Highlights from New York Product Conference 2018
The recent product conference explored strategy, machine learning, blockchain, design systems, AR/VR, and more with New York’s leading product thinkers.
The 2018 New York Product Conference ran on November 10, 2018, expanding to TheTimesCenter for the event’s third year. The event brought together the New York product community of product managers, product designers, founders, engineers, product marketers, and others to learn about product management new and best practices, as well as reinforce relationships.
This year’s theme of Product Strategy bookended and threaded the day, which also included deep dives on community-requested topics strategy+brand, design systems, remote teams, machine learning, AR/VR, blockchain, and interviewing.
Biggest Takeaways
- Most product people don’t get product strategy right, all the way from individual contributors up to executives. Not only is product strategy challenging, but it’s also difficult to make time for.
- By investing in your product strategy you’ll put yourself ahead of most of your peers and greatly increase your chances of building sustainable companies delivering products users love. Product strategy thinking will also help you find better companies and get selected for jobs.
- Virtual reality, and blockchain are still nascent technologies most product people don’t need to know about.
- Machine learning and augmented reality technologies are also early, but are more broadly applicable to most product areas as features.
- Two other changes on the rise affecting product people are design systems, which product teams need to invest in to keep up with the pace of their industries, and distributed work, which companies and employees increasing expect to happen well.
- Product strategy needs to tie closely to the company strategy as well as that other functions, like marketing.
Product Strategy: Framing The Day
Brent Tworetzky opened the day with a framing of product strategy. From surveying a dozen product executives including those from ClassPass, Foursquare, Rent The Runway, Jet, Shutterstock, Atlassian, and more, we found:
- Product strategy is your product [goal] and the [path] to achieve the goal. While most people use different words for goal (e.g. vision, north star) and path (e.g. rules, resource allocation), the meanings all snap to goal + path.
- Most product people don’t do product strategy well, so say the surveyed product execs, and the NYPC audience. Share that does it well? Less than a third of product leaders, less than a quarter of product managers.
- Product strategy needs to be clear from the top, and often isn’t. If you don’t know your company’s product strategy, demand it. Else it becomes very difficult for anyone else in the company to get their strategy right
The Power of Brand and Product
Carolyn Tisch Blodgett, SVP of Global Brand Marketing at Peloton, shared lessons from Peloton’s history and product strategy, which has driven 80+ NPS, high 90s retention, and tremendous growth:
- Peloton’s goal is to create the world’s best fitness experience in the home. The brand, marketing, and product strategy have tightly aligned around this goal.
- Brand and product leadership are tightly aligned on strategy and major decisions, employees are onboarded to understand the power of both areas, both teams perform, share, and take action on user research. The two sides generate healthy tension to balance growth vs. authentic engagement, aspirational brand vs. low friction usability.
- The company focuses on tracking and improving metrics that show user love via engagement: frequency of exercise, frequency of opening the app, activity across the product.
- Product innovation has frequently been driven by user learnings, such as providing deeper music content and experience, moving class engagement away from rider-focused video to rider-to-rider light interactions (e.g. high fives), instructor types and programs.
The Rise of Design Systems
Catriona Shedd (InVision) interviewed Leland Rechis (Google Material), Evan English (Amex), Abigail Hart Gray (Google), and Laura Hahn (Priceline) about what product people need to know about design systems: rules and technologies to provide consistency of design experiences across an organization’s apps and websites. Key learnings:
- Design systems provide standardized design rules and templates, within design files like Sketch and in live code, to help organizations build experiences faster (e.g. don’t rebuild the button) and keep experiences consistent (e.g. automatically keep/update all buttons to the same color). Rules can include language, colors, fonts, and motion, also well as small items such as buttons up to larger items such as navigation bars and overlays.
- Google famously launched their design system Material in 2014, and since then several companies, especially larger and more tech-forward organizations, have released their own internal and external named design systems, such as Salesforce’s Lightning and Shopify’s Polaris.
- Benefits:
- [Value] By having shared design systems, designers focus more on unique and strategic product challenges than spend time rebuilding commodity components.
- [Speed] Designers and engineers can assemble webpages and apps faster. They can also collaborate more effectively by more clearly understanding each others’ intentions.
- [Consistency] Design systems help provide consistency, with less thought/stress, across all websites, mobile apps, watch apps, etc.
- [Culture] Design systems can focus an entire organization into the important of consistent, and then strategic design.
- [User expectations] Users increasing expect consistent, high quality experiences across a brand’s touch points. Without consistency, users can lose trust and even get confused about using a product. - Five years ago most organizations had policies but no teams or technologies for design systems, now it’s critical for organizations to invest people and technology into this platform. But organizations need to build up to design systems over time. Note that engineering has been building up operations for much longer than design has and took on a similar maturity evolution.
- Several panelists remarked that design systems are often considered for consumer experiences, but design systems must also be developed for enterprise products and internal tools.
