John Caddell’s Reading Journal: Morten Hansen’s “Collaboration” (book review)

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by John Caddell on 2 November, 2009 – 21:49


I’ve finished a few books recently but am a bit behind on reviewing them. My kids have started documenting their books in reading journals that help them with reading comprehension. To add a bit of variety (and to make sure I’m not getting lazy), I’m going to use the reading journal format for this week’s reviews.

Collaboration: How Leaders Avoid the Traps, Create Unity, and Reap Big Results,” by Morten Hansen. 2009: Harvard Business Press, 231pp.

When did you read it? September-October 2009.

Subject: A study of collaboration in business; when it is and when it is not appropriate, and best practices for successful collaboration.

Did you like it? How many stars would you give it (1-5)? 4 (thankfully I don’t have assigned reading… I won’t be writing about any 1-star books here!)

Summary: Hansen has spent his academic career studying how corporate groups collaborate, effectively and ineffectively. This book sums up a number of studies he has worked on with various companies over the past 15 years. First, Hansen discusses obstacles to collaboration – including the warning that not all collaboration is good collaboration. In other words, when the costs of collaboration (communication, coordination, negotiation, etc.) outweigh the benefits. This frequently happens when businesses lacking key synergies are combined via merger.

The bulk of the book is devoted to discussing what Hansen calls “disciplined collaboration.” He discusses four collaboration barriers – not invented here, hoarding, search (inability to find the insight you need), and transfer (inability to put others’ knowledge to use), and three “levers” to promote collaboration: “unify people, practice T-shaped management, and build nimble networks.”

These are practical suggestions and, on their own, not revolutionary. But to me seeing these three levers together as requirements for successful collaboration was distinctive and valuable.

Favorite quote: “Paradoxically, the emphasis on performance management over the past decade has created what Harvard Professor Leslie Perlow calls a ‘time famine’ at work. As people are pressured to perform, they feel that they don’t have the time to help others; reasonable requests for help are seen as burdens that put them behind in their own work. So people are faced with a trade-off – to do their own work (but not help others), or to help others (but get less work done).” p.55

Was it similar to anything you have read before? There are echoes of the recent book “Senior Leadership Teams” which takes up the question of how to get groups of senior executives, who naturally work to drive results from their own groups, to collaborate – another application of the “T-shaped management” approach.

Will this book end up on your bookshelf or in the library donation pile? The bookshelf. Collaboration is an important subject and I don’t have any books that deal with that as a main topic. Plus it’s good.

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Listening to Shop Talk Podcast: Roberto Verganti on his excellent “Design-Driven Innovation”

Post inspired me to read Roberto’s Verganti book. May it inspire you to read it or at least grab the concept!

I still like it after rehearing!

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Roberto Verganti’s book “Design-Driven Innovation” is one of the best business books of the year. It discusses the methods certain companies use to create products with radically new meanings, offering customers something they never realized they wanted and generating long-term competitive advantage and outsized profits as well. In this podcast, Professor Verganti discusses the ideas behind the book and how it applies to companies like Apple, BMW, Artemide, and Harley-Davidson.

For more information, visit the book’s companion website.

Podcast: Roberto Verganti on Design-Driven Innovation (mp3, 39:41)


0:35 What is the “meaning” of a product?

6:00 The meaningfulness of the iPhone

13:50 The role of “interpreters” in Design-Driven Innovation

19:50 Relationships between companies and interpreters

23:45 What is the CEO’s role in Design-Driven Innovation?

30:00 How much of the CEO’s time is required?

33:25 More resources on Design-Driven Innovation

Related post:
Review: “Design-Driven Innovation”

[Theme music: “Up the Coast” from West Indian Girl’s CD “4th and Wall”]

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Customers Are Talking: Retailer Zara Constructs, connect and compacts

Great, great post found about how retailer ZARA made a constructs that enables them to act fast, efficient and effectively. A living proof that a construct does not always imply heavily investments in technology. Keen and eager people are the keys to success!

Artist Talia Chetrit

Artist Talia Chetrit


by: John Caddell

Andrew McAfee’s blog is a great place to learn about how businesses can gain competitive advantage by their use of IT. But yesterday he took a left turn and discussed business situations where data crunching is not helpful to decisionmaking, and I loved it.

In “When Information is NOT the Answer,” McAfee takes issue with Don Sull’s assessment of fashion retailer Zara’s “fast fashion” approach, at least when it comes to data-driven decisionmaking. Writes McAfee:

Sull stresses that “Zara’s business model demands good information,” which is certainly true. But my work with the company (see this Sloan Management Review article and this case study) revealed something I found fascinating: 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.

McAfee further explains the difference he sees between Zara and other retailers’ use of information:

The decisions about which clothes should to go which stores at what time(s) are probably the most important decisions made by any large apparel retailer. Most chains make them by collecting large amounts of daily sales data from stores, combining it with other hopefully relevant information, then applying a variety of statistical techniques to generate a forecast – a quantitative prediction about what will sell. This forecast is used to push the ‘right’ items – the ones predicted to sell — over time to each store.

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.

This seems sensible enough, and it also seems logical that as the business world gets more and more turbulent more and more supporting data will be required. This data will need to be acquired, analyzed, shared, and interpreted with ever-greater velocity, requiring ever-bigger computers, ever-faster networks, and ever-more-quantitative decision makers.

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.

I think this distinction between high-level numbers (what McAfee calls “general knowledge”) and the ground-level view of the customer needs (”specific knowledge”) is very important. In order to gather and understand specific knowledge, it’s necessary to be very close to the customer, “walking the floor and talking to customers and employees.”

Small retailers have always worked this way. When I worked at the local hardware store during high school, each department had a buyer who looked at stock levels, assessed what was selling, took the season into account, and placed orders weekly.

For large retailers, the fashion has been, as McAfee writes, to gather scads of information “Numerati“-style and make central purchasing and stocking decisions. Overreliance on this had a negative effect on one large store: Home Depot.

So it’s good to learn that at least one mega-retailer is using high-level number crunching judiciously, and relying on the folks closest to the customer to set ordering levels at each store. However, I think even they can do better.

As McAfee describes it, Zara “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.” In other words, headquarters’ visibility into the “specific knowledge” in the store is limited to the managers’ forecasts.

I wouldn’t propose changing the ordering process, but I do think Enterprise 2.0 has a role here in sharing specific knowledge more widely. Information in the form of customer or employee narratives (generated by a simple prompt–”what was the most interesting thing that happened today?” or “tell me about your experience today” for example) could be captured at the store level and uploaded to a story-bank accessible to all Zara employees–especially those at a remove from the direct customer experience.

Through tools like commenting, scoring, nudging, sharing, etc., those narratives can inform a much broader base of employees what customers are doing and how they’re reacting to the products on the shelves. [I have been trying out a very cool open-source story-banking tool currently in alpha test that would fit this need perfectly.] This would provide a great service to the company by “bringing the outside in” (John Kotter’s phrase) and enabling all employees to make decisions with much deeper customer insight than they now possess.

This narrative data can supplement the high-level numbers, essentially combining McAfee’s general and specific knowledge to provide better insight into customers–for product, marketing and customer service purposes.

Artist Talia Chetrit

Artist Talia Chetrit

Related posts:
John Kotter on corporate change and “bringing the outside in”
A competitive advantage: employees who talk to customers
Time to listen to front-line employees

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