of their annual budget in this area will rise from 18% to 32% through 2018. But analytics leaders and followers prioritize spending differently. Followers will focus much of their spending on traditional technologies, such as business intelligence applications and executive dashboards. These are the basic building blocks of an effective analytics capability.
Analytics leaders, meanwhile, will earmark significantly more money than followers for expanded commitments to AI, machine learning and predictive analytics. It’s important to note, however, that analytics leaders understand that investing more in the analytics tools themselves isn’t enough. Success also comes down to comprehensive, timely and accurate data. As a result, analytics leaders will spend significantly more for modern foundational infrastructure technologies, including intelligent networks that use internet of things sensors for collecting real-time data about customers, production facilities, supply chains and other core operations.
In addition, analytics leaders are achieving the tricky balance between both corporate analytics and departmental data strategies by adopting what some executives call a “hub and spoke” model. This capitalizes on enterprise-wide information collection — think online e-commerce transactions — as well as insights that are most impactful for individual departments and locations, such as foot traffic in brick-and-mortar stores.
Staying competitive in the future will come down to what data you have and how you filter out the noise. From there, success will be determined by how well you're using the information to drive value in the market.
The lessons from analytics leaders are clear: As analytics becomes a core function within successful enterprises, the C-suite must plan and invest to achieve near-term rewards from a comprehensive data strategy, with the ultimate goal of achieving real-time and predictive analytics. “Staying competitive in the future will come down to what data you have and how you filter out the noise,” says Scott Penberthy, director of applied artificial intelligence at Google Inc. “From there, success will be determined by how well you’re using the information to drive value in the market.”
58% of analytics leaders see a correlation between analytics initiatives and a “significant improvement” in their competitive positions
60% of analytics leaders report revenue growth greater than 7%
76% of analytics leaders will expand and/or modernize their underlying IT infrastructure to better support analytics in the coming year
88% of analytics leaders will earmark new spending for intelligent networks
73% and 64% of analytics leaders have invested in and implemented predictive analytics and machine learning, respectively
This report is based on a Forbes Insights/Cisco survey of 207 global executives. Forty-nine percent were from the United States, and 51% from Europe. The executives work in a variety of sectors, including healthcare, manufacturing, finance and telecommunications. All are senior executives, with 51% representing the line-of-business C-suite and 49% representing the technology C-suite.
Respondents who are designated as analytics leaders are those who describe their organizations as analytics pacesetters in their markets, and with an enterprise-wide analytics strategy in place.
The Forbes Insights/Cisco survey found that executives have clear ideas about what analytics can do for their organizations. “The name of the game for marketing is to understand how to best engage with customers across multi-touch, multi-channel situations. And analytics provides us insight for doing that,” says Tobias Lee, chief marketing officer for the legal business at Thomson Reuters. “We have tons of information that gives us a rearview-mirror look at where we’ve been successful or not. Now we are also applying some predictive algorithms to understand how to become more successful in the future.”
When thinking about analytics investments, executives seek a range of tactical and strategic outcomes from improving product and service quality to enhanced satisfaction and retention rates for customers and employees alike (see Figure 3). This shows that analytics has widespread appeal across both customer-facing and internal operations.
We have tons of information that gives us a rearview-mirror look at where we've been successful or not. Now we are also applying some predictive algorithms to understand how to become more successful in the future.
It’s no surprise that data insights have so far had the greatest positive impact on finance and IT. Both are departments that have long collected and analyzed data as part of their core functions. But the Forbes Insights/Cisco survey also found a growing list of other high-impact areas, including operations, sales, HR and marketing. Other business units remain in catch-up mode, with the greatest room for improvements in engineering, distribution, manufacturing and R&D.
“Analytics is becoming both a method to help us transform to keep up with social, economic and competitive changes, as well as one of the things that’s causing us to transform our business,” says Jim Korcykoski, senior vice president and chief technology and information security officer at Nationwide, an insurance and financial services company.
