When Information is NOT the Answer : Andrew McAfee's Blog - The Diigo Meta page

• 06 Aug 09
  

  Driessen Samuel

  informationarchitecture IT knowledgemanagement cio

  • IT’s ability to provide needed information to business decision makers
  • What type of supporting data do we need to make sense of a rapidly changing market? What other information is required to support execution? What organizational, behavioral, and cultural changes will we need to capture the benefits of improved information?
  • 13 more annotations...
  • • These companies track fashion globally, spot emerging trends, and translate them into new products
    • demands good information,
    • Zara succeeds in large part because the company makes comparatively light use of market data and sales information, at least as these terms are commonly understood in the retailing industry.
    • combining it with other hopefully relevant information
    • Each retailer forecasts differently, of course, but I find their techniques broadly similar: they all gather lots of data, analyze it centrally, then use the resulting predictions to determine shipments to stores. In this model, the stores themselves have fairly limited roles: they are expected to record data accurately and send it promptly, then do their best to sell whatever headquarters decides to send them.
    • But Zara, operating in an intensely turbulent environment, does something totally different. The company doesn’t really generate a store-level sales forecast at all. Instead, it relies on its store managers to tell headquarters what they think they could sell immediately at their locations. Headquarters then gets as many of these clothes as possible to the stores as quickly as possible.
    • They rely largely on intuition and experience, on walking the floor and talking to customers and employees.
    • Information technology is still critically important at Zara. The company uses technology to present store managers with a multimedia digital order form, and to transmit completed forms back to headquarters. IT is used heavily to support execution, in short, but not at all to assist with data-based analysis or decision making about getting the right clothes into stores at the right time.
    • ‘data vacuum’ – a lack of aggregated, filtered, and massaged information from throughout the corporation
    • As I wrote here, Zara believes that the relevant knowledge for fast fashion forecasting isn’t general knowledge (the kind that can be digitized), it’s specific knowledge (the kind that can’t)
    • Zara spends almost no time on store-level sales forecasting and other similar kinds of data analysis. Second, it has moved decision making down very low in the organization, because this is where the relevant knowledge is. And third, it gives these decision makers very little market data or other forms of general knowledge.
    • For this decision, what’s the relevant knowledge?  What’s the mix of specific knowledge and general knowledge required to make this decision well?
    • that executives will assume that all or most of the relevant knowledge will be general knowledge
• 20 Jul 09
  

  Adriana Lukas

  Zara's decision making processes start at the shop floor, best place if you ask me! Also, finally someone from business theory space says that sometimes data and analytics is not the best input for decision making.

  retail analytics supply information IT data business

  • But Zara, operating in an intensely turbulent environment, does something totally different. The company doesn’t really generate a store-level sales forecast at all. Instead, it relies on its store managers to tell headquarters what they think they could sell immediately at their locations. Headquarters then gets as many of these clothes as possible to the stores as quickly as possible.

    
    

    What’s more, the store managers are given very few quantitative or analytical tools to help them make their short-term predictions. They rely largely on intuition and experience, on walking the floor and talking to customers and employees.

  • IT is used heavily to support execution, in short, but not at all to assist with data-based analysis or decision making about getting the right clothes into stores at the right time.
  • 1 more annotations...
  • • Zara is obsessed with making good decisions about what clothes to stock, but has configured itself so that people making these decisions operate in what looks like a ‘data vacuum’ – a lack of aggregated, filtered, and massaged information from throughout the corporation. This is because the good information that Zara’s business model requires is not the kind that’s easy to digitally encode, transmit, aggregate, and analyze. Instead, it’s information that comes from watching, talking, and listening, then using the computer between our ears to pattern match, draw conclusions, and peer just a little bit into the future.
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  Marc Buyens

  Andrew McAfee Zara

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