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Discovery

discovery

Science is ever-evolving, and 2021 was rich in discoveries. From health to space, there were developments in diverse scientific areas bringing us knowledge and further understanding. In this slogging thread, our community shared their favorite scientific discoveries of the year. This Slogging thread by Mónica Freitas, Daniel Guzman, Sara Pinto, Amy Shah and Jack Boreham occurred in slogging's official #random channel, and has been edited for readability. Mónica Freitas Dec 6, 2021, 2:26 PM What's the 2021 scientific discovery that most excited you? Mónica Freitas Dec 6, 2021, 2:30 PM For me, it was a team from Northern Arizona University and Johns Hopkins University discovering that water was once present in a region of Mars called Arabia Terra. It can tell a lot of past environments and their evolution. 😮 2 Mónica Freitas Dec 6, 2021, 2:31 PM Limarc Ambalina, Sara Pinto, Jack Boreham, Khamisi Hamisi, Daniel Guzman, Teri Eyenike, Favour Amadi, Allyson Blinkhorn, Amy Shah: What was yours? Daniel Guzman Dec 6, 2021, 4:43 PM Hey Mónica Freitas! I heard a while ago that a group of astronomers identified a planet outside the Milky Way, using NASA's Chandra X-ray Observatory! We're one step closer to Aliens 👽, do you believe in Aliens? Mónica Freitas Dec 7, 2021, 12:40 PM Daniel Guzman, did we? Did we name it yet? I want to google it! I'm not narcissistic to the point of believing that we're so special that there are no other forms of life outside of earth. So, I do believe in Aliens. I'm not sure about the grey big-headed image we're often fed, but I'm sure there are other forms of life. There are so many hints of patterns that repeat themselves in the universe, so it's only logical to me that other living creatures also exist somewhere else. What about you? 👽 Sara Pinto Dec 8, 2021, 12:49 PM Mónica Freitas, I'm not sure if it's considered a discovery, but yesterday I saw in the news that we managed to get a  quite detailed photo of the sun. Since I enjoy the visual side of the space discoveries, this, for me, was pretty amazing! https://www.news18.com/news/buzz/this-could-be-the-clearest-ever-photo-of-our-sun-have-you-seen-it-yet-4528412.html 🔥 1 Sara Pinto Dec 8, 2021, 12:56 PM Mónica Freitas, on the other hand, an actual discovery was finding the two black holes near Earth. These two might merge at some point, creating a massive black hole. I wonder what this means for us since black holes have a big gravitational and magnetic force. https://www.eso.org/public/news/eso2117/ Mónica Freitas Dec 8, 2021, 2:48 PM Sara Pinto, WOW, that picture is amazing! We've never been able to see beyond the gases around the sun. This is so clear! 💚 1 Mónica Freitas Dec 8, 2021, 2:51 PM Sara Pinto, I can see how that can be a massive deal for us. If their gravitational force is big enough, it can affect our solar system. It's a bit frightening. Sara Pinto Dec 8, 2021, 3:55 PM Mónica Freitas, it probably doesn't excite us, but it certainly leaves us alert! 🔥 1 Mónica Freitas Dec 16, 2021, 10:29 PM Sara Pinto, true that! On another news, a spacecraft has 'touched' the sun for the first time. I only found that out now, but it happened back in April. "NASA's Parker Solar Probe reached the sun's extended solar atmosphere, known as the corona, and spent five hours there. The spacecraft is the first to enter the outer boundaries of our sun." https://www.sciencedaily.com/releases/2021/12/211214134947.htm 🔥 1 Mónica Freitas Dec 16, 2021, 10:33 PM Also, there seem to be new developments around HIV. "An experimental HIV vaccine based on mRNA - the same platform technology used in two highly effective COVID-19 vaccines - shows promise in mice and non-human primates, according to scientists. Their results show that the novel vaccine was safe and prompted desired antibody and cellular immune responses against an HIV-like virus." This is very inspiring. https://www.sciencedaily.com/releases/2021/12/211209124236.htm Amy Shah Dec 17, 2021, 5:53 PM Not sure if this was in 2021, but I was pretty excited about the COVID vaccine as well as other treatments that have been developed to get us out of this pandemic. Amy Shah Dec 17, 2021, 5:54 PM Anything to get me out of the house and social again. Mónica Freitas Dec 20, 2021, 5:54 PM Amy Shah ABSOLUTELY!I will be even more excited when we get a cure for this disease and can resume our lives as before. Jack Boreham Dec 21, 2021, 10:51 AM https://www.sciencedaily.com/releases/2021/12/211214134947.htm Jack Boreham Dec 21, 2021, 10:51 AM This is pretty cool!! Mónica Freitas Dec 21, 2021, 5:05 PM Jack Boreham COPYCAT! I saw that article. It's awesome! I don't know how they were able of building something that could endure those high temperatures. Jack Boreham Dec 22, 2021, 12:26 PM Mónica Freitas, hahaha, great minds think alike. 🔥 1 Jack Boreham Dec 22, 2021, 12:26 PM Mónica Freitas, would you live in space if you got the chance? 😄 Mónica Freitas Dec 22, 2021, 2:18 PM Jack Boreham, ahahah let's blame it on our geniality. Mónica Freitas Dec 22, 2021, 2:18 PM Jack Boreham, actually, I've thought of that a lot growing up. So, here's my line of reasoning: I'd love to see the space for myself. However, I have a weak stomach that cannot handle the trip to the stratosphere - I'd be sick and nauseous throughout. The journey would take long, meaning I'd a chunk of my life on that trip. So, I'd a single trip to see one thing would be costly time-wise - imagine going young and fresh and returning with wrinkles already ahaha; Unless we're just talking about a short trip to the moon - then it's more doable. The food is terrible. In conclusion, yes, I'd love to go, as long as it was for free, I was knocked out during the flights, a month-long tops and I can take my snacks. Mónica Freitas Dec 22, 2021, 2:19 PM Jack Boreham, how about you? Sara Pinto do let us know your thoughts on this. Jack Boreham Dec 23, 2021, 12:36 AM 😂 Mónica Freitas, I completely agree with the knocked-out part. There's no way I would want to wait around, hoping nothing bad would happen. Hopefully, they will speed up the process. By that point, I hope the suits aren't as claustrophobic; otherwise, I'm going to die in space. I hate things that feel like they are going to suffocate me. Mónica Freitas Dec 23, 2021, 2:59 PM Jack Boreham, ahahah you must hate amusement parks. But I get it. I've tried those scuba diving things and panicked. Being stuck on a spaceship would be equally nerve-wracking 😂 Sara Pinto Dec 23, 2021, 4:18 PM Mónica Freitas, I'm a little late, but the news on "touching" the sun, that's (almost) literally fire 🔥😂 Sara Pinto Dec 23, 2021, 4:29 PM Mónica Freitas, I would like to go on vacation, for like 3 days. Actually, living there? I don't think so. The view would be amazing every time, but after a while, it's just you and space. Unless you are an enthusiast about it, I don't think it's that exciting. Sara Pinto Dec 23, 2021, 4:29 PM Mónica Freitas, when it comes to the journey there, in my naive head, I think I would actually like to be awake, haha. Mónica Freitas Dec 27, 2021, 3:32 PM Sara Pinto, oh yeah, I'm with you. I wouldn't be able to live in space, maybe if I were more of an introvert. Mónica Freitas Dec 27, 2021, 3:33 PM Sara Pinto, oof, you're braver than me

