Why Analysts Should Do Strategy, Not Spreadsheets

mamta Devi
Sep 8
4 min read

Pricing analysts are among the sharpest minds in retail, yet much of their talent is often wasted on low-value tasks. Instead of shaping strategy, they’re stuck collecting data, updating spreadsheets, and running endless “what-if” simulations by hand. The result? Slow decisions, higher error rates, and missed opportunities in a market where every pricing move counts. In fact, research shows analysts spend nearly 40% of their time just preparing data instead of analyzing it—a huge tax on productivity and profitability.

As retail competition intensifies and shoppers expect smarter promotions, leading chains are realizing that automation isn’t just about efficiency—it’s about freeing analysts to focus on strategy, shopper psychology, and value creation. This article explores why it’s time to move analysts out of spreadsheets and into the strategic heart of pricing.

The spreadsheet tax is real (and expensive)

Data prep eats the week. Recent surveys show data professionals still spend ~38–45% of their time on preparation/cleaning rather than analysis and action. That’s time your competitors are spending on strategy. Predictive Analytics Worldbigdatawire.com
Spreadsheets are error-prone at scale. Decades of research by Raymond Panko finds 1–5% cell error rates in real-world spreadsheets—meaning large models almost certainly contain critical mistakes. In operational spreadsheets, error rates remain stubbornly high even after reviews. panko.comeusprig.org

Figure 1: Spreadsheet Errors Impacting Profit

And when pricing is on the line, even small errors hurt. McKinsey has long shown that a 1% price improvement can lift operating profit ~8%+—and the reverse is also true. Why risk that on fragile files? McKinsey & CompanyMcKinsey & Company

Automation is shifting work from grunt to great

Retailers are systematically removing manual price-change work:

Digital/ESL rollouts at scale. Walmart is expanding digital shelf labels to 2,300 U.S. stores by 2026, after successful trials that cut the time to update prices from hours to minutes. Walmart Corporate News and InformationGrocery Dive
Documented labor savings. Case reports show ESL deployments saving double-digit hours per store per week, eliminating all-night price-change “war rooms,” and slashing paper waste. PricerThe Australian

“A task that took a week now takes minutes — with better outcomes.”

Figure 2: ESLs Improve Retail Efficiency

These aren’t fringe stories. Even amid public debate about digital labels, independent analysis of U.S. supermarkets found no evidence of surge-style price spikes after adoption—while retailers cite efficiency and labor benefits. AP News

What changes when analysts stop doing spreadsheet labor

Faster, smarter promotions: Augmented pricing tools can surface the best promo sets automatically—factoring seasonality, elasticity, and competitor moves—so analysts spend time judging tradeoffs, not assembling them. (Data pros still interpret results; they just start from stronger candidates.) thekeycuts.com
Localized, human decisions: With the basics automated, teams finally focus on store-level nuance—assortment tweaks for neighborhood tastes, better price endings, and messaging that reflects shopper psychology. (You can’t automate empathy.)
From firefighting to forecasting: Always-on models help teams simulate what-ifs before committing—so fewer last-minute price rescues and more calm, confident execution. When every 1% of price matters, simulation beats scramble. McKinsey & Company

Figure 3: Impact of Automation on Pricing Decisions

Concrete examples you can benchmark

Big-box ESL timeline and scale. Walmart’s public plan (2,300 stores by 2026) is a clear signal that large retailers see ROI in automating price updates and shelf tasks. Use this as a board-level proof point for modernization. Walmart Corporate News and Information
Operational hours back to the floor. In practice, retailers report ~12 hours saved per store per week post-ESL and millions of paper tags avoided—time that can be redeployed to merchandising and service. The Australian
Illustrative math for your chain. If automation saves a conservative 4 hours per store per week, a 500-store chain frees ~104,000 hours/year (4 × 52 × 500). Redirect just half of that to price tests and competitor response, and you’ve materially increased decision throughput. (Illustrative calculation.)

Risk, compliance, and customer trust

Concerns about dynamic pricing are valid—and manageable. Policy discussions continue, but independent studies show minimal change in temporary price hikes post-DSL adoption, while the main gains are labor savings and accuracy. Clear guardrails (no surge pricing; transparent unit pricing) preserve trust while unlocking efficiency. AP News

The payoff

Cost & time savings: Fewer hours on tag printing, store walks, and spreadsheet plumbing; more hours on analysis that moves margin. Pricer
Better decisions: Automated checks reduce manual error exposure in your most sensitive models. eusprig.org
Strategic empowerment: Teams spend their week on pricing strategy, testing, and storytelling—not VLOOKUP triage.
Profit leverage: Small, systematic improvements in price and promo mix compound into outsized EBIT impact. McKinsey & Company

Call to action

It’s time to let machines handle the mundane, and let your team focus on making pricing a true competitive advantage.

Why Analysts Should Do Strategy, Not Spreadsheets

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