Learning from Distributed Organizations
Linda Escobar (Alpha) interviewed John Allison (Customer.IO), Nikita Miller (Trello/Atlassian), Giri Iyengar (eBay), and Helen Millson (1stDibs) about the overcoming challenges and creating opportunities with increasingly distributed organizations. Key findings:
- While few organizations are entirely distributed (no office at all, everyone works from home/co-working space), many organizations are partially distributed (central HQ + some people who work from home or central HQ + multiple offices). For bigger organizations with many offices, it’s now common for individuals to work from offices but have their daily teams be in completely different locations.
- Benefits: recruit and retain great talent from anywhere; working from home creates an attractive work environment for people with flexible timing needs (e.g. parental obligations); office costs (though this benefit is lower than most would guess); the ability to scale an organization quickly through a larger hiring pool and no office to build out.
- Challenges: harder to build shared context and culture; not everyone can thrive in this more solo environment (especially earlier tenured employees); can be hard to understand what’s important.
- Learnings: a lot of work historically thought of as necessarily synchronous can be done separately/asynchronously; seeing each other in person semi-regularly is critical for team relationship, culture, strategy setting, and context building; getting the right tools helps, but it’s just as important to get everyone to use the tools rigorously.
- Must haves: overlapping work hours (ideally 4+ hours/day); meetings with a single remote person must be done with everyone individually online; good video conferencing; the ability to turn off messaging (else be bombarded all day); strong communications culture; good online whiteboarding/brainstorming tools.
Augmented Reality + Virtual Reality: What’s Coming When?
Jenny Fielding (Techstars) interviewed Sakina Groth (Magic Leap), Neha Singh (Obsess), Nate Beatty (IrisVR), Mike Podwal (Google), and Raj Advani (Viro) about the realities of Augmented Reality (AR)/Virtual Reality (VR) technologies, and what today’s product people need to know. Key findings:
- AR and VR break into more useful categories: AR headsets and wearables (e.g. Magic Leap, Microsoft Hololens), VR headsets/wearables (Oculus), AR smart phone apps (Snap filters), and VR smartphone apps (Google Cardboard). AR and VR can be blended together into an experience called Mixed Reality. Most people think of dedicated headset devices when they think of AR/VR, even though most AR usage is happening on mobile phones!
- Smartphone AR and VR is here today and in everyone’s pockets, while headset based AR/VR has a small device footprint. Smartphones are limited by device processing power and cellular bandwidth, while dedicated devices are limited by cost, standalone value, and non-standardization.
- The easiest place to enter is by adding AR features into an existing smartphone app — the software is easier to build, the hardware exists, and use cases are tied to things users are already doing. Google Android and Apple iOS are both investing in augmented reality development though Apple ARKit and Google ARCore.
- Emerging dedicated devices users are gamers. The broadest opportunities seem to be emerging in retail, education, healthcare, and manufacturing.
- The field of AR/VR is still very early, and it’s an excited time as a developer and supporting software platforms mature. There is more enthusiam for big adoption in AR, especially on mobile devices, through we expect to be surprised and delighted by vertical/industry special applications in AR/VR that solve major problems.
Evaluating a Company’s Product Strategy During the Interview Process
Dan Storms (XO Group) interviewed Rebecca Greene (Handy), Meagan Palatino (Instagram), Nate Stewart (Cockroach Labs), and Andrea Chesleigh (One Kings Lane) about how to learn about a company’s product strategy when you’re interviewing for a position there. The panelists collectively had interviewed and worked at many dozens of New York’s biggest tech companies and had the following lessons to share:
- A organization’s ultimate success is greatly shaped by its market opportunity and its product strategy to attack that market. Many people don’t think enough about a company’s success potential and choose companies that struggle for the success the candidate is hoping for when joining.
- Find more successful company by investing this extra time and discipline during your evaluation process. In doing so, you’ll also come across as a stronger, more prepared candidate!
- Understand the product by actually using the product, and speaker to other customers about their experiences and impressions.
- Understand the market by researching and testing competitors, reading analyst reports, listening to company earnings calls, and reviewing related business school case studies.
- Use your preparation to ask targeted questions when you interview, including
- what’s your product strategy (do they even know it?)
- what’s your value proposition to customers? What jobs to be done do you serve? And how does that fit vs. competition?
- what’s your business logic? How are you going to market? How are you attracting, serving, and retaining customers in a sustainable way?
- what are the key business model drivers, and how is the product strategy supporting a healthy business? Is the business model feasible? - Based on responses, you should expect that people answer the questions (many can’t) and that the answers make sense (they often don’t).
- Talk to current and former employees, not just your interviewers, to inform your preparation and understanding. If possible, talk to the organization’s investors too.
