Great Ideas Don't Always Make Great Products - Jonathan Rivers' Presentation at Health 2.0
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The presentation that accompanied 3Pillar CTO Jonathan Rivers' talk at Health 2.0 in Santa Clara, CA on September 17, 2018. Jonathan covered 3 core tenets of building successful digital products in the healthcare space: making data-driven design choices, placing a relentless focus on the customer, and minimizing time to value.
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Great Ideas Don't Always Make Great Products - Jonathan Rivers' Presentation at Health 2.0
- 1. GREAT IDEAS DON’T ALWAYS MAKE GREAT PRODUCTS Jonathan Rivers Chief Technology Officer
- 2. DIGITAL PRODUCTS: BETTER PATIENT CARE
- 3. 3 BRILLIANT IDEAS & ALGORITHMS Ideas and algorithms may not make good products.
- 4. WHEN GOOD IDEAS FAIL CIRCA 2000
- 5. WHEN GOOD IDEAS FAIL JUICERO
- 6. THE PATH A play in three acts. TO VICTORY
- 7. CHAPTER ONE: IT’S NOT ABOUT YOU. IT’S ABOUT THEM.
- 9. THIS ABOVE ALL... The digital generation has high expectations. KNOW THY CUSTOMER
- 10. CHAPTER TWO: IF YOU DON’T HAVE DATA, IT’S JUST A HUNCH.
- 11. DATA-DRIVEN Maximize the parts they’re actually using. DESIGN
- 12. IDEA VALIDATION IS NECESSARY Leave the building.
- 13. MACHINE LEARNING FOR IMPROVED PATIENT OUTCOMES Never stop learning.
- 14. CHAPTER THREE: IF YOU AIN’T FIRST, YOU’RE LAST.
- 15. MINIMIZE TIME TO VALUE Strike a balance.
- 16. DOLLARS ARE THEY STACKED? Doubt it. If so, call me.
- 17. COMPETITORS WILL FOLLOW And that’s okay.
- 19. SPEAKING OF COPYING BE ORIGINAL! It’s the only way to build authentic products.
- 20. GOT AN IDEA? SO WHAT? Customer Focus. Data Driven. Time to Value.
Editor's Notes
- Digital healthcare technology aims to promote personal healthcare, enhance relationships between patients and their physicians and improve workflow in healthcare businesses. Systems are modernizing. These innovations include: Personal Fitness Tracking Chatbots to Explain Lab Results Vast quantities of health data online Virtual Assistant for Patients and Clinicians
- Unfortunately, brilliant ideas do not necessarily translate into successful digital products. True success in health technology is defined by solutions that promote personal ownership in health and wellbeing, enhance the patient-provider relationships, and improve clinician workflow to create a better healthcare experience for all parties involved. None of that is going to happen if they are not coupled with a relentless pursuit to serve the customer. It’s essential to offer the experience customers want and need. All an Idea is, is a starting point. It’s the genesis, or the jump off. Its a method for solving a problem All you have done is solved a problem, or identified a need. Frankly, that's the easy part Getting it to market is going to be the hard part And even if you do that's no guarantee of success What will make you successful? A focus on UX, empirical data-driven decisions (say goodbye to charismatic design) and building the right thing in the right order
- AskJeeves (NLP Search Engine) Perfect example of a great technology poorly productized Let down by its search engine component Failure to tie the two together
- Juicero $120m raised $400 machine 4 tons of pressure You could squeeze it yourself fail
- Winning is simple Make Data Driven Design Choices Relentless focus on the customer Minimize time to value
- What lets you win on the space are customers who are successful. You get that by thinking about them, not about yourself. There is a reason Amazon leaves a chair empty in their meetings It’s not about what you want to build It’s not about why you think it’s good Pygmalion lesson. Don’t fall in love with your statue It’s about helping your customer be successful
- 1. Useable. Security technology needs to be used. 2. Useful (does the word “helpful” work here?) Algorithm for customers. 3. Desirable- Website example. Table stakes. Usable - Your Product has to work. It needs to be easy to use. If it’s not your customers will get upset and leave. If it’s too cumbersome, they will leave (more words) Useful - It has to solve a need. Novel and Cool done work for long. How big is the problem it solves? That’s the impact. Reference Segway again Desirable - Back in the day that meant pretty. We had agencies focusing on design rather than UX. Desirable is partly design and look, but also FEEL. In mobile, the feel of an app is enormous. Do your customers WANT what you are building, or do they feel forced into it? Behavioral change requires engagement. Engagement requires desirability These three things all reinforce each other.