The company is using advanced analytics, such as machine learning, in a variety of ways. This includes scouring large volumes of insurance claims for patterns that indicate potential fraud; this ultimately allows human investigators to focus their efforts more effectively.
Nationwide also relies on analytics to spot current customers who are ready to move to a competitor. “We want to identify those people before they act and perhaps send them offers designed to retain them,” Korcykoski says.
Another large insurance company, London-based Aviva, capitalizes on analytics to micro-segment customers for highly targeted sales and marketing campaigns. “We have millions — in some cases, hundreds of millions — of data points, which we use to uncover clusters of customers in the marketplace,” says Orlando Machado, global director of customer analytics and data science.
This analysis has identified seven broad customer segments and more than 400 microsegments, which Aviva’s propositions development, brand strategy and creative teams use to personalize customer experience (CX) and marketing campaigns. In the process, the company is “busting the millennials myth,” Machado says. “People like to think of millennials as being a well-defined segment of consumers, but we have identified 87 different millennial subgroups, all with different needs.”
Besides age, other factors include affluence, different levels of price sensitivity, affinities to different brands, and those who actively plan for the future versus people who primarily live for today. “All of these factors add much more richness to our understanding of customers as opposed to just saying they are a millennial because they were born within these certain years,” Machado says. In addition to underpinning marketing and CX campaigns, insights about millennials and other customer segments are guiding product development strategies, he adds.
Large manufacturing companies are also becoming more data-savvy to improve performance. “By becoming smarter about what’s the right inventory level to carry, we can improve our cash flow,” says Vince Campisi, chief information officer at United Technologies, a provider of technology and services for the building and aerospace industries.
To do that, the company is using machine learning to identify thorny parts, suppliers or buyers in the organization. For example, algorithms identify buyers who struggle to optimize their inventory levels, leading to expensive expedited deliveries. In addition, these insights look out about 24 weeks to see which parts suppliers are likely to be short of, and then send an alert to the appropriate buyer. “They can override or adjust that advice, but it becomes a starting point for taking action,” Campisi says. “Help like this puts us in a better position to balance our demand curve with what’s realistic to expect from our suppliers. We’re still early in this journey, but we are seeing results that give us a firm belief that these insights can unlock inventory working capital and put us in a position to fulfill customer orders faster.”
[We're] busting the millennials myth. People like to think of millennials as being a well-defined segment of consumers, but we have identified 87 different millennial subgroups, all with different needs.
How can all enterprises benefit from analytics and create a foundation for successfully incorporating advanced tools? The survey and interviews with C-level executives at large enterprises highlight five critical areas that separate analytics leaders from followers.
It’s clear that global enterprises understand the power that analytics can bring to business decision making today, and why data-driven organizations will be tomorrow’s market analytics leaders. The Forbes Insights/Cisco research shows this in the high percentages of executives who have turned to analytics to increase sales and profits, improve product quality and cultivate better customer experiences.
A steady stream of technology innovation is coming both to traditional tools, such as BI and decision-support systems, and to advanced capabilities. AI, machine learning and predictive analytics are rapidly maturing for mainstream business use. Unfortunately, the latest and greatest tools alone won’t help. In fact, the Forbes Insights/Cisco data shows a significant gap between today’s most effective analytics practitioners and less mature organizations. But these analytics leaders offer a valuable model for others, one that combines smart investments in data-analysis technology with four other critical components:
• A balanced “hub and spoke” analytics strategy
• Targeted spending for IT infrastructure modernization
• Cultural and change-management best practices
• Policies for promoting and encouraging widespread analytics adoption
Analytics leaders see compelling results, ranging from impressive increases in sales and profits to their ability to outmaneuver competitors. “Technologies like AI may seem fanciful, but in a couple of years they’re going to be no less mysterious than something as commonplace as an SQL database,” Penberthy says. “So it behooves people to punch through the hype, understand what’s real, and then think about where they can start using data to better drive their businesses. That’s something that everyone can and should be doing today.”