What 2021 Scientific Discovery Excited You the Most?

Nowadays it’s unreasonable to start a software development project without preliminary comprehensive analysis. The discovery phase is an information-gathering procedure that provides an in-depth comprehension of the industry, the client’s business, and the target audience. It’s important to gain a profound understanding of the stakeholders’ anticipations of the product and your end-users' expectations. The main aim of the preliminary analysis is to provide a quotation to the customer. For this purpose, gather as many details as possible about the clients' needs and put it in a separate document. All the details found in the course of the discovery will help you to scope and plan your project. In the end, you will benefit from the delivery of the state-of-art custom software product to your client. To deliver really cutting-edge products do not underestimate the discovery phase! What do you need the analysis for? To find out the motives, the aims, and the problems of the users. To comprehend the context of product usage. To find new ideas for product development and new insights. To understand what are the users’ expectations and attitudes to the product. How long should the discovery be? For mid-sized projects — 1-2 weeks. For large projects — 3-4 weeks. What you should do during the Discovery Phase? During the Discovery Phase, you have to create a series of documents and schemes for future effective work on the project. 1. Lean Model Canvas Firstly, a conceptual description of the future product business model for MVP is created in the form of a diagram describing all business processes related to the product: proposal, infrastructure, consumers and financial aspect. 2. Customer Journey Map In addition, a «map» of customer communication with the product is created. This is a visual scheme of the user interaction with the product, which includes all the proposed points and channels of such interaction, as well as the client’s visualized experience, with his thoughts, emotions, goals, motives, fears on the way to achieving the result taken into consideration. 3. User Flow To determine how the user will interact with the interface of the new product, User Flow is created in the form of schematic screens of the software solution and transitions between them. Thus, the user behavior scenarios are projected through the visual interface prototypes. 4. User Stories A brief description of how the system will be used describes functional requirements for the system and its acceptance criteria. User Stories allow the team to effectively prioritize the implementation of product functionality. 5. Product Vision This document, describing the general objectives of the project and the proposed solution, allows a better understanding of the product creating goals, potential, and future prospects. Product Vision is useful to all the parties involved in the development — developers, staff, marketing department, etc. 6. Non-functional requirements Our team also issues recommendations regarding the properties of the system or limitations that are not related to the behavior of the system — the optimal technology stack, infrastructure architecture, and expected load. What are the main benefits of a Discovery Phase? The benefits of the preliminary analysis and research are in fact multiple. Quite often you face startups that have an idea but do not have a deep understanding of what the project should be like and which components it should contain. It’s likely that the team experiences difficulties understanding what the future users really need. Besides, due to the lack of technical background, the team often fails to make a comprehensive list of the required software elements. The research is conducted by your business analyst, designer, and CTO. They communicate to the customer, find out the requirements and analyze the market. Later on, they make the project description. Such an approach minimizes the number of alterations in the development process because the scope of the project is defined along with the other key factors such as the type of solutions, features, and functionalities required, best platforms to be used, timeframes to fit in and costs to match. By identifying all the details in advance, you gains a number of benefits. The main of them are: Honing of the idea and the essence of the project, based on real analysis. Finding out certain project aspects, which have not been taken into consideration initially. Customers’ expectations and problems comprehension, based on the competitors’ products research. The opportunity to get an expert evaluation of the project and the ways it can be brought to life as well as an additional insight into the alternative solutions and technologies offered by the contractor. Creating a clear list of user stories for the project. Avoiding the need of making costly changes during the development process. Achieving the balance between the business goals of a client and the needs and wants of the users. Getting the possibility to understand if the contractor is a good fit for the client’s expectations, how comfortable the interaction between them is and the opportunity to make the final decision as to future cooperation. You have to always perform the expert evaluation of how the project fits into your present infrastructure and operational processes and recommend changes, improvements or updates if they are necessary. An additional bonus, which a client may receive as a result of the discovery phase, is the clear project quotation with the scope and plan of works required and proper cost estimation. With such a document you can turn to the potential investors and get funding easier. Through discovery, you lay the ground for the great project experience, and provide valuable software solutions customized for your needs. Previously published at https://stfalcon.com/en/blog/post/discovery-phase

The Discovery Phase Is Crucial To Your Software Development Project and Here's Why

