Category Archives: Big Data

179. 2020 I.T. Plans? Lost Luggage Lessons (C*)

American Airlines’ Lost-Luggage, Pain-Removal Solution

On a recent American Airlines trip, I turned on my cell phone as I landed at 10 PM. I got a text from American’s AI-bot alerting me that my checked bag did not make it to my hub-connection flight. There were also links for: filing my lost bag info and desired delivery address; and tracking the bag. Continue reading 179. 2020 I.T. Plans? Lost Luggage Lessons (C*)

178. 2020 Sales Force Plans/Questions (B*)

Selling-Model Stress Fractures?

Recent surveys find that next-gen, B2B, digital-first buyers want only-scheduled-as-needed sales rep calls. They prefer, initially, maximum e-information and real-time e-support: 24/7/365. And, texts about real issues are preferred over “how’s-it-going”, outbound phone calls. Continue reading 178. 2020 Sales Force Plans/Questions (B*)

177. Scary Strategic Questions for 2020 (A)*

The Usual Drill and What Breakthrough-Insight Experiments?

Calendar-year distributors: what’s your planning routine for 2020? Is it forecasts, goal setting and budgets, to beat last year by trying harder? Plus, what big-new-competitive-advantage experiments will you be trying? If you aren’t planning something a bit scary, then you are doing same old stuff in new clothes to get fading results. Continue reading 177. Scary Strategic Questions for 2020 (A)*

The Usual Drill and What Breakthrough-Insight Experiments?

Calendar-year distributors: what’s your planning routine for 2020? Is it forecasts, goal setting and budgets, to beat last year by trying harder? Plus, what big-new-competitive-advantage experiments will you be trying? If you aren’t planning something a bit scary, then you are doing same old stuff in new clothes to get fading results. Continue reading 177. Scary Strategic Questions for 2020 (A)*

175. Melting-Unicorn Wisdom for Distributors

Unicorn Melt-Downs?

Valuations for WeWork, Uber, Blue Apron, etc. have been tanking. They all prove that a company’s business service-cost model can’t spend more costs on a unit of activity than the unit’s margin-dollar content, and then make it up on volume.    

The same economic reality hit many retail dotcoms back in 2000. Remember eToys? In ’99, they were averaging $20 in margin per order while spending an all-in cost of $300 per order for fulfillment.

Continue reading 175. Melting-Unicorn Wisdom for Distributors

174. Doctors Prescribe: “Evidenced-Based Management”

“Data-Driven Decision-Making” vs. HiPPO Wisdom

When decisions are made at Amazon, “the best data and innovation metrics” win. No hearsay, golden-gut, follow the herd, or political self-interest beliefs. The HiPPO (Highest Paid Person Opinion) in the room doesn’t win with suck-ups bobbling in agreement. Continue reading 174. Doctors Prescribe: “Evidenced-Based Management”