How to run your Library like a Startup

Editor's Notes

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• #4: (MJ & Helen) Intro: Helen UTM Institute for Management and Innovation; MaRS; etc. Intro: MJ UG Library; Course Instructor for Entrepreneurship; etc.
• #5: (MJ) Agenda Too difficult to cover everything on this topic Our strategy: five simple strategies to run your Library more like a startup This session is an opportunity to think about different approaches We want this to be thought-provoking – save time for discussion at the end
• #6: (MJ) Objectives Introduce basic principles of startup thinking Suggest practical steps to get started Invite discussion on startup thinking in libraries
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• #8: (MJ) Libraries are NOT Startups We don’t have the same revenue model or profit motive We have institutional constraints and complexity (i.e. established norms) We are established organizations (i.e. we’re not just starting up) We have legacy systems & structures (i.e. inherited baggage) We have to negotiate the analog-digital divide (i.e. we can’t be purely digital)
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• #10: (Helen) The Case for Startup Thinking in Libraries We operate with limited resources We experience conditions of uncertainty We need to respond to and anticipate change Our staff are committed to the mission of the profession We build/support platforms for users to do more of what they want
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• #13: (Helen) Entrepreneurs are adrenaline junkies with a high-tolerance for risk Not true: serial entrepreneurs adopt processes for reducing risk
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• #15: (Helen) Entrepreneurs rely exclusively on their intuition Not true: serial entrepreneurs commit to evidence-based processes
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• #17: (Helen) Entrepreneurs emerge from their garage with perfectly formed ideas Not true: serial entrepreneurs commit to iterative improvement
• #18: (Helen) Learning Organization In essence: Startups are committed to learning and discovery Learning what works (and what doesn’t) Discovering what people want (or don’t want) Libraries foster learning and discovery for our users BUT the best libraries foster learning within their organization Our premise: startups offer engaging approaches that we should translate for our context
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• #21: (MJ) 1. Focus on Understanding the Problem Startups try to understand the root problem that customers face They talk a lot about user pain – and spend a lot of time & energy diagnosing that pain What are users trying to do and what is blocking them or making it difficult to do X, Y or Z They dive deep into the problem with empathy They design a solution that suits based on what they learn To truly focus on the problem, we need to stop looking for solutions that fit our view Too often this leads to solutions that we like, that work with our systems, that solve our inefficiencies We need to adopt the customers’ mindset and stop making assumptions about how they think or what they experience
• #22: (MJ) How to Focus on the Problem Get out of the building Listen more, talk less Find data first hand Make customer interaction a regular part of every process Go to where their users live – they seem them at work, at home, understand their workflow Gather and evaluate feedback regularly Seek out non-users Determine why they aren’t using the service or coming to the library Find out how they are solving the problem instead
• #23: (MJ) Key Concept: Pivot A fundamental change in strategy based on learning Because startups admit that they don’t know everything and don’t invest as much up-front, they can change more easily and rapidly After a pivot, the startup has a number of new untested assumptions or hypotheses that need to be tested
• #24: (MJ) Be prepared… To be humbled People won’t see the need as you see it They often don’t see the value in what you’re offering They have lots of opinions about why your product is bad Remember: Don’t get defensive, honest feedback is essential to getting to the root of the problem
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• #26: (Helen) 2. Build products for the few (at least at first) Startups don’t have a lot of resources, so they can’t build for everyone They focus on one or two key groups They choose groups that are most likely to see value in the product and who are relatively easy to target or sell to If the effort fails it only fails with a small group of people If you build for everyone from the outset, you might please no one You might produce a bland solution that doesn’t excite anyone You might invest too many resources in an unproven idea Start small with a few users - once you have traction with your idea, you can scale your offering
• #27: (Helen) How to build products for the few Select target customers who are already familiar with you It is easier to start with segments of your customers that you know well (and who have some knowledge of your services) It’s also easier to access these people what they think you need more information Find early adopters Who really needs your solution? Who is most likely to overlook any early bugs or inconsistencies?