This is the fourth and final post in my series on an approach to product discovery - Double Diamond Discovery (again thanks to the British Design Concils super awesome framework).  So far I have posted an overall view  and then expanded on Diamond 1 (D1) and Diamond 2 (D2). This final post discusses the delivery track (https://www.jpattonassociates.com/dual-track-development/) and how this feeds back into the discovery track.  In the diagram above there are two steps after discovery - “Delivery” and “Learn”. Although we want to have a ‘ship to learn’ (https://www.intercom.com/blog/intercom-product-principles/) mindset I need to emphasize most of the learning is done in D2 where learning is cheap and fast. There are always many new things to build/fix/improve so it’s easy to ship and forget.  But shipping is only half the job. Shipping is only half the job. Most of our discovery work will have a handful of users and mostly qualitative feedback so although we may have done a thorough job in discovery and are ready to ship with confidence, most of the time we are not shipping with certainty. No matter how much discovery you do, even AB testing with statistical significant results, shipping is the only way to answer the question “Do our customers use the feature?”. Delivering production quality software (https://svpg.com/discovery-vs-delivery/) provides feedback at scale - but only if appropriate instrumentation to capture the metrics (e.g. our key results) are implemented. We need to setup a dashboard in the analytics tool to easily view and draw understanding from the usage behaviour.  I suggest spending 15min every day looking at the dashboard and sharing the interesting metrics with the team. Do a deep dive Do a deep dive into the usage data with the full team - design, engineering, product, analytics and data science.  What is the data telling us?  What can we learn? How can we take these learnings back into discovery? What is the adoption?  The engagement?  The retention? Are the key results moving? And then... how does the adoption, engagement, retention vary between users? And then... is there a segment of users highly engaged?  What are the characteristics of that segment?  Which of those characteristics makes the software more useful?  If the segment is large enough focus your future efforts on that segment (be careful not to create custom solutions for each segment - although this is great consultancy work its lousy product management). Fiddle with the dashboard, look for patterns, look for the “hm… that seems a bit odd”.  Dig in and become one with the data {-_-}. As mentioned in step 5 of the ground work we need to setup a recurring meeting to review the outcome of what we have shipped and reflect/share/capture what we have learned. Take these insights from the data and the lessons learned back into discovery.  Rinse and repeat. Good luck. This is the fourth and final post in my series on an approach to product discovery - Double Diamond Discovery (again thanks to the British Design Concils super awesome framework ).  So far I have posted an overall view and then expanded on Diamond 1 (D1) and Diamond 2 (D2) . This final post discusses the delivery track (https://www.jpattonassociates.com/dual-track-development/) and how this feeds back into the discovery track.  In the diagram above there are two steps after discovery - “Delivery” and “Learn”. Although we want to have a ‘ship to learn’ (https://www.intercom.com/blog/intercom-product-principles/) mindset I need to emphasize most of the learning is done in D2 where learning is cheap and fast. There are always many new things to build/fix/improve so it’s easy to ship and forget.  But shipping is only half the job. British Design Concils super awesome framework overall view Diamond 1 (D1) Diamond 2 (D2) most Shipping is only half the job. Most of our discovery work will have a handful of users and mostly qualitative feedback so although we may have done a thorough job in discovery and are ready to ship with confidence, most of the time we are not shipping with certainty. No matter how much discovery you do, even AB testing with statistical significant results, shipping is the only way to answer the question “Do our customers use the feature?”. Delivering production quality software (https://svpg.com/discovery-vs-delivery/) provides feedback at scale - but only if appropriate instrumentation to capture the metrics (e.g. our key results) are implemented. We need to setup a dashboard in the analytics tool to easily view and draw understanding from the usage behaviour.  I suggest spending 15min every day looking at the dashboard and sharing the interesting metrics with the team. Do a deep dive Do a deep dive into the usage data with the full team - design, engineering, product, analytics and data science.  What is the data telling us?  What can we learn? How can we take these learnings back into discovery? What is the adoption?  The engagement?  The retention? Are the key results moving? And then... how does the adoption, engagement, retention vary between users? And then... is there a segment of users highly engaged?  What are the characteristics of that segment?  Which of those characteristics makes the software more useful?  If the segment is large enough focus your future efforts on that segment (be careful not to create custom solutions for each segment - although this is great consultancy work its lousy product management). Fiddle with the dashboard, look for patterns, look for the “hm… that seems a bit odd”.  Dig in and become one with the data {-_-}. As mentioned in step 5 of the ground work we need to setup a recurring meeting to review the outcome of what we have shipped and reflect/share/capture what we have learned. ground work outcome Take these insights from the data and the lessons learned back into discovery.  Rinse and repeat. Good luck.

