Analytics is about to change—organizationally, technically, infrastructurally. Maybe even philosophically. It may sound like empty futurism, but as with all things at Mixpanel, there’s data behind it.
Product lies at the heart of most innovative companies doing business today. After all, strategies and business models change based on how a product performs. And seeing as Mixpanel’s launch in 2009 invented modern product analytics, we believe we’re qualified to talk about the state (and future) of how companies analyze their data and make business- critical decisions.
But first, a very quick history lesson: For a long time, buying power in IT- related decisions was located in centralized IT departments. Stakeholders lacked power in and around information technology. They had to route requests into a never-ending queue.
And then information technology exploded. Data storage shifted to the cloud. A slew of SaaS applications arrived. Professionals ditched their company Blackberries, recentralizing their favorite applications on iPhones. Laypeople got comfortable y and began to own tech in the workplace.
By 2013, 61% of enterprise technology projects were funded by business leaders, instead of their IT counterparts, according to IDC. That means doers want to choose which applications they use for vital business functions. And this isn’t accidental. Market forces and technological progress had converged to drive a more efficient model for IT decisions.
We think a paradigm shift like this is coming in analytics. Through the power of analytics, employees with no formal analytics training will begin to own and actively consume data relevant to their roles, freeing data scientists, analysts, and engineers to pursue more rigorous experiments.
This eBook calls on the examples of some early movers to show enterprises how they can navigate this new landscape competitively. In these pages, you’ll learn about:
• Startups that successfully pioneered a data for everyone approach, enabling laypeople and data wonks to level-up their capabilities,
• How machine learning will become more essential to cutting-edge companies and become a differentiating factor,
• Why it pays to ignore “best practices” and throw manpower at the newest challenges of customer engagement,
• How fixing outstanding data challenges in spaces like Internet of Things can put your business ahead in a world eaten by so ware.
In today’s changing economy, predictability and profitability are the most important part of any investor’s portfolio. As a result, analytics isn’t a small piece of the business anymore. It’s front and center.