• #28: (Helen) Key Concept: Segmentation This can be hard for libraries, but we need to break down large groups into smaller segments with easier to define needs By defining the needs it becomes easier to build something that works for the segment The hope is that these early adopters will love what you’re doing so much that they’ll become your best sales people AND you can get them hooked on what else you offer
• #29: (Helen) Be prepared… For pressure to increase scope Libraries have a cherished value for being open and accessible to everyone BUT those egalitarian values get us into trouble when we think that everything we build has to be for every possible customer Remember: Increase scope and scale, after you’ve validated the idea with customers
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• #31: (MJ) 3. Build-measure-learn Startups prefer an iterative design approach Instead of launching a fully featured product, they launch a barebones service to see if there is any interest Then they watch what happens They take what they learn and improve it along the way Iterating to a better finished product Too often we write a big project plan, find the money and time, build the project, then when we launch it no one uses it (and we’re out of resources to fix it)
• #32: (MJ) How do you iterate Build successive prototypes Prototypes help make your ideas tangible They are easier for people to respond to – so you learn so much more Monitor user behaviour Once you launch a prototype or put it in front of someone, watch what they do The aggregated patterns of user behaviour will tell you whether you’re on the right track or not
• #33: (MJ) Key Concept: Minimum Viable Product Launching a product with only the features required to make it work Getting something to market faster Develop new features only if there is demand More affordable approach to development – customer-driven
• #34: (MJ) Be prepared… To get comfortable with imperfection Prototypes are not pretty or polished Librarians are closet perfectionists – we need to drop that approach Where you start is never where you finish – but you have to get your product/service out into the hands of people Remember: The long view is more important than first impressions– every prototype is a step toward a successful product
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• #36: (Helen) 4. Monitor key metrics Startups collect all kinds of data, but they watch a few key metrics They figure out which metrics demonstrate impact (e.g. adoption, retention, sign-ups, time on the site) They also look at these very frequently and adjust their product or service appropriately We need to use real-time data more frequently Data should be more like a heartbeat – not an annual physical Continuous improvement – not just cumulative analysis Every system we have gathers data, but which metrics actually show that we’re doing the right things?
• #37: (Helen) How to monitor key metrics Select the key metrics Choose data that show the greatest impact of each product and service Monitor data regularly Visit the stats on a daily or hourly basis Draw connections between the user behaviour and changes that you’ve made to the product/service
• #38: (Helen) Key Concept: Dashboarding Actively tracking key metrics to monitor the health of the business These dashboards would be open and transparent They would communicate clear measures of success Data is refreshed at least once a quarter, if not more often
• #39: (Helen) Be prepared…. To discuss data Quantity does not equal quality, but quantity is important to tracking momentum Conversations around data and what they mean to the organization are essential Remember: The data provides the evidence for you to pivot or proceed
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• #41: (MJ) 5. Articulate your value Startups tend to start with value They communicate the benefit(s) they generate for users They talk about why customers should choose their product/service over others in the market They are precise about what they offer (this focus keeps them on track) Answer the question in the customer’s mind: “What’s in it for me?” Value gets at higher order motivations (e.g. save time, money, effort, etc.) Instead of focusing on details, or features that we think are essential, we need to get to the root of the solution
• #42: (MJ) How do you articulate your value Align your value to each segment Recognize that each customer segment wants something different, so adapt to them Create different value statements for different groups Internalize your value Make sure your staff/team can clearly articulate what the product/service stands for Building consensus among staff is crucial to consistency
• #43: (MJ) Key Concept: Value Proposition The bundle of services and products that make your offer compelling (and unique) Value Propositions may vary for different customer segments (e.g. immigrant populations will use a public library for different reasons than children or business professionals) Knowing the value proposition for every customer segment is the key
• #44: (MJ) Be prepared… For disagreement Articulating value in a way that staff and customers understand it is very challenging The words which resonate with staff will seem foreign to customers (and vice-versa) Remember: without a clear value proposition, the product/service will feel unfocused
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• #46: (Helen) Five suggestions (review) Focus on understanding the problem (don’t jump to solutions) Build products for the few (don’t try to satisfy everyone) Iterate based on what you learn (don’t build it, then forget it) Monitor key metrics (don’t ignore the data) Articulate your value (don’t assume your customers understand it)
• #47: (MJ & Helen)