Engaging Customers as Individuals

This is part 3 of 13 from “Analytics: The Widening Divide,” a report on the findings of the 2011 New Intelligent Enterprise Global Executive Study and Research Project.


In addition to an intense focus on risk, our analysis revealed Transformed organizations pay more attention to understanding and engaging with their customers in new ways (see Figure 8). They appear to be responding more pervasively to a profound market shift, namely the explosion of new customer expectations generated in part by our digital, social and mobile marketplace. Likewise, Transformed organizations are also seizing the competitive advantage created when they understand their customers as individuals and engage them in more “authentic” or personalized ways.

FIGURE 8: Focused on Customers

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Transformed organizations are learning to use customer analytics that yield something better than broad statistical averages. Instead of segmenting customers along two or three dimensions — sales and interactions, for example, or income, age and geography — they are analyzing a broader set of customer dimensions. These dimensions can include everything from transactional patterns to psychographic profiles of how customers prefer to shop, their likelihood of product purchases and their cumulative value to the company. The result is a highly individualized understanding, otherwise known as a “market of one,” making authentic customer engagement possible.9

As one Australian respondent in the financial services industry noted, “As interactions become more electronic and distant from staff interactions, insight to customer behavior and needs is increasingly essential.” Analytical insights and actions help restore the sense of a personal relationship that human tellers once provided, he said.

Transformed organizations are putting analytical insights like these into the hands of customer-facing employees. Two-thirds of them support these employees with insights to drive sales and productivity compared to one-fourth of Aspirational organizations.

Many organizations, for example, are learning to anticipate customer needs by understanding what customers actually do when they go online. Pfizer Inc., a global biopharmaceutical company, has taken this approach. “What’s really changed this past year or so, as we continued to evolve to a digital interaction and multi-channel model, is the sheer magnitude of data we collect directly about our customers. It’s more activity-based,” says Dr. David Kreutter, vice president of the company’s U.S. Commercial Operations. “We’re focusing on discerning patterns early, and using them in a predictive way.” As a result, conversations initiated by representatives are tailored and approved based on these patterns, and consistent with policies to provide the information that busy physicians need and are likely to act upon.

Every organization, regardless of size, industry or market, has an opportunity to benefit from the petabytes of new data being created. The impact of this information surge, of near real-time data and unstructured content, is only beginning to be understood. But the past 12 months have already introduced some startling changes in what organizations are doing, and underscore the growing gap between those who are standing still and those with a sense of urgency to act.

Mastering Analytical Competencies

To achieve analytics sophistication, we found, organizations typically master three competencies: (1) information management, (2) analytics skills and tools and (3) data-oriented culture. We then dug deeper to define the capabilities required to achieve each one (see Figure 9).

FIGURE 9: Analytics Competencies

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To help organizations improve on these competencies, we analyzed the specific capabilities required for each and compared the proficiency levels of Transformed organizations, which have largely mastered the competency, with Aspirational organizations, which lack most of the key capabilities.

Competency #1: Information Management

Companies with a strong information foundation are able to tackle business objectives critical to the future of the entire enterprise. Their robust data foundation makes it possible to capture, combine and use information from many sources, and disseminate it so that individuals throughout the organization, and at virtually every level, have access to it. This ability to integrate information across functional and business silos is a hallmark of Transformed organizations, which are 4.9 times more likely to do this well than the Aspirational group.

The information management competency involves expertise in a variety of techniques for managing data and developing a common architecture for integration, portability and storage. In a world where the quantity of data continues to rise astoundingly, standards for data quality must be established with rigorous consistency across all business units and functions. Is data being extracted from disparate data sources, both internal and external, accurately and thoroughly? Can it be used by multiple business units and functions? Is it compatible with existing processes? Can it be managed in real time, or nearly so?

Information management competency:

The use of methodologies, techniques and technologies that address data architecture, extraction, transformation, movement, storage, integration and governance of enterprise information and master data management.

This competency also involves a rigorous approach to data governance, a structured management approach designed to track strategic objectives against the allocation of analytical resources. Decision makers at every level of the organization can then be confident they have the right information to do their jobs effectively and make informed decisions using analytics to guide day-to-day operations and future strategies.

Transformed organizations effectively manage data: (percent proficient, Transformed versus Aspirational organizations)

Capability: Solid information foundation

  • Integrate data effectively — 74% versus 15%
  • Capture data effectively — 80% versus 29%.

Capability: Standardized data management practices

  • Use a structured prioritization process for project selection — 80% versus 45%
  • Use business rules effectively — 73% versus 39%.

Capability: Insights accessible and available

  • Make information readily accessible to employees — 65% versus 21%
  • Make insights readily available to all employees — 63% versus 16%.

Competency #2: Analytics Skills and Tools

Organizations that deploy new skills and tools for analytics can typically answer much harder questions than their competitors. Which customers, for example, are most likely to opt into high-margin services? What will be the impact of a delivery route change on customer satisfaction and on the company’s carbon footprint? How will specific shortages within the supply chain impact future delivery capabilities? Competency in analytical skills and tools, essential for answering key business questions, can be achieved through internal development and cross-training or external hiring and outsourcing in areas like advanced mathematical modeling, simulation and visualization.

