How Data Investments Can Help Business Leaders Stay the Course

All Hands on Deck:

A Broad Definition of Stakeholders

Successful data programs involve more than analytics and data science teams. They incorporate and empower functions across the organization, from business operations to financial planning to people operations. Data literacy initiatives reach further, including everyone from executives to operational employees in decisions around what data to collect, how to interpret it, and the best courses of action to take in response. Everyone brings unique perspective based on his or her role in the organization, and with broad engagement and contribution, the results of data investments help in faster decision-making, reduced risk, increased customer loyalty and employee satisfaction, and continued innovation.

Keep a Lookout:

Boosting Real-time Awareness

With rapidly changing economic and market conditions, real-time awareness of what’s going on in a business is a requirement. Waiting for end-of-month or end-of-quarter financial results may cause you to miss an opportunity to uncover, react or meaningfully respond to current dynamics. A trusted executive dashboard with key metrics, such as sales pipeline and product utilization, is often the first step in keeping a pulse on your business. But successful companies go further, backing up the dashboards with sophisticated analysis on key drivers and root causes. They build strong partnerships between business teams, data scientists, and business operations. Data scientists can help make sense of unexpected results, while business operations realign work to quickly address challenges and capitalize on new advantages. Over the long-term, investments in data quality and literacy help the business to recognize and respond to emerging trends. Comparing current results to historical benchmarks puts those insights into context so that executive teams can act on the data rather than debating what it means.

Stay Ashore or Set Sail:

Assessing Projects and Investments

In any economic environment, nearly all businesses are required to make investment decisions with intention and a high degree of confidence in the likely results. This is particularly critical when faced with turbulent market conditions. New proposals for headcount, technology, and marketing programs will face intense scrutiny, and in many cases existing spend will be probed as well. Scoping out new projects is notoriously difficult – from estimating time and effort needed to complete a project to qualifying the potential impact. Unknowns and less-understood factors often lead to overly optimistic forecasts. Often, data needs to be sourced from multiple systems and synthesized, both core competencies of a data and analytics function. While historical data does not always accurately predict the future, it can help establish a more reasonable estimate. We encourage teams to draw on historical data to better assess the reliability of new technology or supply chain partners, evaluate resource deployment, or understand post-implementation maintenance and to help project the investment required for a new project. In addition, past data on new customers and revenue, efficiency improvements, or changes in customer or employee retention can provide realistic bounds to the upside potential. Ultimately, any project proposal that arrives without supporting data should be sent back – or rejected.

Have Confidence in Your Crew:

Working Smarter

Faced with labor shortages and hiring freezes, many teams are trying to do more with fewer people. Having accurate, actionable data at their fingertips helps employees focus on the most important – and most urgent – opportunities and risks. Data provides insight into which prospects need an extra phone call or promotion to convert, when existing customers have changed behavior in a way that might indicate churn, and what candidates your recruiting personnel should target to meet staffing needs. Data-driven alerts help operations employees respond to supply chain issues, equipment maintenance and marketing campaign performance before small problems turn into larger ones.

Customers are also increasingly looking for data and insights that help them manage their businesses more effectively. We see this in spades across our portfolio companies, both in the products and solutions offered and in the way teams manage their own customer interactions. For example, the Klaviyo platform is designed to store customer data on behalf of Klaviyo customers – to build experiences across email and other “owned” channels and to measure the results in revenue, not just opens or clicks. StackAdapt’s solutions provide deep insights on drivers of customers’ campaign performance. Immersive Labs’ dashboards help its customers understand their own employees’ cyber readiness and assess an organization’s cyber competencies against industry frameworks. Whether delivered in-app or through an interaction with the customer success team, providing engaging and timely information to your customers creates the kind of positive experiences that make and keep them loyal.

Many organizations struggle to place an accurate value on the ROI of data initiatives – whether they be in analytics, data science or business operations. While the costs may be relatively easy to tally, the benefits can be less tangible, often showing up in quality decision-making, and the ability to be informed and ready to react rapidly to the market. Data teams and infrastructure are an essential foundation for understanding the business in real time, making informed investment decisions, and amplifying the impact of employees. Companies that can anticipate and respond to changes with their markets, customers, and employees will be best positioned to navigate challenging environments with the wind at their backs.

ABOUT THE AUTHOR

Cathy Tanimura is Vice President of Analytics & Data Science at Summit Partners. She works closely with the Summit team and our portfolio companies to help create and execute strategies that effectively use data and analytics to drive better decisions and build better products. She is the author of SQL for Data Analysis: Advanced Techniques for Transforming Data into Insights. Prior to Summit, Cathy worked at Strava, where she built an analytics and data science team focused on product, marketing and business development. Previously, she led analytics teams at Okta and Zynga.

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