Before racing up big data mountain, look around.

Author:Porter, Les

"A journey of a thousand miles begins with a single step." This familiar aphorism by Lao Tse captures an important thought: A successful journey to extract valuable information from "big data" starts with small steps. While there certainly are mountains of valuable data out there, it isn't necessary to grab it all at once.

Despite media proclamations that big data leaders are already miles ahead, it could be perilous to a company's financial health to try too much too soon.

A more faithful translation of the philosopher's words, according to, is "A journey of a thousand miles begins beneath your feet." That wordshift suggests that a successful climb up "Big Data Mountain" starts with the question: What lies beneath your organization's feet?

Before scaling the heights of big data, consider the immediate surroundings. Know where the company stands. Does it sell to a price-sensitive and fickle mass market or to discerning niche customers with unique requirements?

Different product/market characteristics give rise to different decision-making challenges and pace, and thus different data requirements and opportunities. Do customers expect product features to change frequently to fit the latest fads and fashions, or do they place a higher value on durability and timeless quality?

Consider how Zara, LL Bean Inc. and Wal-Mart Stores Inc. differ. Zara focuses on "fast fashion," selling clothes that its fashion-forward customers expect to wear only a few times. Its systems support nimble production, integrated with quick-from-the-stores feedback based on thin transaction data (how many of this size/color shirt sold this week?).

LL Bean's keep-a-customer-for-life strategy focuses on lasting value. Bean learns a great deal about each customer's purchases and interactions with its several selling channels (retail, Web, phone, mail), and over time it uses sophisticated data analytics--a capability developed over several decades.

As far back as the 1980s, Bean sorted its customers into different buckets according to the recency, frequency and average amount of their purchases.

"Beaners" don't brag about big data, yet they have a sophisticated customer relations management (CRM) capability and intensely analyze how each customer interacts with the business.

Walmart's legendary supply chain management initiatives--also with roots in the 1980s--initially worked with a focused set of demand data, tightly integrated with suppliers'...

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