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Competing on Analytics

The Idea in Brief

It's virtually impossible to differentiate yourself from competitors based on products alone. Your rivals sell offerings similar to yours. And thanks to cheap offshore labor, you're hard-pressed to beat overseas competitors on product cost.

How to pull ahead of the pack? Become an analytics competitor: Use sophisticated data-collection technology and analysis to wring every last drop of value from all your business processes. With analytics, you discern not only what your customers want but also how much they're willing to pay and what keeps them loyal. You look beyond compensation costs to calculate your workforce's exact contribution to your bottom line. And you don't just track existing inventories; you also predict and prevent future inventory problems.

Analytics competitors seize the lead in their fields. Capital One's analytics initiative, for example, has spurred at least 20% growth in earnings per share every year since the company went public.

Make analytics part of your overarching competitive strategy, and push it down to decision makers at every level. You'll arm your employees with the best evidence and quantitative tools for making the best decisions--big and small, every day.

The Idea in Practice

To become an analytics competitor:

Champion Analytics from the Top

Acknowledge and endorse the changes in culture, processes, and skills that analytics competition will mean for much of your workforce. And prepare yourself to lead an analytics-focused organization: You will have to understand the theory behind various quantitative methods so you can recognize their limitations. If you lack background in statistical methods, consult experts who understand your business and know how analytics can be applied to it.

Create a Single Analytics Initiative

Place all data-collection and analysis activities under a common leadership, with common technology and tools. You'll facilitate data sharing and avoid the impediments of inconsistent reporting formats, data definitions, and standards.

Procter & Gamble created a centrally managed "überanalytics" group of 100 analysts drawn from many different functions. It applies this critical mass of expertise to pressing cross-functional issues. For instance, sales and marketing analysts supply data on growth opportunities in existing markets to supply-chain analysts, who can then design more responsive supply networks.

Focus Your Analytics Effort

Channel your resources into analytics initiatives that most directly serve your overarching competitive strategy. Harrah's, for instance, aims much of its analytical activity at improving customer loyalty, customer service, and related areas such as pricing and promotions.

Establish an Analytics Culture

Instill a companywide respect for measuring, testing, and evaluating quantitative evidence. Urge employees to base decisions on hard facts. Gauge and reward performance the same way--applying metrics to compensation and rewards.

Hire the Right People

Pursue and hire analysts who possess top-notch quantitative-analysis skills, can express complex ideas in simple terms, and can interact productively with decision makers. This combination may be difficult to find, so start recruiting well before you need to fill analyst positions.

Use the Right Technology

Prepare to spend significant resources on technology such as customer relationship management (CRM) or enterprise resource planning (ERP) systems. Present data in standard formats, integrate it, store it in a data warehouse, and make it easily accessible to everyone. And expect to spend years gathering enough data to conduct meaningful analyses.

It took Dell Computer seven years to create a database that includes 1.5 million records of all its print, radio, broadcast TV, and cable ads. Dell couples the database with data on sales for each region in which the ads appeared (before and after their appearance). The information enables Dell to fine-tune its promotions for every medium--in every region.

Copyright 2005 Harvard Business School Publishing Corporation. All rights reserved.

Further Reading


Diamonds in the Data Mine

Harvard Business Review

May 2003

by Gary Loveman

Gaming giant Harrah's CEO Loveman describes how his company uses analytics to win its clientele's devotion and supercharge revenues. Harrah's acquires extensive customer information through a transactional database that records each customer's activity at various points of sale, then slices and dices the data finely to develop strategies for encouraging customers to visit Harrah's casinos regularly. It identifies core customers by calculating their lifetime value, and rewards them for spending more. Thanks to analytics, Harrah's scored 16 straight quarters of same-store revenue growth.

The Surprising Economics of a "People Business"

Harvard Business Review

June 2005

by Felix Barber and Riner Strack

The authors explain how to use analytics to manage your company's human resources more effectively. In "people businesses"--companies with high employee costs, low capital investment, and limited spending on activities intended to generate future revenue--you need to use the right metrics to assess performance. Avoid relying on capital-oriented metrics (such as return on assets or return on equity); they mask weak performance or indicate market volatility where it may not exist. Instead, use financially rigorous, people-oriented metrics--such as a reformulation of a conventional calculation of economic profit--so you're gauging people's productivity. Reward excellent performance through variable compensation schemes, and price products and services in ways that capture a share of the additional value your people create for customers.

Countering the Biggest Risk of All

Harvard Business Review

April 2005

by Adrian J. Slywotzky and John Drzik

This article presents ideas for using analytics to understand and mitigate a particularly grave strategic risk--sudden shifts in customer tastes that redefine your industry. Mitigate this risk by gathering and analyzing proprietary information to detect potential shifts. And conduct fast, cheap experiments to identify attractive offerings for different customer microsegments. For example, Coach wondered whether its customers would remain loyal if it offered trendier styles. It conducted in-store product tests and market experiments to gauge the impact of new pricing, features, and offers by competitive brands. It used the information to quickly alter product designs, drop unappealing items, and create new lines featuring different fabrics and colors. The upshot? Coach retained its traditional fans and attracted new customers.

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