5 ways data can help your company navigate the bear market

Data Culture
4 min readJun 30, 2022

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By Caroline FitzGerald, CEO @ Data Culture

Photo by Tackey on iStock Photo

In the bear market of 2008 data infrastructure was in its infancy. Companies relied on costly, siloed data storage and nascent analytics solutions without sophisticated capabilities (e.g., Excel). To extract even minimal insight from data required considerable human effort. In this environment, leaders unsurprisingly viewed data spend as a ‘cost center’ and naturally reduced spending and investment when the market turned.

Today, the picture is very different. Increasingly, companies see data as a source of measurable value. Moreover, the return on investment for data solutions has exponentially increased thanks to advancements in cloud infrastructure, automation solutions, and analytics tooling. Unlike 2008, to navigate the current bear market, companies are ‘doubling down’ on data as a strategic differentiator, essential for competitive advantage. (credit: insights gathered from conversation with Neil Assur, founder Birch Biosciences, former Associate Partner affiliated with McKinsey’s Digital and Sustainability)

This poses an interesting dilemma for companies, as they look to control spending and find cost efficiencies, often the investments needed to ensure future growth are sacrificed. We’ve compiled 5 recommendations on ways data can help your company navigate the bear market:

1.) Develop a holistic KPI scorecard. User growth is always relevant, but in a bear market, it’s a myopic indicator of business health. The KPIs to guide your journey will need to be more sophisticated, drawing on data from multiple sources — finance, sales, customer service, product, operations, and marketing. It will be more important than ever to get data out of silos, develop a set of shared metrics, establish good data governance, and enable business users to leverage data in their everyday work. We are seeing companies take this approach earlier and earlier, made possible by new pricing models for data products that mean easier entry points for Series A & B companies. Unlike the 2008 bear market, we now see the most competitive, high growth companies, investing earlier in data products that enable this approach.

2.) Build the foundation for effective experimentation. Strategies that have worked in the past may have the opposite effect in today’s market. The companies who can harness their data to test pricing, product optimizations, logistic/operational changes, customer success initiatives, etc. will have an advantage over competitors with less data-driven decision-making power.

Photo by Tumisu from Pixabay

3.) Manage data infrastructure costs. There has been major innovation since 2008. A vast ecosystem of data products designed for specific use cases has emerged. Now is the time to audit your stack to ensure it’s optimized for your business needs. Among other cost-saving strategies, optimizing your warehouse environment and addressing cloud cost management can be huge wins for reducing recurring costs for years to come.

4) Establish a data culture. Changing human behavior is notoriously difficult, but psychology research suggests transition periods and major events are among the most opportune times to introduce new mindsets and behaviors. The bear market is both a transition period and a major event. Leaders can capitalize on this moment of heightened motivation to establish new norms that embed data into decisions, interactions, and processes. Your team is looking for a way to have agency when things feel out of control. Equipping them with the mindset and tools to leverage data meets both a business and a human need.

Photo by Annie Spratt on Unsplash

5) Leverage fractional data talent. Adding to the challenge of these times is a highly competitive market for recruiting data talent. Couple this with hiring slowdowns/freezes, and executing the initiatives described above can feel daunting if not downright impossible. Now is the time for a flexible approach to data talent that saves time and money without sacrificing quality or strategic impact. A Fractional Data Team makes it possible to have a first-class data team for a set period of time. Compared to [temp] staffing agency solutions, a Fractional Data Team is a group of senior data practitioners adept at working together, advancing data strategy from a holistic perspective, providing expert advice on tooling selection, and applying best practices to implementation. The project-based approach taken by Fractional Data Teams can also de-risk data initiatives by establishing clear scope and deliverables upfront, enabling continuity during execution, and containing costs via fixed project fees.

All this to say, while a bear market presents several challenges for companies today, it also creates the conditions for a more strategic activation of data. It forces a higher level of intentionality and scrutiny that can ultimately lead to even better results at a lower cost. Our Fractional Data Team at Data Culture is ready to meet this moment with you. Reach out if you’d like to set up a conversation.

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Data Culture
Data Culture

Written by Data Culture

We help organizations build data capabilities and get value from their data.

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