Category: Technology

My product management toolkit (38): discovering opportunities and solutions

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As product people we all know how enticing it can be to take an idea for a product or feature and simply run with it. The number of product teams I come across that will straight away test a specific idea without understanding the problem or opportunity it’s trying to address is plentiful. This observation is by no means intended as a criticism; I know first hand how easy it is to get excited by a specific idea and to go for it without contemplating any other ideas.

Teresa Torres – probably one of the best product discovery coaches I know – observes that “we don’t examine our ideas before investing in them” or “our solutions don’t connect to an opportunity or our desired outcome at all” (you can find Torres’ observations in her great article here). To solve these issues, Torres has come up with the “Opportunity Solution Tree” framework:

 

 

Taken from: Teresa Torres, Why This Opportunity Solution Tree is Changing the Way Product Teams Work, https://www.producttalk.org/2016/08/opportunity-solution-tree/

 

Torres argues that “good product discovery requires discovering opportunities as well as discovering solutions.” Product people are problem solvers most and foremost, and Torres encourages us to start with the problem first and I like the definition of what constitutes a problem by the late David H. Jonassen that she refers to:

 

“A problem is an unknown that results from any situation in which a person seeks to fulfil a need or accomplish a goal. However, problems are problems only when there is a “felt need” that motivates people to search for a solution in order to eliminate discrepancies.”

 

This problem definition by Jonassen made me reflect on what makes an “outcome” as defined in the excellent book by Joshua Seiden titled “Outcomes Over Output”:

 

“Outcomes are the changes in the customer, user, employee behaviour that lead to good things for your company, your organisation, or whomever is the focus of your work.”

 

Torres talks about how we often will retro fit an idea or solution to a desired outcome, thus failing to both fully understand the desired outcome and explore an appropriate number of potential solutions to that outcome:

 

 

Taken from: Teresa Torres, Why This Opportunity Solution Tree is Changing the Way Product Teams Work, https://www.producttalk.org/2016/08/opportunity-solution-tree/

 

Instead, Torres’ “Opportunity Solution Tree” encourages us to think about the desired outcome first, after which we can explore opportunities to achieve the desired outcome. We can then examine each opportunity and potential solution in more detail, cross-compare perceived value of each solution in a more objective and systemic manner:

Main learning point: A key takeaway from the Opportunity Solution Tree is to consider multiple opportunities and solutions. Whilst this may sound like no brainer, we’re often tempted to zoom in on or commit to a single opportunity or solution straight away, failing to consider its impact on the desired outcome.

 

 

 

 

 

 

Product review: ZocDoc

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I’d never heard of ZocDoc before until I heard someone recently mention it on a podcast. The person in question mentioned something about an app that lets you find your local doctor. Intrigued to learn more, I decided to do a product review:

My quick summary of ZocDoc before using it – I expect a mobile app which lets me find local doctors and book appoints through a single interface.

How does ZocDoc explain itself in the first minute? Unlike other apps, I’m not entirely clear about what ZocDoc is all about. Perhaps I’m slightly distracted by the overlay message which asks me whether I want to accept notifications to “Get important reminders and wellness updates”:

 

How does ZocDoc work? Once I’ve dismissed the notification alert, I can view ZocDoc’s homepage in full. It enables me to search by illness, filter by location and availability:

 

Once I click on “Find” I get a load of results local to me, and available today:

This interface feels intuitive, although I personally could have done without the sponsored result at the top of the screen. This is where ZocDoc’s sorting functionality comes in handy, although I doubt whether I can completely filter out the sponsored results 🙂

Instead, results can be sorted based on “relevance” – although when I do this I start getting results with dentists who aren’t available today (which was one of the original filters) – “distance” and “wait time rating”.

 

Did ZocDoc deliver on my expectations? Yes. The app feels intuitive and does make it easier to book a medical appointment. I nevertheless feel that the app can work harder in terms of enabling customers to sort results, e.g. by price (with and without insurance) and availability. I believe this additional sorting ability will make the results feel even more relevant to the user.

Book review: “Autonomy”

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Lawrence Burns is a veteran of the automative industry. Having worked his entire professional career in the car industry – in Detroit, the birthplace of modern car manufacturing no less – you might expect Burns to be apprehensive about ‘change’ and modern technology. The opposite couldn’t be more true of Burns, since he’s been an advocate for driverless cars for the past 15+ years, starting his foray into this field whilst at General Motors.

In his latest book, “Autonomy: The Quest to Build the Driverless Car – and How It Will Reshape Our World”, Burns and cowriter Christopher Shulgan paint a picture of driverless cars dominating our streets and roads, and having a positive impact on the environment and transportation as a whole. For those sceptics out there who dismiss driverless cars as science fiction, I recommend they read “Autonomy” and take note of the technology and societal developments Burns describes:

Getting started, the DARPA Challenge and Google’s “Project Chauffeur”:

The book starts off with the story of the “DARPA Challenge” in 2004 and how this helped shaped learning and development with respect to driverless cars. Burns gives the reader a good close-up of the experiences and learnings from one of the teams that took part in this challenge. At this first DARPA challenge, every vehicle that took part crashed, failed or caught fire, highlighting the early stage of driverless technology at the time.

