Powering Advanced Analytics

Why investing in a data mature organization matters

BY RYAN HARRINGTON

WHO ARE MY CUSTOMERS? Where are they located? What communities share characteristics with them? Which potential customers are likely to purchase my product? Can I recommend other products for them to purchase?

These challenges, and so many others, represent the types of questions that an organization might want to answer about who they serve. Empowered with answers, organizations can make strategic decisions about how to grow and understand the way they impact the communities they serve. Fundamentally, addressing these challenges requires data—both qualitative and quantitative—about customers, their purchasing habits, and beyond.

As organizations begin to unlock the power of using data for strategic decision-making, they often begin by considering descriptive questions—“what happened?”, “who made the purchase?”, “how many items did we sell?” Descriptive analytics questions allow us to understand what occurred in the past and what is happening in the present. Further, descriptive analytics allow us to establish baselines by which we can strategically define new metrics for success.

As organizations grow their data savviness, they will begin to consider more advanced questions. They consider predictive questions –“will a customer churn?”, “will a lead convert to a customer?”, “can I predict demand one year from now?” While descriptive analytics allow us to answer questions about the past and present, predictive analytics allow us to answer questions about the future. This is the realm of advanced analytics, which includes concepts such as statistical modeling, machine learning, and artificial intelligence.

Answering predictive analytics questions requires an organization to have the appropriate building blocks in place to support this work. It requires that organizations have considered—and invested in—their own data maturity and commitment to data-driven decision making.

Data maturity is a concept that covers the gamut of technical capability and strategic thinking of organizations. Data mature organizations— whether they are for profit or nonprofit institutions—tend to have several common characteristics:

• They use data to continuously inform decision making. Data is not simply used for reporting but to drive strategy.

• They foster a data-driven culture across the whole organization. This culture doesn’t live in small pockets in the organization, but rather is a language shared by everyone.

• They implement modern data architecture that supports their goals. Their data isn’t stored on spreadsheets or in filing cabinets; it is integrated into a warehouse that allows all teammates to have their needs met.

• They constantly seek new sources of data to incorporate into their practice, building upon their own internal data and considering third party data sources.

• They utilize advanced analytics techniques—like machine learning and artificial intelligence—to drive decision making at scale.

As these building blocks are progressively implemented, data-mature organizations position themselves to strategically utilize data to drive decision making across their teams. Investing in data maturity creates a positive feedback loop. An organization with a data-driven culture will ask continuously more sophisticated questions and seek to automate decision making. Investments in modern architecture make it easier to answer these questions and support advanced analytics techniques.

The Data Innovation Lab at Tech Impact partners with mission-driven organizations to use data for social good. In this process, the Lab works with its partners to assess their data maturity and ensure that the building blocks are in place to support statistical modeling, machine learning, and artificial intelligence to address their challenges. The Lab believes that all organizations—whether they are for profit or nonprofit—can better serve their communities by embracing data-driven strategies.

If you are a mission-driven organization that wants to use data more effectively, let us know. We’d love to hear from you at techimpact.org/services/data-lab.

Ryan Harrington is the director of strategy and operations with Tech Impact’s Data Innovation Lab.