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September 8, 2018 - June 16, 2020
fivethirtyeight.com website,
What does it mean to compete on analytics? We define an analytical competitor as an organization that uses analytics extensively and systematically to outthink and outexecute the competition.
Among the firms we studied, we found that the most analytically sophisticated and successful had four common key characteristics: (1) analytics supported a strategic, distinctive capability; (2) the approach to and management of analytics
was enterprise-wide; (3) senior management was committed to the use of analytics; and (4) the company made a significant strategic bet on analytics-based competition.
Targets: Organizations can’t be equally analytical about all aspects of their businesses, so they need to target specific business capabilities and functions for the extensive use of analytics.
Analysts: Analytical organizations succeed in part because they hire and train high-quality quantitative analysts and data scientists.
An increasingly common approach to enterprise-level analytics is to establish a chief data and analytics officer (alternatively called a chief data officer or chief analytics officer). The CDAO is a senior executive (often reporting directly to the COO, CMO, or CIO) While this is a relatively new role, Gartner estimates that there are over a thousand CDAOs today; it expects 90 percent of the world’s largest organizations will have one by 2019.
Job descriptions vary, but the CDAO is usually responsible for ensuring that the organization has the data, capabilities (human, financial, technical, and operational) and mindset needed to successfully leverage big data and analytics for competitive advantage.
establishing strategic policies regarding data governance (including data policies and cybersecurity), determining investment priorities to enhance analytical capabilities, developing analytical talent, and building enterprise-wide analytic capabilities.
Charles Thomas, the chief data officer at Wells Fargo, says his team’s “main purpose is to champion the enterprise’s use of insight and action to drive business strategy, reduce risk, optimize performance, and increase value for Wells Fargo’s...
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The CDAO may also head an “analytics hub,” an enterprise-wide, deeply skilled, multidisciplinary team (analysts, data scientists, IT specialists, and data visualization experts) who tackle the most difficult and strategic challenges and opportunities on behalf of the organization.
information-based strategy.”
“In God we trust; all others bring data”
“Do we think, or do ...
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Anyone presenting ideas for initiatives or strategies is pressed for...
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Barclays’s consumer finance organization, for example, had a “five-year plan” to build the unit’s capabilities for analytical competition.
New people with quantitative analysis skills had to be hired, and new systems had to be built. Given all these activities, it’s no surprise that it took five years to put the information-based customer strategy in place.
“yield management” at
Leprino y&e -- project northstar
analytical competitors we’ve studied tend to be relatively high performers.
Analytics or information was not mentioned as one of the firm’s strategic competencies.
The IIA benchmarking suggests that this is the largest group.
By no means have analytics transformed the way these organizations do business. Marketing, for example, may be identifying optimal customers or modeling demand, but the company still markets to all customers and creates supply independent of the demand models. Their analytical activities produce economic benefits but not enough to affect the company’s competitive strategy. What they primarily lack is any vision of analytical competition from senior executives. Several of the firms have some of the same technology as firms at higher stages of analytical activity, but they have not put it to
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They can’t connect demand and supply information, so they can’t optimize their supply chains.
They can’t understand the relationship between their nonfinancial performance indicators and their financial results.
links in greater detail and describe how several highly successful companies have transformed their ability to compete on analytics into a key point of differentiation and lasting competitive advantage.
After conducting a statistical analysis of the data, we found a significant correlation between higher levels of analytical maturity and robust five-year compound annual growth rates.12
Once a firm has established a solid foundation of high-quality transaction data,
its managers are able to shift their focus to using the data and systems for better decision making.
In fact, one of the strongest and most consistent differences between low- and high-performance businesses is their attitude toward, and applications of, analytics
Only 8 percent of low performers valued analytical insights to a very large extent compared with 36 percent of top performers. And while one-third of the low performers in our study believe that they have above-average analytical capability within their industries, 77 percent of top performers believe that. Finally, 40 percent of high performers employ analytics broadly across their entire organization, but only 23 percent of low performers do.
They concluded that “top-performing organizations use analytics five times more than lower performers.
High performers are three times as likely to invest a substantial portion of their technology spend on analytics. In addition, more than twice as many high performers are spending more on investments in analytical human capital through training, investments in people and the use of consultants.
Regardless of the approach, for companies to sustain a competitive advantage, analytics must be applied judiciously, executed well, and continually renewed. Companies that successfully compete on analytics have analytical capabilities that are:
Hard to duplicate.
Unique.
Capable of adapting to many situations.
Better than the competition.
The company’s managers refer to the concept of deaveraging—how can they break apart a category or a metric to get more analytical advantage?
Renewable.
By the time competitors
notice that Progressive has targeted a new segment—such as older motorcycle drivers—it has captured the market and moved on to the next opportunity.
Finance groups, naturally, have long used reports, dashboards and scorecards, and online queries in the course of their work. The problem is that these descriptive analytics applications don’t tell the user anything about underlying patterns in the numbers, and they only describe the past. Finance professionals may experiment with an occasional regression model in Excel, but for the finance function to make advanced analytics a core capability—on the same level as external reporting or the closing process—is quite rare.
Intel started several specific initiatives in the forecasting area, including statistical forecasts of revenue and inventory levels, and prediction of impairments in Intel Capital’s investments.
Over the past decade or so, the biggest advance in management reporting has been the shift from IT delivering structured reports or fairly static scorecards to giving managers unprecedented access to enterprise data.
“We compete on analytics and culture,”
Companies increasingly have the ability to relate their investments in human capital to their returns on financial capital.
There are varying approaches to quantitative HR, including 360-degree evaluations, forced rankings, predictions about attrition, and so forth.
