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December 5, 2022

The Analytics Advantage for Enterprise Operations

Introduction

Today’s enterprises are awash in data, but many do not understand how to unlock the power of data through what we like to call the analytics advantage. Analytics are necessary to discern trends or long-term insight from large pools of data. Without analytics, data is untapped and ultimately wasted. When enterprises use analytics to generate data-driven decisions for everyday interactions and processes, profitability increases along with improved customer experiences. They may still encounter data quality issues and lack of corporate buy-in, but with the analytics advantage, enterprises can provide greater customer support with improved operational efficiencies, long-term growth, and a distinct business advantage.

The Analytics Enterprise

The analytics-savvy enterprise needs a powerful platform to process and deliver critical business insight in real time, with flexible data stores integrated with ready-to-use analytics. But realizing data value is not only limited to the investment in an intelligent platform; it is going beyond the technology to take an integrative approach.1 An organization that sees analytics as a strategic rather than a purely IT-related issue, with executives who take a hands-on attitude toward customer analytics and appreciate their importance is also vital.2 Overall, combining IT investment with in-house expertise, staff skills, and the development of proprietary analysis models is what can make the difference for a firm that wants to be a data-driven, analytics enterprise.

Remaining Data Challenges

IT and staffing investments along with organizational buy-in can take an enterprise far, but other technical obstacles often remain, especially within larger, complex organizations. Some of the most common growing pains that companies can experience in trying to achieve the analytics advantage include:

  • Isolated data silos. It’s hard to get a consolidated data picture in a single organization. Data often resides in different formats across different departments, with different owners making it very difficult to have an accurate, 360-degree view across the entire business.
  • Outdated information/Data quality. Organizations cannot make headway on major initiatives when project data is in question. Staff must be confident that collected data accurately reflects what is happening so that it can be relied on for active and ongoing use. If an enterprise doesn’t address ongoing data quality issues, it won’t be used regularly, much less trusted by all.
  • Inability to analyze and act in real-time. With the challenges of isolated data silos and poor data quality, it is almost impossible to make business decisions that drive a positive business outcome. With new sources, formats, and technologies, critical data can be transformed and delivered in a real-time analytical solution. The expectation is that by 2025, vast networks of connected devices will power and transmit analytical insights, often in real-time, while data generation, processing, analysis, and visualization is transformed by smarter, more ubiquitous technologies.3

Achieving the Analytics Advantage

Once an enterprise can overcome any data quality, processing, or cultural acceptance issues, they can often achieve the highest business return from data-driven, analytical-supported capabilities. The more mature and accurate the analytics, the stronger the performance, with customer acquisition 23x more likely and profitability advantage 19x more likely.4

Final Thoughts

Data is key to any successful enterprise. But the analytics advantage embedded across an organization is what unlocks the true value of data. The analytics advantage can provide enterprise operations with agility, transparency, and important insight into customer engagement, to maximize profitability and large-scale results.


1 “Five facts: How customer analytics boosts corporate performance,” McKinsey & Company
2 Ibid.
3 Ibid.
4 Ibid.

SCOTT PLUMMER

Scott Plummer is Vice President, Product Management at Vitech, and is responsible for driving solutions from ideation through development as well as digital transformation strategy and execution. In addition to roles at Marsh & McLennan and Origami Risk, Scott served 14+ years at Guidewire, the leading provider of P&C Insurance software solutions, leading product efforts for Guidewire’s Claims Management and Digital policy lifecycle products.


BARRY REDFERN

Barry Redfern is Director of Product Management at Vitech and is responsible for driving V3locity platform solutions, strategy, and execution. Prior to joining Vitech, Barry worked at Guidewire for seven years leading product efforts for Guidewire’s persona-centric digital products servicing the full insurance lifecycle.

SCOTT PLUMMER & BARRY REDFERN

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                  Gartner, Magic Quadrant for Life Insurance Policy Administration Systems, North America, Richard Natale, 5 August 2019.

                  Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.