- All applications are now judged by best of breed consumer applications. This is expected in all enterprise implementations. Why does it matter? Engagement is needed to change behavior or learn Engagement is needed to want to use the system It needs to work in a way they are comfortable with for threat response when time counts The thing about the enterprise space is that many of the products (especially on the digital side) are B2B2C. I mentioned it before, the buyers of the systems, often aren’t the actual audience. Products that do not engage audience drag down business performance metrics and reduce the viability of the product. The notion that the buyer and the audience are different, and the engagement of the audience is more important than your customer seems counterintuitive, but essential in today’s marketplace. A highly engaged customer will demand products from their service providers
- I harp on this a lot My teams get mad when they come to me with ideas, and I ask what data they have to back it up. If you don’t have data at best you have a hunch, at worst you have an opinion. Who here is building a product? Who is experiencing the loudest or most important voice making the decisions? Is that ok? This is computer science, not art class.
- There is the potential to have the data you need to make decisions if you build it into your products. In many cases there is substantial data there already about your customers that most businesses do not know how to utilize. Reporting on, and socializing the usage data is what is going to lead to more successful product design. Building more of what people are using, how that trends over time, and how engagement strengthens and wanes is the cornerstone of data-driven design. Analytics need to be baked into everything, including your application. If you don’t know what parts of the application your customers are using, how do you know what to develop? 4 feature example. Which to develop? What if one single feature got 75% usage? What if it was 90%? Would you develop the others? Should you put more time into them? Do you know why? With AI you need to add explainability. Why did you make that decision?
- Ideas need to be validated. Now here is the thing: Idea validation isn’t going in an echo chamber Hey, Scott? Hey, Sue? What do you think? You’re right, boss! It’s going out and talking to the people who use the software day in day out and ask what they think. Beware the Exec, Beware the SME 7-10 touches to know if you are on the right track
- Still run with the SmartDX story, it plays well. We had a customer come to us with an idea. He wanted to build an algorithm His idea was #tottallysweet he wanted to use AI to determine what possible scenarios during surgery to inform the decisions people in the OR would use. He came to us to help build a pitch and a prototype. We took the idea and took it to his peers working in the field. What we found is that 70% hated the idea. Most of them said they would never use it; they would never trust the computer’s results (this for the record is a common problem in ML assisted builds) The more significant learning is they told us it won’t work. The data needed to feed this beast was not centralized. Most of it was private, most of it was non-structured, and even more of it was handwritten. He has pivoted his startup to solve the data problem
- Chapter 3. We talk about stalling out is a critical problem for companies with a new product introduction. You need to get to market fast, capture value, innovate and iterate. Software in a repository has no value. It makes no money, and you learn nothing from it, other than how to hold a retrospective.
- Time is linear Time is finite While we can go get more money, we can never get more time Order. Real-world evidence must be gathered to justify success at scale. In order for digital health products to make the leap from novelty to necessity, product developers focus on driving patient engagement in real-world settings. Engagement will require taking lessons from other industries, creating products that are tailored to the correct audience. They are going to need to be sequenced for value. Which markets first?
- Stack of Dollars Imagine a stack of dollars on a table. Each decision you make takes a dollar of the top. If you don’t make decisions that put dollars back on faster than you take them off….. Well….then you lose.
- Once the idea is out there, it can be copied. It can be riffed on. If it’s a new take, or a new idea, it’s a race to market. You can also bet the blanket providers will be adding it to their suite either through development or acquisition. Time to market matters.
- Idea and take their slice. Casio, Garmin, Samsung. Wi-Fi Watches. Fossil.
- Don't do it You don't know why your competitors made that feature decision They didn't necessarily validate their ideas You might not have the same buyers Remember when I talked about idea validation? Can’t build on a list. Your customer may not be theirs.
- You’ve got an idea. So what? That’s not the leading indicator of success. According to Bill Gates, it was timing. Now luck isn’t a business strategy, but building good products is. If you take anything away from this it’s this: (Customer) UX matters. A poorly designed product is going to fail. Data-driven development will save you time and money ...and that while time to market isn’t everything, getting something usable into the market quickly, is.