Lean Analytics 31

Conclusion: Beyond Startups

If all goes well, you eventually stop being a startup. You’ve found product/ market fit, and you’re scaling even as your growth slows to that of a big company. But hopefully you’re still analytical. Hopefully you’re still thinking in terms of learning, and continuous improvement, and demanding that data back up your opinions. Your startup has succeeded when it’s a sustainable, repeatable business that can generate a return to its founders and investors. It might take on additional funding at this point, but the purpose of the funding is no longer to identify and mitigate uncertainties, it’s to execute on a proven business model. Data becomes less about optimization and more about accounting. If there are “lean analytics” going on, they’re probably in new product or feature discovery, and look more like intrapreneur innovation. We started by saying that if you can’t measure something, you can’t manage it. But there’s a contrary, perhaps more philosophical, observation we need to consider. It’s a line by Lloyd S. Nelson, who worked at Nashua Corporation. “The most important figures that one needs for management are unknown or unknowable, but successful management must nevertheless take account of them.” This smacks of Donald Rumsfeld’s “unknown unknowns,” and as your company grows and achieves a degree of operational consistency, figuring out what you don’t know becomes a key task of management. Nelson’s point was that we often do things without knowing they’ll work. That’s called experimentation. But experimentation—for companies of any size—succeeds only if it’s part of a process of continuous learning, one we hope to have instilled in you whatever the size or stage of your business.

How to Instill a Culture of Data in your Company If you’re a leader—the founder of a startup, or a C-level executive in a large enterprise—you can turn analytics into a competitive advantage simply by asking good questions. Earlier in the book we said that a good metric is one that drives decision making. As a leader within your organization, demand proof through data before making decisions. Data doesn’t just lead to better decisions. It also improves organizational efficiency. You can create a flatter, more autonomous organization once everyone buys in to a data-informed approach, because rather than needing to propagate an opinion across the organization, you can let the facts speak for themselves. You can empower employees to make more decisions and take on more responsibility once they’ve got the data in place to support them. Create a culture of accountability, and then reward those who step up and deliver. Whether you’re in a leadership position or not, you can make your organization more data-centric. Here’s how.
Start Small, Pick One thing, and Show Value There will always be naysayers in an organization who believe instinct, gut, and “the way we’ve always done business” are good enough. The best thing you can do is pick a small but significant problem your company faces (take any single metric of importance, be it churn, percent daily active users, website conversions, etc.) and work to improve it through analytics. Don’t go after the most crucial issue your company is facing—that’s likely got too many cooks in the kitchen already (or worse, it’s mired in politics you don’t want to wade into). Instead, pick an ancillary issue, something that can add demonstrable business value but is being overlooked. This approach, if taken too far, can lead to silos within the company, and that’s a bad thing. Once you’ve demonstrated the benefits with one issue, roll out the process across all departments and product areas.
Make Sure goals Are Clearly understood To prove the value of an analytics-focused company, any project you take on needs to have clear goals. If you don’t have a goal in mind (including a line in the sand that you’ve drawn), you’ll fail. Everyone involved in the project needs to be aligned around the goals.

get Executive Buy-in Unless you’re the CEO and pushing this approach top-down, you’ll need executive buy-in. For example, if you want to improve the conversion of website visitors signing up for your free trial software application, make sure the person in charge of marketing is on board. This person’s buy-in will be critical in aligning goals, but also in driving the culture up and down the corporate ladder.
Make things Simple to Digest A good metric is one that’s easy to understand at a glance. Don’t overwhelm people with a firehose of numbers. They’ll get frustrated, and they’re also very likely to start looking at the wrong things, focusing on the wrong numbers, and making decisions without understanding what they’re looking at. Metrics can be extremely valuable, but used incorrectly they’ll lead down the wrong path. Remember the One Metric That Matters. Use that principle as a way of easing people into analytics and number crunching.
Ensure transparency If you’re going to use data to make decisions, it’s important that you share the data and the methodologies used to acquire and process it. Decisionmaking frameworks are needed so that your company can find repeatable strategies for the use of analytics (and lessen the “flying by the seat of our pants” approach that companies often take). Transparency (in both success and failure) is important for breaking down the data silos and people’s preconceived notions about analytics.
Don’t Eliminate your gut As we’ve said before, Lean Analytics isn’t about eliminating your gut, it’s about proving your gut right or wrong. Accenture Chief Scientist Kishore Swaminathan says, “Science is purely empirical and dispassionate, but scientists are not. Science is objective and mechanical, but it also values scientists who are creative, intuitive, and who can take a leap of faith.”* You can help push your company’s culture by making sure you balance people’s notion that instinct and gut are enough with small, data-driven experiments, proving the value of analytics while not completely eliminating the benefits of instinct.

Instilling change in any size organization takes time. You can’t expect a company to change the way it does business and makes decisions overnight. Start small, and find experiments you can box in easily and which generate measurable results quickly. Prove the value of analytics in moving your company’s KPIs (even a little bit), and you’ll be able to make the case for an analytics-focused shift. Use concepts like the One Metric That Matters and tools like the Problem-Solution Canvas to make analytics approachable and understandable for everyone, not just the data scientists. Get people focused on lines in the sand—measurable targets that everyone (including executives) agrees to—so that you can demonstrate results.
Ask good Questions There’s never been a better time to know your market. Your customers leave a trail of digital breadcrumbs with every click, tweet, vote, like, share, check-in, and purchase, from the first time they hear about you until the day they leave you forever, whether they’re online or off. If you know how to collect those breadcrumbs, you have unprecedented insight into their needs, their quirks, and their lives. This insight is forever changing what it means to be a business leader. Once, a leader convinced others to act in the absence of information. Today, there’s simply too much information available. We don’t need to guess—we need to know where to focus. We need a disciplined approach to growth that identifies, quantifies, and overcomes risk every step of the way. Today’s leader doesn’t have all the answers. Instead, today’s leader knows what questions to ask. Go forth and ask good questions.

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