Double Diamond Discovery - Part 4 and final

Discovery is undertaken in two steps with continuous iteration within each step. Step one is ensuring we are and step two is ensuring we are . This post is about step one in this process, AKA diamond one (D1) - . I started this series with an . Again thanks to the . solving the right problem solving the problem right my previous post explains step two, AKA diamond two (D2) overview of how to apply the double diamond to product discovery British design council for their very awesome double diamond Whilst D2 involves a lot of doing e.g experimenting, and failing efficiently, D1 involves a lot of pondering - data informed pondering. Doing a great job in D2 is pointless if we haven’t done due diligence in D1 - remembering from the that building awesome products that nobody uses, is not that awesome. So making sure we are solving the right problem is the key to being awesome ¯\_(ツ)_/¯. This is why D1 is the foundation of the product. original post Diamond one is the foundation of the product D1 is where strategy comes in to play. The strategy is normally coming from the c-suite supported by the strategy team who undertake massive amounts of research to determine the long term (3 to 5+ year) direction of the company. As product managers, it is our job to ship products which support this strategy. This can be referred to as the "business impact" of our products. As product managers, it is our job to ship products which support this strategy The first thing is which "customer outcomes" will have the most “business impact” - i.e which customer problems can we solve to deliver business value. we need to learn One way to do this is the driver tree. The driver tree, not to be confused with an inverted funnel, is the practice of starting with the metric we want to increase - the “thing we optimizing for” - and then branching out to all the things that drive that metric (driver trees need to be an entire post). These drivers are the levers which the product may be able to influence. This is where we undertake divergent (exploratory) user research - using the customer advisory board (CAB) and key internal stakeholders, for example the support organisation, speaking to support teams and looking at support tickets/feedback.  Also deep diving into the available analytics. This is iterative. As new ideas for problems worth solving arise we are validating these problems with users using convergent (validation) user research. Convergent and divergent. Rinse and repeat. Once we have established which drivers we think the product can influence (i.e. which customer problems we think we can solve) we can carve out some inspirational objectives. Next we need to define concrete metrics which can be delivered within three months - key results.  It is super important to work closely with your data analyst to ensure that the metrics are sound i.e. the metrics measure what you want they can be pulled from the data that you can get. and There is much written about OKRs, and I am no expert, but as a practitioner I can testify that having inspiring objectives which support the organization's strategy coupled with metrics which measure progress toward those objectives works pretty well. It is this framework which I use to evaluate problems/opportunities in D1. If solving a problem does not potentially move the needle on one of the key results, the idea goes to the bottom of the list - but try to avoid ‘decision debt’ - if an idea is totally ridiculous, it should be clear that this is the case. It’s only fair. In summary Looking at D1 we first apply divergent thinking - what are all the problems we could be solving - followed by convergent thinking - what problems should we be solving for our customers which move the needle on a metric we care about. This identifies which opportunities feed into D2. I mentioned D1 is the foundation of our work, and there is a lot of thinking involved - but don’t overthink it. We just don’t want junk going into D2. We can do an awesome job in D2 but building awesome products that nobody uses, is not that awesome.

Double Diamond Discovery: Part 3

In my I described how to apply the Double Diamond - a tool of design thinking (https://www.designcouncil.org.uk/news-opinion/what-framework-innovation-design-councils-evolved-double-diamond) - to product discovery.  In I will be diving deeper into diamond two (D2) where we address four types of risk as defined by : previous post this post SVPG Is it valuable to the customer? Is it usable by the customer? Is it feasible for us to build it? Is it viable for our business? D2 in a nutshell: conjure as many solutions as possible (divergent thinking) and then validate each idea to eliminate all but the optimal solution (convergent thinking). The final convergent step should not be confused with the “Learn” step which is intended to reflect a “ship to learn” mindset (https://www.intercom.com/blog/intercom-product-principles/). NB: D2 is an iterative process and starts with some hypotheses which can be validated at varying levels of fidelity.  A good hypotheses takes a format something like this “We believe suggesting improvements to authors at point of submission will increase the quality of submitted manuscripts as measured by a decrease in the desk reject rate from 50% to 45%”.  See a great post on hypothesis here < >.  Surveys, interviews, wireframes, live data prototype and AB testing are typical methods to validate a hypothesis. On occasion, for a big bet, an idea may pass through multiple levels of validation, say starting with a survey, then wireframe and then AB test (assuming at each validation your hypothesis is not disproven).  Commonsense is needed to determine how much time and effort to spend on validating an idea (i.e. cost vs benefit).  Ray Dalio principle 5.6 ( ) “Think of every decision as a bet with a probability and a reward for being right and probability and a penalty for being wrong.  A winning decision is one where rewards times it probability of occurring is greater than the penalty of it occurring”. https://www.producttalk.org/2014/11/the-5-components-of-a-good-hypothesis/ https://www.principles.com So let’s dive into D2. The discovery workshop First we need to make sure you have the right people in the room - physical room where possible - this should include product, engineering, design and, depending on your situation, a data scientist.  In my current role we always include a subject matter expert from the area of the business where the problem is causing the most pain. It is important to find a real subject matter expert rather than someone with a lot of opinions. I start this kind of workshop with a slightly modified version of the lean canvas ( ).  I prepare a first draft of the canvas prior to the meeting and then, in the meeting, walk through the canvas box by box and update the canvas.  Its important for everyone to contribute and feel part of this process - I find this helps get everybody in a ‘product thinking ( ) mindset.  This should take . http://leancanvas.com https://www.mindtheproduct.com/why-product-thinking-is-the-future-for-product-management/ about 30min to max an hour At this point everybody should be focused on the problem. Its important to note that the outcome of these workshops are shared with other key stakeholders to mitigate  viability risk early on.  For example, it may not be neccessary to include a participant from your ethics department, but sharing your ideas early with ethics can save you a lot of time and wasted effort. Unfortunatly I speak of this example from personal experience :/ Ideation There are many methods to conjure up ideas to solve the problem at hand (selected in diamond 1).  Often the ideas come from outside the room but typically ideas come from: Random gut feel Iterating existing features Customer feedback Tech eg scale Quality eg bugs/performance  (cite this) Which method is best for your team is an experimentation process in itself.  Using Jobs to be Done ( ) is one of my favorites.  A method I haven’t yet experimented with but am super keen to try is the opportunitiy assessment tree ( ). https://hbr.org/2016/09/know-your-customers-jobs-to-be-done https://www.producttalk.org/2016/08/opportunity-solution-tree/ Easier said than done One of the things I struggle with is speed - validating ideas quickly to reduce the cost of failure. Iterating at speed (without forgoing too much quality) is difficult.  This is what I like to refer to as . This is, in my imagination, when dual track development ( ) is working in perfect harmony (NB: I have never achieved perfect harmony).  Setting up a Customer Advisory Board (CAB) ( ) and having recuring scheduled calls with users on an ongoing basis is key to having good Discovery Flow.  I, with my awesome UX lead, are recruiting our CAB at the moment - so any academic researchers out there wanting to help please reach out [end plug]. Discovery Flow https://www.jpattonassociates.com/dual-track-development/ https://www.productplan.com/glossary/customer-advisory-board/ The other thing I find difficult is designing experiments to validate ideas which are both meaningful and .  One of my heroes Don Norman ( ) (if you havent read this book it really is one of the classics - I think Design of everyday things, along with and are the 3 essential product management books).  In this example Mr Norman and his team want to understand how pedestrians will respond to driverless cars - so they go to an auto-store, buy some car seat covers and make suits out of them.  They then drive around in these suits and it appears there is no driver.  Genius! as small as possible https://www.nngroup.com/books/design-everyday-things-revised/ Lean Analytics Inspired