Analytics skills and tools competency:

Enhances performance by applying advanced techniques such as modeling, deep computing, simulation, data analytics and optimization to improve efficiency and guide strategies that address specific business process areas.

Advanced skills and techniques also make it possible to embed analytical insights into the business so that actions can take place seamlessly and automatically. Embedded algorithms automate processes and optimize outcomes, freeing employees from routine tasks (for example, looking for customer records to process a claim or repeatedly recalculating variables to determine the best distribution route). As a result, individuals have time to apply data and insights to higher-level business questions, such as using analytics to detect fraud or finding patterns that yield new customer insights.

One key success factor in achieving mastery of this competency is the creation of analytics champions. Transformed organizations have analytics champions that initiate and guide activities by sharing their expertise to seed the use of analytics throughout the enterprise. These specialists pair expertise with a deep understanding of the business. They are able to provide guidance in getting started with analytics, as well as identifying resources for ongoing support. Without an established internal competency, it’s harder for beginners to recruit needed talent.

Transformed organizations understand the data: (percent proficient, Transformed versus Aspirational organizations)

Capability: Develop skills as a core discipline

  • Have strong analytical skills — 78% versus 19%
  • Have analytics champions — 59% versus 18%.

Capability: Enabled by a robust set of tools and solutions

  • Excel at visualization tools — 74% versus 44%
  • Excel at analytical modeling — 63% versus 28%.

Capability: Develop action-oriented insights

  • Develop insights that can be acted upon — 75% versus 38%
  • Use algorithms to automate and optimize processes — 68% versus 31%.

Competency #3: Data-oriented Culture

In a data-oriented culture, behaviors, practices and beliefs are consistent with the principle that business decisions at every level are based on analysis of data. Leaders within organizations that have mastered this competency set an expectation that decisions must be arrived at analytically, and explain how analytics is needed to achieve their long-term vision.

Organizations with this culture are likely to excel at innovation and strategies that differentiate them from their peers (see case study, BAE Systems: A New Business Model Takes Flight). They typically benefit from a top-down mandate, and leaders clearly articulate an expectation for analytical decision making aligned to business objectives. Transformed organizations, in fact, are nearly five times more likely to do this than Aspirational organizations.

Data-oriented culture:

A pattern of behaviors and practices by a group of people who share a belief that having, understanding and using certain kinds of data and information plays a critical role in the success of their organization.

In these data-driven cultures, expectations are high. Before “giving the green light” to a new service offering or operational approach, for example, leaders ask for the analytics to support it. They express their conviction in the value of faster and more precise decisions by using analytics to guide to day-to-day operations. Employees are confident they have the information to make data-based decisions. They are encouraged to challenge the status quo, and follow the facts in order to innovate. Transformed organizations are more than twice as likely as Aspirational groups to be receptive to new insights.

Transformed organizations act on the data: (percent proficient, Transformed versus Aspirational organizations)

Capability: Fact-driven leadership

  • Open to new ideas that challenge current practices — 77% versus 39%
  • Individuals have data need for decisions — 63% versus 16%.

Capability: Strategy and operations guided by insights

  • Guide future strategies with analytics — 72% versus 15%
  • Guide day-to-day operations with analytics — 67% versus 15%.

Capability: Analytics is used as a strategic asset

  • Use analytics as core part of business strategy and operations — 72% versus 15%
  • Increased use of analytics in the past year — 70% versus 34%.

Each of these three competencies — information management, analytics skills and tools, and data-driven culture — is critical to analytics sophistication. Mastery of these competencies is how Transformed organizations manage, understand and act on data to create a competitive advantage.

References

1. Organizational performance is a self-assessed measure that delves into the organization’s competitive position relative to its industry peers. Respondents are asked to select one option from five choices: substantially outperforming competitive peers, significantly outperforming competitive peers, on par with competitive peers, slightly underperforming competitive peers, or significantly underperforming competitive peers.

2. LaValle, Steve, et al. “Analytics: The New Path to Value.” MIT Sloan Management Review and IBM Institute for Business Value knowledge partnership. October 2010.

3. ibid.

4. IBM Institute for Business Value. “Capitalizing on complexity: Insights from the 2010 IBM Global CEO Study.” May 2010.

5. Corporate Executive Board, “Internal Audit’s Role in ERM,” referenced 21 October 2011.

6. Torok, Robert. “Improving enterprise risk management outcomes.” APQC. 2011.

7. Clanton, Brett. “Chevron stayed busy while idling in deep water: Staying busy while idle – Confronting a deep-water slowdown in the Gulf, Chevron worked to get more from its data.” Houston Chronicle. July 11, 2011.

8. ibid.

9. Teerlink, Dr. Marc and Dr. Michael Haydock. “Customer analytics pay off: Driving top-line growth by bringing science to the art of marketing.” IBM Institute for Business Value. September 2011.

10. Our findings on the two paths are based on response patterns from a representative sample of Experienced organizations using a subset of key questions from our survey.

i.Looking at Robert Bruce’s Two Huge Healthcare Bets,” Guru.com. September 6, 2011. Accessed on October 17, 2011.