- Suggested readings:
Made to Stick (Heath & Heath)
Competing Against Luck (Christiansen)
Principles (Dalio)
Good Strategy Bad Strategy (Rumelt)
On Strategy (HBR)
The Innovator’s Dilemma (Christiansen)
Machine Learning
Noah Weiss, Senior Director of Product at Slack, built up Slack’s machine learning products and shared his thoughts on how to practically apply machine learning technologies in your products today:
- Machine learning means different things to different people. Noah describes machine learning as “training machines to use examples of history to make predictions about an uncertain future.” Fundamentally, turn relevant historical data into ways to better solve user problems today.
- Examples of useful machine learning: Spotify’s Discovery Weekly to find music you’ll like that you might not have heard before, Gmail (and iMessage and LinkedIn) pre-composed messages to speed up writing.
- Examples of machine learning gone wrong: shopping or video streaming services that show too many recommendations based on a one time unusual purchase or view. (Training an algorithm on too little data.)
- Machine learning can’t solve most problems, and struggles with open ended problems. But machine learning works well with specific use cases. Noah suggests starting small to add value where you can add valuable predictions, especially where there is existing data exhaust/history to learn from. If your product lacks user data history, it can be challenging to build a valuable machine learning product.
- Examples of machine learning in Slack includes personalized and smarter search results, as well as suggested channels to join/leave.
- Machine learning requires that a team be comfortable with the algorithm failing in unpredictable ways, so be prepared to give up some control of the user experience. Noah recommends matching your confidence in the machine learning algorithm results with the user interface/design of the results — e.g. call the results beta or list them to the side if less confident, and suggest auto-fill if more confident.
- Teams don’t need dedicated data scientists to get started. Your engineering partners can test with SaaS API providers such as Amazon Web Services or Microsoft Azure.
Blockchain for Product People
Ali Hamed (CoVenture) interviewed Nikhil Kalghatgi (CoVenture Crypto), John Dempsey (Chainalysis), Angus Champion de Crespigny (Cryptocurrency industry advisor, previously EY), and Kevin Wang (Orion) about blockchain technologies and what product people need to know:
- Blockchain is a distributed database technology, which can serve as the backbone of other applications.
- A coin/unit of monetary value can be assigned to a blockchain unit, but it doesn’t need to be.
- Bitcoin is a currency application built on top of blockchain technology with Bitcoin as the coin — this blockchain based currency is called a cryptocurrency, since cryptography is part of the technology. This poster child of blockchain technologies has grown since launching in 2010 and popped in 2017, along with newer cryptocurrencies Ethereum and Ripple. 2018 has been a pullback year for cryptocurrencies.
- The underlying blockchain technologies and services environment around those technologies is still very early, and many recent uses for blockchain haven’t been appropriate. While good for experimenting with and developing the the technology ecosystem, there haven’t been major product-market fits of the technology use at scale yet.
- When thinking about blockchain companies, consider three buckets:
- public blockchains (associated with a crypto component, e.g. Ethereum, Bitcoin, blockchains with a coin on top) — these are fully open and accessible, with minimal barriers to entry.
- private or permission blockchains — new products (often B2B) using the underlying blockchain structure, such as Walmart using blockchain technology to track food supply chains.
- the ecosystem of companies supporting the blockchain economy — companies doing forensics on the blockchain, exchange platforms (onramps for coin purchasers), companies that service blockchain. - The panel suggested being very careful about using blockchain-based technologies given the immaturity of the technology and the surrounding ecosystem, but did think that building the ecosystem was an excited space to develop for the next several years.
Strategy Frameworks
Gib Biddle closed the day with a talk called “Digital Disruption: The Good, The Bad, and The Ugly,” linked here. He suggested three product strategy frameworks and shared examples of using each:
Product Strategy 1: GLEe
Get big, Lead, then Expand.
- Get big → give people a step by step path of how to grow, get big on something
- Lead → lead an industry or change
- Expand → expand globally / growth strategy
This model suggests a sequential approach to building a successful organization. This model forces you to think big and think ahead, finding an initial beachhead.
Product Strategy 2: GEM
Growth, Engagement, and Monetization.
- Growth → grow accounts, grow revenue
- Engagement → retention
- Monetization → unit economics
This model articulates the three things an organization needs to focus on, but forces the team to choose which of the three to focus on, when?
GEM offers a test for alignment. How does a team prioritize GEM? Is everyone aligned? If not, the team will move in different directions.
Product Strategy 3: DHM
Delight customers in hard to copy, margin enhancing ways.
- Delight customers → Understand and execute on delivering user value.
- Hard to copy → Build a sustainable competitive advantage, e.g. apply economies of scale, network effects, brand, unique technology.
- Margin enhancing ways → Over time, find grow a healthier business engine on both the top line/pricing side and the bottom line/cost side.
The DHM approach provides a path to enduring value to sustainable competitive defensibility.
Thanks to Rose Pember and Dan Storms for help with this summary article!