Double Diamond Discovery - Part 2

Large enterprises have lots of smart people with great ideas.  Some of these people are charming, passionate and convincing.  Some of these people are very good at lobbying for their idea with your boss’s boss.  And some of these people have the patience and persistence of a Zen priest. And then of course we have our users and our customers.  And governments and regulatory bodies (*cough* ). GDPR It is easy to get lost in the avalanche of great ideas. Saying ‘no’ to a new idea is easier said than done. In this article, I propose a robust procedure to help product managers say ‘no’ and have that decision be palatable to those raising the idea.  Decisions which are made without buy-in are brittle. Working smarter not harder My hope is that this procedure will save product managers time and unnecessary stress whilst building better relationships with your key internal stakeholders. Discovery is our opportunity to really listen to each other. Although this process may require more time to decide on what to build, through providing a sense of fairness we will accelerate implementation - afterall, fairness builds buy-in. Idea overload Looking at two economic concepts: "THE economic problem – sometimes called the basic or central economic problem – asserts that an economy's finite resources are insufficient to satisfy all human wants and needs. It assumes that human wants are unlimited, but the means to satisfy human wants are scarce". Wikipedia "Opportunity cost is a key concept in economics, and has been described as expressing "the basic relationship between scarcity and choice." A choice needs to be made between several mutually exclusive alternatives; assuming the best choice is made, it is the "cost" incurred by not enjoying the benefit that would have been had by taking the second best available choice." Wikipedia. In other words, we as product managers will never have enough engineering, data science and design capacity. As product managers, we have a wide range of responsibilities to maximize the ROI of our products – and deciding what to build is at the core of these responsibilities. Theoretically it’s very easy to “just say no” and move to the next idea.  But we all know that humans/colleagues/organisations don’t work like that. To deal with idea overload you need an air tight discovery process.  A transparent and repeatable discovery process that will bring ‘procedural justice’ to your decision making -  whereby stakeholders understand how decisions are made and that they will be made in a consistent manner. So how do you objectively make evidence driven priority decisions within your discovery process? A discovery process which I have been experimenting with is a hack of The British Design Councils Double Diamond. The Double Diamond The British Design Councils double diamond model of design is a powerful tool of design thinking. When applied to product discovery, the double diamond provides not one but two evidence driven opportunities to say “no”. So how, exactly, does one apply the double diamond to discovery? Groundwork Before we get to the double diamond discovery – I recommend you do some groundwork. Step 1: Gain agreement from all key stakeholders on the process itself. Do this with whiteboarding, powerpoint or whatever is your preferred communication medium. Propose, align, iterate and repeat.  Agreement to the process is essential to the alignment. Step 2: Compile the strategic objectives of your key stakeholder’s function and define metrics which measure progress towards those strategic objectives (OKRs are a great tool for this exercise).  If your stakeholders don’t have this information it’s a good opportunity to build a relationship and guide them through this.  Once you have goals and metrics in place you will have decision-making framework to use in the first diamond. Step 3: Provide a single entry point for all ideas.  It can be low-fi (e.g. email or slack) but an ‘ideas portal’ (I use ProdPad for this) to capture critical information will save time.  Providing fields to capture additional details (e.g. Insights so far? Target users? What is the value proposition? What would success look like? Which strategic goal does this help us reach?) will prevent the need to ping pong with the person raising the idea. There are many tools to help you do this easily and the better tools allow the person raising the idea to track their idea without you having to manually update them.  Idea voting and duplicate idea suggestions are also great features to have (I have no affiliation with ProdPad). Step 4: Schedule a recurring meeting every one or two weeks with key stakeholders to review new ideas. Step 5: Schedule a recurring meeting every six to eight weeks with key stakeholders to review the outcome of experiments (i.e. ideas currently in the 2nd diamond) and/or the impact of the things that were deployed to production (i.e. the things that have made it through the discovery into delivery). Done?  Then lets get to discovery. Applying the Double Diamond to Discovery Image thanks to Anna Peniaskova. Diamond One Applying the double diamond to discovery first employs divergent thinking to capture all the problems we couldsolve.  This is where the idea portal (see step 3 above) captures all the ideas in a structured manner.  When colleagues suggest new ideas to you at the coffee machine, in the elevator, via email or anywhere else, politely refer them to the idea portal – explaining that all ideas are created equal. Then its time to start convergent thinking to focus our scarce resources on the problems that we think might help us achieve our agreed goals.  Review each idea against the decision-making framework you compiled in step 2 (above).  You will likely need to map ideas back to problems (as many ideas will be solutions rather than problems) and do some grouping of ideas if they relate to the same underlying problem. Do this in partnership with your key stakeholders in the ideas review meeting (refer step 4 above).  This sounds painful, but its worth it.  Do it for your users. This completes the first diamond. You should now have a shortlist of ideas which map to the problems that you and your stakeholders care about.  It is important to remember that to progress from the first diamond to the second diamond you need evidence - either qualitative or quantitative. Stakeholders opinions or hearsay from users is not enough. A key output of the first diamond is a forecast in the metric we expect to shift and by how much.  This is the bet we will try to validate in diamond two. Diamond Two We start the 2nd diamond with divergent thinking again to uncover all the possible solutions to solve the problems we shortlisted – some of the solutions may in fact be the ideas already suggested. We need to have at least two distinctly different solutions for each problem. We then converge on the optimal solution through validating the potential solutions using historical data (e.g. support issues raised by users), interviews with users (sometimes including wireframes), surveys or AB experiments.  The amount of effort you want to spend should be relative to the size of the idea/risk. This completes the second diamond. Finally, to ensure we learn from our previous decisions we measure the actual result and compare it our forecast.  We present these at a benefits retrospective meeting (see step 5) every six weeks to discuss: where did we fail where did we succeed what did we learn To learn more details on the discovery track and "Tasks within the steps" just reach out. How do we measure the effectiveness of the discovery track? Measure the effectiveness of the discovery track by tracking different outputs over different tasks of the process in combination with cycle time and time spent with customers. But the essential outputs are as follows: Diamond 1 Ideas can be measured and are mapped to a metric on the driver tree Improvement in a metric has been forecast Business value has been validated User value has been validated Diamond 2 At least two feasible solutions to solve the problem have been identified (i.e. not just one solution with slight variations) Test results (from testing the feasible solutions) Epics and user stories + other artifacts (e.g. design brief) Being inclusive is key – not to be confused with consensus - we involve the team of five + 2 (product, technology, analytics, user experience and quality plus operations and publishing). Consensus on the process is key – but once everyone is agreed on the process – you are on firm ground to say ‘no’. A final thought Applying the double diamond to discovery does not mean to make decisions by committee. Product managers are responsible for the ROI and a key part of that responsibility is to understand our customers, users, competitors, strategy and trends - and then based on that understanding make product decisions regarding which problems to solve. Working through a rigorous discovery process enables us to make better product decisions which are accepted by stakeholders - because building awesome software that nobody uses is not that awesome. Just ask these guys... Final, final thought There are many way to do discovery and this one of them.  I am always looking to do better discovery so if you have any thoughts, want to discuss other methods please reach out.