U.S. Firms Overshadow European Counterparts in Key Analytics Areas
However, European executives may need to reevaluate their views in some key areas of analytics maturity. For example, nearly two-thirds of U.S. officials believe it’s vital for stakeholders in analytics initiatives to understand business goals and technology capabilities. Only 35% of European executives rate this level of understanding so highly (see Figure 11). Who’s right? U.S. officials appear to be on to something: 64% of the survey’s highest performers for analytics also rated business and technology expertise as crucial.
However, this continental split may signal more than simply an attitudinal difference about Europe United States Analytics leaders business strategies. European Union executives are also contending with the looming deadline for General Data Protection Regulation (GDPR). The sweeping scope of the privacy and security regulations and the punitive measures enterprises face for non-compliance are impacting decisions about broader data and analytics strategies.
“We have always been absolutely committed to protecting our customers’ data,” says Orlando Machado, global director of customer analytics and data science of London-based Aviva. “Transparency in this area, as required by legislation such as GDPR, is a good thing because we consider it an open contract that we have with our customers to use their information appropriately.”
Whether it’s for regulatory compliance or to promote business goals, European firms have edged ahead of U.S. counterparts in a key category: advanced analytics technologies. Higher percentages of European companies have adopted artificial intelligence, and throughout 2018, they’re planning double-digit increases in other rapidly maturing analytics tools, including machine learning and predictive analytics.
(percentage who answered, "Completely agree")
Business and IT: Not Always in Perfect Alignment
It’s not surprising that line-of-business managers and senior IT staff don’t always agree on analytics policies. After all, each discipline has unique sets of priorities. These differences clearly surface in response to questions about tools and organizational considerations. For example, IT managers understand that accurate analyses need a strong foundation, with nearly half seeing a modern IT infrastructure as a necessity (see Figure 12).
(percentage who answered, "Completely agree")
But LOB managers are better able to look beyond technology to see that analytics won’t flourish without close attention to people and processes (see Figure 13).
(percentage who answered, "Completely agree")
However, there’s one area where the LOB and technology teams are in close alignment—the realization that analytics are a necessary resource for maintaining and growing market share (see Figure 14).
(percentage who answered, "Completely agree")
Going forward, close collaboration between these two groups will help define how quickly and effectively their enterprise will achieve analytics maturity. Understanding where these analytics leaders see eye to eye and where their attitudes diverge is a first step in cultivating successful working relationships.
Forbes Insights and Cisco would like to thank the following individuals for their time and expertise:
Vince Campisi, Chief Information Officer, United Technologies
Jim Korcykoski, Senior Vice President and Chief Technology and Information Security Officer, Nationwide
Tobias Lee, Chief Marketing Officer for the Legal Business, Thomson Reuters
Carlos Lopez, Business Intelligence Consultant and Former Vice President of Business Intelligence, Management Control and Investor Relations, Melia Hotels International
Orlando Machado, Global Director of Customer Analytics and Data Science, Aviva
Scott Penberthy, Director of Applied Artificial Intelligence, Google Inc.
Forbes Insights is the strategic research and thought leadership practice of Forbes Media, a global media, branding and technology company whose combined platforms reach nearly 94 million business decision makers worldwide on a monthly basis. By leveraging proprietary databases of senior-level executives in the Forbes community, Forbes Insights conducts research on a wide range of topics to position brands as thought leaders and drive stakeholder engagement. Research findings are delivered through a variety of digital, print and live executions, and amplified across Forbes’ social and media platforms.
DIRECTOR, ACCOUNT MANAGEMENT
Todd Della Rocca
Kasia Wandycz Moreno DIRECTOR
Hugo S. Moreno DIRECTOR
Alan Joch REPORT AUTHOR
Zehava Pasternak DESIGNER
Ross Gagnon DIRECTOR
Scott McGrath RESEARCH ANALYST
Tibor Fuchsel MANAGER
Serene Lee EXECUTIVE DIRECTOR
Did you like this article?