Book review: “Running Lean”

Eric Ries started it and now everyone is doing it. It wasn’t that long ago that Eric Ries starting writing about the “lean startup”, evangelising a culture of continuous improvement within startups. Ash Maurya has also written a book on this subject called “Running Lean”. Published earlier this year, “Running Lean” offers a lot of practical tips on how to develop products the ‘lean’ way.

What I found most useful about “Running Lean” is the way in which the book focuses on risk. Maurya, founder of a number of startups himself, explains in this book that ‘lean’ is all about eliminating risk. In the book, Maurya highlights that “the way you quantify risk in your business model is by quantifying the associated loss if you’re wrong.” He then goes on to tackle this issue of assessing and prioritising risk from a few different angles:

  1. Thinking about the stage your business is at – Maurya identifies 3 stages of a startup’s existence: (1) ‘problem/solution’ fit – do I have a problem worth solving? Can the problem be solved? And is that solution something that customers want and are willing to pay for? (2) ‘product/market’ fit – have I built something that people want? and (3) Scale – how do I accelerate growth? Answers to these questions can really help one in validating a business model and prioritising product features.
  2. What’s your “unique value proposition”? – It’s easy to get excited about an idea or a feature whilst losing sight of what differentiates your product from existing solutions already on the market. Maurya therefore hones in on the “unique value proposition” (UVP). Ask yourself the question why your product is different and why it’s worth getting attention and buying. The UVP forms a key part of Maurya’s “lean canvas” (see Fig. 1 below) which is a variation on the “business model canvas” by Alexander Osterwalder.
  3. Assess the risk type – One of the things I found most helpful in “Running Lean” is the way in which Maurya distinguishes between three types of risk: (1) product risk – getting the product right (2) customer risk – building a path to customers and (3) market risk – building a viable business. In my experience, determining and addressing such risk types upfront really helps a company in focusing on the key desired outcomes. It also helps to determine the main product hypotheses to test with customers in real-time.
  4. Tackling these risks through experiments – Like Eric Ries, Maurya is a strong believer in addressing risks through experiments. This means that you come up with an assumption or hypothesis and test it in real-time through a “minimum viable product” (MVP). You can feed your findings from such an experiment back into a “lessons learned report”, outlining (1) your original assumptions (‘what we thought’) (2) what you learned (‘insights’) and (3) your next steps (‘what’s next’).
  5. Features must be pulled, not pushed – Another way to tackle risk is by avoiding bombarding customers with features (that they didn’t ask for in the first place). Rather than continuously pushing out new features, Maurya makes a strong case for a simple MVP and only adding new features based on customer feedback or testing insights.

Main learning point: even if you’ve already read Eric Ries’ book on “The Lean Startup” inside out, I still think you’ll find “Running Lean” a very useful book. Ash Maurya provides lot of helpful, practical pointers on how to best reduce the risks related to launching a new product. The idea of ‘learning experiments’ – launching a new product incrementally – is a good way for startups and established business alike to test the market and to get customer feedback. “Running Lean” should thus help businesses in developing their products in an iterative manner, learning and improving along the way.

Fig. 1 – Ash Maurya’s “Lean Canvas”

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Facebook Graph – Can it really take on Google?

With the amount of data that Facebook has on its users and their activities, I guess it came as no surprise when they recently launched Facebook Graph.

One of the first questions raised was whether Facebook is now looking to take on Google when it comes to search. In essence, Facebook Graph generates a variety of results (e.g. people, places, interests, etc.) all based on the social data available through your network on Facebook.

An obvious first comparison would be with Google+ and it triggered to me think a bit more about what Facebook Graph entails and how it compares to Google+:

  1. Facebook uses the data it’s already got – I thought this post on Fast Company explains Facebook Graph pretty well: “Graph Search leverages Facebook’s social data to pinpoint any combination of people, places, photos and interests. It is designed to field queries such as “photos of my best friend and my mom” or “friends of friends who like my favorite band and live in Palo Alto” or “Indian restaurants in Palo Alto that friends from India like.” In essence, all Facebook Graph does is using the social data it already has. In contrast, the launch of Google+ signified a venture into a fairly new area for Google, with it having to build a new social platform almost from the ground up.
  2. Facebook Graph has its (search) limitations – It was interesting that Facebook founder Mark Zuckerberg said that “We wouldn’t suggest people come and do web searches on Facebook, that’s not the intent” at the launch of Facebook Graph. Indeed, Graph is no Google when it comes to web search; searches on Graph are limited to data that are either public or visible to you. Also, as the aforementioned Fast Company article points out; if one of your friends has wrongly labelled a certain picture it’s just a case of tough luck with Facebook Graph.
  3. Different algorithms – Whereas Google’s search algorithms are predominantly based on keywords and links, Facebook Graph takes into social data around “likes” and “check-ins”. Consequently, the search results that Graph returns are likely to be a lot more personalised and authentic than Google’s. As I mentioned under point 1. above, Facebook has an almost endless amount of social data at its disposal which Google will struggle to compete with. Unlike Google, Facebook Graph enables users to search by using combined phrases such as “My friends who like cycling and have recently been to France.”

Main learning point: the main question I asked myself after having done this brief comparison of Facebook Graph and Google (Plus) was: “is it really fair to compare the two?” Google has clearly established itself as a very reliable web search platform, whilst Facebook Graph is clearly concentrating on “social search”. Having said that, I can see Google+ eventually suffering from Facebook Graph, mostly due to Facebook’s head start when it comes to social data. Facebook Graph, however, is currently only available in beta and it might not hit the dizzying heights that Facebook has hit. Facebook users might not sign up to Zuckerberg’s grand ‘one stop shop’ vision and prefer to search through Google …

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