Double Diamond Discovery

Working with Product Manager customers on , I’ve observed some interesting patterns. Teams move from problems to solutions too quickly, use MVPs for solution feedback, are biased on singular requests, and loose context across the process. If the following observations seem like common sense and aren’t problems with your team, good for you! product discovery Moving from Problem to Solution Too Quickly Even design-thinking technologists move from understanding problems to creating solutions too quickly. Perhaps because we’re grounded in what we know how to build with technology. Perhaps we pattern match to solutions we’ve worked on before. Or perhaps we take customer feature requests from customers seriously. If you move too quickly into solution mode, it’s not just that you skip real problem discovery. You’ll naturally be biased to extend the solution you start creating and it blinds you to understanding the problem or alternative solutions. Until further down the road when you have negative signals about the solution, which is, expensive. MVPs Are for Problem Validation First Most people think of Minimum Viable Products as prototypes that help validate a solution. I think that’s a mistake. Put aside the MVP, or anything that involves writing code, until you’ve got an understanding of the customer problem with some validation from conversations with customers and those on the front lines (sales, support, customer success and marketing). Then when you create lightweight prototypes for customers to react to, most of the feedback you seek should be about the problem. Customers may tell you: I don’t think you understand my problem This is interesting, but let me describe my problem in further detail This helps me realize that the adjacent problem is more important Ask and listen first for insight about problems in reaction to the prototype. Customers will likely have lots of feature ideas if just framed as a solution, and most don’t even solve what’s important for them. And iterating on the prototype should be driven more by what it solves than what it could do. Problems Come in Patterns Often when a customer has a feature request it’s viewed as solid problem with readiness to pay for a solution. And with talented salespeople advocating for it in your organization, the singular opportunity offers impact and certainty. But the best problems are patterns across multiple conversations and requests. Continuously organize and associate them until the pattern and business case becomes clear vs. other priorities for what to build next. End-to-end Context So much context is lost in product discovery. Yielding less than optimal decisions, designs and implementation. Problem context has value in the initial understanding, relative prioritization, solution design, development implementation, quality assurance, product marketing and more. Pure fidelity of context is burdensome to capture, so keep it simple. When the product manager sees signal in a customer conversation that is likely to be acted upon, use that moment to gain the context needed to understand the problem. Along with the anecdotes, capture the Who, What, When, Where, Why and sometimes How. The goal should be end-to-end context from the customer discovery conversations to customer success outcomes. If you capture the context up front, and use the right tools, it can be maintained across the functions of your business. Shameless plug: if you are a product manager and your team is on Slack, you should be using Pingpad for Collaborative Product Discovery .

