Leveraging algorithms is the only way that merchandising can meet the customer centricity challenges of digital business and the digitalization of retail. Retail merchandisers fight a daily battle to garner and retain customers and to meet rigorous sales, margin and inventory targets. In an oddly similar example, a military pilot, when confronted with a battle situation, cannot optimize just one decision. If a fighter pilot focused only on optimizing fuel, ammunition or speed, the results could be catastrophic. The pilot’s goal is the successful completion of the mission, which requires constant observation, decision and action. Algorithmic merchandising leverages big data to make large and small merchandising decisions with greater accuracy and precision.
The OODA loop was originated by U.S. Air Force Colonel John Boyd, who developed it to define a way to understand how fighter pilots, often in inferior aircraft, consistently won air combat engagements against enemy pilots. What Boyd observed was that winning pilots acted more quickly than their less-successful opponents by cycling rapidly through four states:
- Observe — See the situation and adversary.
- Orient — Size up the vulnerabilities and opportunities.
- Decide — Determine which combat maneuver to take.
- Act — Execute the maneuver.
The OODA loop is similar to the more familiar approach known as Plan-Do-Check-Act; however, the emphasis on observation and orientation is a notable enhancement. With a proliferation of big data, the complexity of multichannel and the speed of change, the loop must spin much faster than the typical merchandising cycle. Algorithmic merchandising represents a transformation enabling the use of big data to drive even simple decisions. As seen in Figure 2, algorithmic merchandising will be comprised by similar loop that will drive automated and manual decision making.
Gartner clients can read more about algorithmic business in this special report Explore Algorithmic Business to Drive Differentiation and Algorithmic Retailing: Merchandising Leads the Way.
Category: customer-analytics data-and-analytics-strategies retail-trends
Tags: algorithms analytics customer-analytics customer-centricity digital ecommerce infocentricity multichannel omni-channel personalization retail smart-machines
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