Image taken from: https://www.wired.com/story/darpa-grand-urban-challenge-self-driving-car/

Driverless cars are the (near) future:

Bob Lutz, former executive of Ford, Chrysler and General Motors, wrote an essay last year titled “Kiss the good times goodbye”, in which he makes a clear statement about the future of the automotive industry: “The era of the human-driven automobile, its repair facilities, its dealerships, the media surrounding it – all will be gone in 20 years.” There’s no discussion that driverless cars are coming, especially that both car and technology giants are busy developing and testing. When I attended a presentation by Burns a few months agogo, he showed the audience  examples of both self driving cars and trucks:

Image taken from: http://www.autonews.com/article/20170316/MOBILITY/170319877/bmw-says-self-driving-car-to-be-level-5-capable-by-2021

Image taken from: https://newatlas.com/volvo-vera-self-driving-truck/56312/

In “Autonomy”, Burns brings Lutz’ predictions to life through the fictitious example of little Tommy and his family. In this example, Tommy steps into a driverless which has been programmed to take him to school in the morning. Tommy’s grandma will be picked up by a driverless two-person mobility pod to take her to a bridge tournament. Burns describes a world where car ownership will be a thing of the past; people using publicly available fleets of self driving cars instead.

Image taken from: https://www.thenational.ae/business/technology/autonomous-pods-the-future-of-city-driving-1.730283

Together with Chris Borroni-Bird, Burns has done extensive research into the potential impact of an electronic self driven car, looking at metrics such as “total expense per mile”, “cost savings per mile” and “estimated number of parts”. Borroni-Bird and Burns provide some compelling stats, especially when contrasted against conventional cars. Reading these stats helps to make the impact of driverless technology a lot more tangible, turning it from science fiction or future music into a realistic prospect.

Main learning point: “Autonomy” by Lawrence is an insightful book about a driverless future, written by a true connoisseur of the car industry and the evolution of driverless technology.

Related links for further learning:

  1. https://spectrum.ieee.org/cars-that-think/transportation/self-driving/auto-consultant-lawrence-burns-dishes-the-dirt-on-waymo
  2. https://www.youtube.com/watch?v=-pLM-2bxNMc
  3. https://www.youtube.com/watch?v=SJVKY1DtZ84
  4. https://www.forbes.com/sites/greggardner/2018/08/23/an-interview-with-self-driving-visionary-larry-burns-co-author-of-autonomy/
  5. http://www.autonews.com/article/20171105/INDUSTRY_REDESIGNED/171109944/industry-redesigned-bob-lutz
  6. https://lucidmotors.com/
  7. https://electrek.co/2017/01/02/lucid-motors-autonomous-tech-all-electric-sedan-mobileye/
  8. http://www.thedrive.com/opinion/9024/who-is-really-1-in-self-driving-cars-you-wouldnt-know-it-from-navigants-controversial-report
  9. https://news.stanford.edu/2017/05/22/stanford-scholars-researchers-discuss-key-ethical-questions-self-driving-cars-present/
  10. https://www.thenational.ae/business/technology/autonomous-pods-the-future-of-city-driving-1.730283
  11. https://www.wired.com/story/darpa-grand-urban-challenge-self-driving-car/
  12. https://spectrum.ieee.org/cars-that-think/transportation/self-driving/google-has-spent-over-11-billion-on-selfdriving-tech

Book review: “AI Superpowers”

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Dr. Kai-Fu Lee is the chairman and CEO of Sinovation Ventures, a China based tech focused investment firm. Previous to becoming a full-time investor, Lee held positions at Google, Microsoft and Apple. A large part of that career, Lee spent working on data and Artificial Intelligence (‘AI’), both in the US and in China. In “AI Superpowers – China, Silicon Valley and the New World Order” Lee bundles his experiences and insights to describe the progress that China and the US have made and are making in the field of AI.

AI Superpowers contains a heap of valuable insights as well as predictions about the impact of technology power that both the US and China have been racking up. These are the main things that I took away from reading AI Superpowers:

  • US and China, contrasting cultures – Lee starts the book by writing about the contrasts in business culture between the US and China: “China’s startup culture is the yin to Silicon Valley’s yang: instead of being mission-driven, Chinese companies are first and foremost market-driven.” Lee goes on to explain that the ultimate goal of Chinese companies is “to make money, and they’re willing to create any product, adopt any model, or go into any business that will accomplish that objective.” This mentality help to explain the ‘copycat’ attitude that Chinese companies have had historically. Meituan, for example, is a group-discount website which sells vouchers from merchants for deals which started as the perfect counterpart of US-based Groupon.
  • “Online-to-Offline” (‘O2O”) – O2O describes the conversion of online actions into offline services. Ride-sharing services like Uber and Lyft are great examples of the new O2O model. In China, Didi copied this model and tailored it to local conditions. Didi was followed by other O2O plays such as Dianping, a food delivery service which subsequently merged with the aforementioned Meituan company, and Tujia, a Chinese version of Airbnb. Lee also mentions WeChat and Alipay, describing how both companies completely overturned China’s all-cash economy. More recently, bike-sharing startups Mobike (see Fig. 1 below) and ofo which supplied tens of millions of internet-connected bicycles, distributing them across them about major Chinese cities and now across the globe.
  • China catching up quickly in the AI department – Having read the story of image recognition algorithm ResNet, and how its inventors moved from Microsoft to join AI startups in China, I can see how China as a country is quickly catching up with the technology stalwart that is Silicon Valley.  One of these image recognition startups, Face +++, has quickly become a market leader in face / image recognition technology, leapfrogging the likes of Google, Microsoft and Facebook along the way.
  • The four waves of AI – In AI Superpowers, Lee argues that what he calls the “AI revolution” will not happen overnight. Instead, AI will wash over us in four waves: internet AI, business AI, perception AI, and autonomous AI (see Fig. 2 below). This part of the book really struck a chord with me, as it brings to life how AI is likely to evolve over the coming years, both in terms of practical applications and use cases.

Main learning point: I’d highly recommend “AI Superpowers” to anyone interested in learning more about how China and the US are furthering the development of AI and the impact of this development on our daily lives.

 

Fig. 1 – Screenshot of the Mobike bike-sharing app – Taken from: https://technode.com/2016/07/07/mobike-uber/

 

Fig. 2 – The four waves of AI – Taken from: Kai-Fu Lee, AI Superpowers, pp. 104 – 139:

  • First wave: Internet AI – Internet AI is largely about using AI algorithms as recommendation engines: systems that learn our personal preferences and then serve up content hand-picked for us. Toutiao, sometimes called “the Buzzfeed of China”, is a great example of this first wave of AI; its “editors” are algorithms.
  • Second wave: Business AI – First wave AI leverages the fact that internet users are automatically labelling data as they browse. Business AI, the second wave of AI, takes advantage of the fact that traditional companies have also been automatically labelling huge quantities of data for decades. For instance, insurance companies have been covering accidents and catching fraud, banks have been issuing loans and documenting repayment rates, and hospitals have been keeping records of diagnoses and survival rates. Business AI mines these data points and databases for hidden correlations that often escape the naked eye and the human brain. RXThinking, an AI based diagnosis app, is a good example in this respect.
  • Third wave: Perception AI – Third wave AI is all about extending and expanding this power throughout our lived environment, digitising the world around us through the proliferation of sensors and smart devices. These devices are turning our physical world into digital data that can then be analysed and optimised by deep-learning algorithms. For example, Alibaba’s City Brain is digitising urban traffic flows through cameras and object-recognition.
  • Fourth wave: Autonomous AI – Autonomous AI represents the integration and culmination of the three preceding waves, fusing machines’ ability to optimise from extremely complex datasets with their newfound sensory powers.

 

Related links for further learning:

  1. https://www.cnbc.com/2018/09/07/chinas-meituan-dianping-confirms-4point4-billion-hong-kong-ipo.html
  2. https://techcrunch.com/2017/10/10/tujia-raises-300-million/
  3. http://www.forbesindia.com/article/ckgsb/how-tujia-chinas-airbnb-is-different-from-airbnb/48853/1
  4. https://en.wikipedia.org/wiki/Mobike
  5. https://towardsdatascience.com/an-overview-of-resnet-and-its-variants-5281e2f56035
  6. https://www.faceplusplus.com/
  7. http://www.iflytek.com/en/
  8. https://www.mi.com/global/
  9. https://www.happyfresh.com/
  10. https://www.grab.com/sg/

App review: Forest

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My quick summary of Forest before using the app – I think I first heard Nir Eyal, who specialises in consumer psychology, talk about Forest. Given that Nir mentioned the app, I can imagine Forest impacts people behaviour, helping them achieve specific outcomes.

How does Forest explain itself in the first minute? – “Stay focused, be presented” is Forest’s strap line which I see first. This strap line is followed swiftly followed by a screen that says “Plant a Tree” and explains that “Whenever you want to focus on your work, plant trees.” This suggests to me that Forest is an app which aims to help people focus on their work and eradicate all kinds of distractions.

How does Forest work? – The app first explains its purpose in a number of nicely designed explanatory screens.

After clicking “Go”, I land on a screen where I can adjust time; presumably the time during which I want to focus and avoid any interruptions.

I set the time at 10 minutes and click “Plant”. I love how, as the time progresses, the messages at the top of the screen keep alternating, from “Don’t look at me!” to “Don’t look at me!” to “Hang in there!” Nice messages to help keep me focus and not fall prey to checking my phone. At any stage, I can opt to “Give up” which presumably means that the tree that I’ve been planting – through staying focused – will be killed.

I’m motivated to see this through and plant my first tree. When I complete my 10 minutes of uninterrupted time, I expect to see a nice tree right at the end of it. Try and imagine my disappointment when I don’t see a tree but instead am encouraged to create a Forest account.

Did Forest deliver on my expectations? – I can see how Forest helps people to focus and avoid checking their phone constantly. Just want to explore the gamification element of the app a bit more.