Problems with Product Discovery

How did I not know about a new Manic Street Preachers until four days after its release? Part user error. Part product shortcomings. So much for counting on as a safety net. I’ll have to keeping doing the dirty work. technology The Manic Street Preachers released a new album, , on Friday. I didn’t find out about it until yesterday (Monday). To be truthful, I probably knew the street date at one point in time. No doubt I got some sort of message about it — I track the band as best possible. There were surely emails leading up to its release. I might have run across an article. But last week the album was far from being on my mind. Resistance is Futile Anonymity is a problem. I’m one of the few thousand people in the U.S. — excluding expats and Europeans on vacation — who like the band. OK, maybe that’s an overstatement, but the Manics are one of those bands whose homeland popularity hasn’t migrated to the States (see James, Girls Aloud, Carter the Unstoppable Sex Machine, The Libertines et al). As a result, the band’s albums fly way under the radar here. Technology is to help solve the anonymity problem. Algorithms predict what new will interest me based on my listening history. A music service I’ve used for seven (Spotify) and ten or 12 (Pandora) years should know my favorite bands by now. They have received thousands of signals on which to base their calculations. supposed music Subscription services talk up their music discovery prowess. Spotify’s roughly 1,000-page form F-1 filed with the Securities Exchange Commission uses the word 35 times. “We are in the discovery business,” it says [page 97]. The service’s “powerful music search and discovery engines,” combined with “a large and growing” user base, enables Spotify to “continuously learn about [users’] listening behaviors” in order “to create a more personalized and engaging experience” each time a person visits [ibid]. discovery But algorithms failed me this time. Curation failed me, too. And this was a textbook case the potential and promise of the algorithm-curation combination. Spotify didn’t let me know came out. There’s nothing in my , the algorithm-created playlist that provides a decent overview of new and recently released tracks. is a good—and popular—discovery tool that introduces me to unknown artists and new tracks by familiar and beloved artists. But not this week. Resistance is Futile New Release Radar New Release Radar I can’t find the Manics if I browse through Spotify’s playlist, a curated group of songs from the more prominent new releases. Digging around a bit, however, I see a new Manics song on the playlist. This was easy to miss. As a U.S. subscriber my default new music playlist is the U.S. version, (minus the ). The solution is obvious: follow the UK playlist and sift through the two new playlists each week instead of one. New Music Friday New Music Friday UK New Music Friday UK Pandora didn’t let me know the album came out, either. I don’t see on either the personalized new releases section or the general list of new releases of the Pandora Premium app. A new song might be programmed into a station but which one? I’d guess but I get Godsmack, Greta Van Fleet, and the like. I just don’t listen to too often…but Pandora knows that. Resistance is Futile New Rock New Rock Finding out about new releases requires some legwork. I have something of a system. It’s far from perfect. Each Friday I look at the previous night’s email from Grimey’s Used and Pre-loved Music, a great Nashville record store, to see what new albums the store highlights. Grimey’s always alerts customers about good albums. I didn’t read the email Friday, but the Manics album wasn’t mentioned. I try to remember to look at ’s Friday emails to see what new releases get a mention. The Manics’ album made the list but I didn’t read Friday’s email. So, user error in that case. MusicREDEF I follow the Manics on Twitter. The problem is I probably miss 95 percent of things on Twitter because I don’t spend much time there. Using Twitter to learn about new music is like scanning movie credits moving at 100x speed— if you’re actually looking at the movie credits to begin with. Side note: Twitter alert me about the album but it was a MusicWeek tweet. I have a list of music industry trade pubs/blogs so I don’t have to sift through hundreds of Tweets to run across a single Billboard article of interest. Maybe I’ll have to put together a Twitter list of my favorite bands. did I rarely look at Facebook, so no chance of learning about an album’s street date there. Perhaps I’m guilty of laziness in this case, but I’ll choose ignorance over frequent Facebook use. I subscribe to the Manic’s email list. The email about the album’s release arrived Friday, but I missed it. With the high number of emails I get, I often miss stuff in my Gmail “Updates” folder. If the email came to my primary folder (I’ll fix that) I might have seen it. Again, user error. You can forgive me for not opening the Manics’ last email, though. Here’s a typical Manics email loosely translated into American English (with a Southern dialect since I live in Nashville): “Thanks for being a fan way over there. We know you enjoy email updates about new concert dates about 10,000 miles from your home. On those rare occasions we announce a U.S. tour, it’s unfortunately one of those eight-city jaunts that skips your market and effectively says, ‘Well, we gave it a try but the U.S. is a hard nut to crack!’ And while we have your attention, we’re going to debut a new video on the band’s official Vevo channel that you’re not allowed to view for licensing reasons.” To be fair, Spotify and Pandora have introduced me to great music I wouldn’t have otherwise found. On a regular basis. But services frequently seem to be more interested in new recordings by new artists than new recordings by familiar bands. There’s ample evidence for this. All streaming services (as far as I’m aware) try to enhance their brand by associating themselves with next big things and up and comers. But I streaming services to do heavy lifting. They’re built to lead listeners to music they’ll love. Left to my own devices, I’ll get crushed under an avalanche of social media posts, emails, and magazine articles. Nobody who works full time and has a family is going have the spare time to outrun the debris. need Data is the solution. I won’t count on human programming. Curators can’t be expected to perfectly understand my likes and dislikes; I can’t be expected to have similar tastes as curators. Help me, algorithms. You’re my only hope.

The day music discovery failed me

When I was a kid, I exploring the World Wide Web. There was just , and I was on a mission to find it all. Unlike the homogeneity of the modern web, back loved so much to discover then was unique. everything Every web site (that's right, we put a space between the words "web" and "site") was lovingly hand-crafted by amateurs and hobbyists to share the things they felt most excited about. Whether it was South African bird watching or collecting 18th century porcelain toilet seats, every site oozed passion and creativity. Instead of feeds and walls, algorithms and search-engine optimization, we had webrings and links pages. Like-minded people created communities, rather than joining one that already exists. their own We connected through guest books and chat rooms, trading the gems we discovered with one another like baseball cards (which were also far more interesting at the time). As the web grew up, and the personal home pages were replaced by Myspace pages, and then eventually Facebook and Twitter and <insert service here>, discovery became more difficult and less spontaneous. For a time, we had services like that allowed us to still be , but the "web site" eventually transformed into the "blog," which itself became a "profile." StumbleUpon explorers What's Old is New Again I know I'm painting a pretty bleak picture, but the reality is that the old web isn't lost. It's just buried. Hidden beneath layers of new growth, waiting to be re-discovered. Just because the noise has gotten louder doesn't mean the signal is lost, you just have to look a little harder. The old web—lovingly called The IndieWeb now—is still alive and kicking, and thanks to some wonderfully crafty creators, it is waiting to be discovered. Webrings Believe it or not, webrings still exist—my website is actually a . While there are still a bunch of different ones out there, if you are looking to join one (or just discover some new sites to explore), here are a few places to start: part of one - websites that are keeping Web 1.0 alive. TheOldNet WebRing - weird, unique websites that are worth checking out. Weird Wide Webring - websites that show individual personality. Hotline Webring - hand-crafted wikis and portfolios. xxiivv webring Search Engines It's been a time since Google took over the internet search game, and even before that there was Yahoo, AltaVista, Ask Jeeves, and a bunch of other services that aimed to consolidate the web and make it searchable. long Well, thanks to Search Engine Optimization, modern search pretty much sucks for discovery now, but that doesn't mean search is dead. all There are a handful of great vertical search engines that focus on unique, niche categories: - built using archived websites, Old'aVista is the gateway to the old internet. Old'aVista - a search engine that favors text-heavy sites and punishes modern web design. Marginalia - search engine for the classic web. Wiby Page Stumblers In the same vein as StumbleUpon, there are some newer sites that are dedicated to completely random discovery. These are experimental pages that will randomly load a website from The IndieWeb, and I use them both often when I'm looking for something new and unique. - go for a walk and enjoy getting lost on the web. The Forest - randomly explore the IndieWeb. indieblog.page Start Somewhere While the services listed above are great tools for rediscovering the art of discovery on the web, they are simply starting points. Once you find yourself going down a rabbit hole, it is often worth it to see how far down it goes. Links pages and blogrolls have made a comeback, and with just a little bit of digging the creators you like will link out to the creators like. they All it takes is to begin. Close your social media app of choice and embrace the personality and excitement of The IndieWeb. Go get lost somewhere on the web—but don't forget to leave some breadcrumbs so you can share what you discover with me later. Also published at . flower.codes Also, check out this awesome track: https://www.youtube.com/watch?v=cq8k-ZbsXDI

