High Altitude Thinking (We)blog

This page is part of an in-progress commentary by Roger Frye
on High Altitude Thinking: The International Informatics Summit.

Monday, October 28, 2002

11.00 am
Stephen N. David, Chief Information Officer, Procter & Gamble
A Trillion Points of Light: Making the Supply Chain More Efficient

Taylor wrote a paper how to elect a unknown person to Congress. Gave a D.A. the personality of the average voter. (Jim Blanch went on to become governer and an effective politician.) Applied Method 1 to rapid diffusion with Arthur Anderson. Best application was to supply chain modeling. Proctor and Gamble is the leading flag in the evolution of SCM through large data aggregation.

Stephen David says he will cover state of world for consumer products, supply chain, next 12 months, what comes after that?

P&G markets more than 25 brands in over 70 countries. Employ 100,000, headquarted in Cincinnati. Core competencies: understand consumer, technology (27,000 patents) -> best brands -> relationship building.

State of world:

Demographics: unprecedented rate of aging (graphs in developed, undeveloped, Japan). But average age in Latin America is 17.

Markets: average prices falling. Growth in CPQ modest.

Market trends: carpet bombing with information. 4000 messages daily now vs 561 in 1971. Media overload. Need to move from mass communication to segmentation.

Other changes: active swarms of consumers (e.g. anti-GMO), personalized media, internet as medium, more accepting of chaos when needed for innovation, flexible organizational structures.

Mission: improve the lives of the world's consumers. Build consumer relationships. 1st moment of truth -- consumer buy the product, 2nd moment --take home and use it.

Shows chart of an activity system for winning 1:1 relationships. Arrows between lots of circles.

Supply chain: supply-> manufacture-> warehouse-> retail-> consumer. classic --20 years ago, 140+ day flow. 1992 ECR=Efficient Consumer Response, 130 day flow. Emphasis between manufacture-> warehouse -> retail. Must move to no touch. Post B2B.

What comes next: Focus on consumer is boss. Out of stock (OOS) -- 1/3 of time physically in the store, but not on the shelf. Retailer and Vendor Processes Disconnected. E.g shelf size not fit product. Speed to shelf takes 8-26 weeks if POS (point of sale) ever put in place.

Impact of OOS. 11% of sales. You can't win the 1st moment of truth if the product is not there. Need consumer driven supply network.

Example: IAMs sustained product damage when going through delivery system.

Need to drive out all costs that do not deliver consumer value.

Benefits of e-Exchanges: real time web based delivery of product, pricing, promotion .... 24/7 access, lower costs. Fewer deductions and returns and refusals and improved speed to shelf because of new item information availability. Returns involve less-than-truck-load deliveries.

Drive standards between suppliers and consumers.

What comes after What comes next?

3 buckets: Anti-theft $50B, Anti.counterfeit $500B, ID

Use electronic chip to prevent theft. Beijing counterfeits get to US. E.g. shampoos with bugs growing on them.

Universal Source-Tagging System Standard (ePC -- Electronic Product Code)

No gain from consumer standing at the checkout counter.

5 part system for unique ID for every palette, case, and consumer purchase unit.: Cheap chips, agile readers, Savant, PML lnguage, object naming service. Unit test in Jan 2003. ePC chip will cost a nickel and give positive ROI.

Informatics, analytics, simulations will play a key role.

Summary: focus on consumer as boss, open standards enable adoption and highest value creation, productivity increases exponentially as more people use it, business case to get started with ePC now.

QUESTION: not just theft but emergent liberty alliance about how my identity is use. Answer: Agree, can't cram product down consumer throat. example of search capabilities, provide information and let them choose.

QUESTION wanted to see info about demand signals instead of from supply point of view. Answer: we don't have architectures in place to find pure demand signals -- aggregated at several stages with 4 day lag time. Must cut out stages and identify stores.

Taylor says really important because becoming less effective in forecasting demand. A 3rd (4th) moment of truth when consumer becomes loyal user. Predicts a FASB (?).

END

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