Light My Web Exploration Fire 

Enciende mi fuego de exploración web

Allumez mon feu d'exploration Web

लाइट माई वेब एक्सप्लोरेशन फायर

ライト マイ ウェブ エクスプロレーション ファイアー

Acenda meu fogo de exploração na web

Thắp lửa khám phá web của tôi

点燃我的网络探索之火

In 2015, Dr. Eric Lander, a professor at the Massachusetts Institute of Technology (MIT) [1]-[2], was invited to the first National Math Festival to give a speech [3]. At the talk, Eric convinced the public how important fundamental research was, how wrong funding organizations were to overlook the value of those fundamental researches, and what they could finally earn from those researches. Eric realized that the U.S. government or any private sector would be careful on financial spending; since the beginning of the 2000s, the United States of America had been in a state of declining economic growth [4]. Even in Europe, some countries aimed to cut off their research funding and tended to relocate to some other social investments with a more obvious short-term payback than scientific research. Professor Dr. Eric Lander claimed that the criteria with which the projects for the country's economy and defense would be justified for funding was not applicable to the basic research. People usually had a wrong perception of how basic research would pay off in the long run. Apart from the initially intended number of financial returns, all unintended scientific discoveries have proved uncountable benefits throughout human history. He had given some examples of math, physics, and biology discoveries during the research and the high values in their today applications. In my opinion, after finishing Dr. Eric's transcription for the festival, I agree with him on the value of research and especially on the countless value of the discoveries along the way of the research. One research would lead to one discovery, and one discovery would lead to another research; and this cycle will continue, as Dr. Eric called it the Miracle Machine, the title of the talk on his Math Festival night. It is probably obscure that we cannot predict what we would find out while conducting research; however, in the end, we will definitely and eventually uncover some new concepts or ideas, according to Dr. Eric's context. Eric called for attention when either the government or any private business evaluates research for capital funding. Unlike other typical investments, ROI does not work for approving a budget for research. Back in the year 300 B.C., Euclid proved that there were an infinite set of prime numbers [5]. RSA cryptography was granted a U.S. patent in 1977 [6], and it has been globally used in cryptography for present-day banking, e-commerce, and secure communications [7]. We can ask ourselves - who would want to invest money in research that had a longer-than 2000 year payback. It did not even pay off in one's life. People may overlook or ignore if they do not understand what the research was for. I would suggest the government or a company isolates the budget for basic research from the capital pool if never done before. This would guarantee the funding for research. We do not let basic research share the ROI policy with the national strategic projects. Congress may set up board committees from academic institutions, university professors, or patent reviewers to make a list of potential research topics and make justification not based on short-term ROI reasoning. In short, I positively support Dr. Eric's observations. I appreciate all math and scientific researches and discoveries done in the past; and their applications. I also see that not all researches are good fundamental researches. ROI and some other financial tools may not be able to tell much about the research value. A Board of academic experts probably can give a reliable justification for the research; however again, we would not know what we would find out not until the research started. Sources: Eric Lander: The Miracle Machine https://www.msri.org/system/cms/files/132/files/original/Lander-Case_for_Research.pdf References: [1] Faculty - MIT Department of Biology. (2019). MIT Department of Biology [Online]. Available: https://biology.mit.edu/profile/eric-s-lander/ [2] Eric S. Lander - MIT Department of Biology. (2019). MIT Department of Biology [Online]. Available: https://biology.mit.edu/about/faculty-directory/ [3] "National Math Festival: Supporting the Math of Today and Tomorrow," Institute for Advanced Study (IAS), The Institute Letter Summer 2015, 2015. [Online]. Available: https://www.ias.edu/ideas/2015/national-math-festival [4] "Economists call it recession," CNN Money, Nov 26, 2001. [Online]. Available: https://money.cnn.com/2001/11/26/economy/recession/ [5] C. Caldwell, "Euclid's Proof of the Infinitude of Primes," The Prime Pages. The University of Tennessee at Martin [Online]. Available https://primes.utm.edu/notes/proofs/infinite/euclids.html [6] R. L. Rivest, A. Shamir, L. M. Adleman, "Cryptographic communications system and method," U.S. Patent 4,405,829, Dec 14, 1977. [7] D. Boneh, "Twenty years of attacks on the RSA cryptosystem," Notices of the American Mathematical Society (AMS), Vol. 46, No. 2, pp. 203-213, 1999. Available: http://www.ams.org/notices/199902/boneh.pdf

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