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Businesses and organizations of all types have embraced cloud integration to transform data into business intelligence. The reason for this is simple: more and more business operations are happening in hybrid cloud — or even fully cloud-to-cloud – environments, and without proper tools to manage data in the cloud, data can become siloed, overlooked, or lost altogether.

It’s the ultimate Catch-22. As businesses grow, executives need to keep a close watch on operations — but that growth itself can blur visibility. Multiple teams, data sources, and silos of information can create challenges in determining who is doing what, where inefficiencies exist, and what improvements should be made.

If you’re a data leader at an early-stage or high-growth company, you’re in a unique position to promote data appreciation. Don’t waste your golden window of opportunity. Take this moment to institute best practices, promote good habits, and build the foundation for a data-driven culture. There’s no universal data strategy that would work for all organizations — wouldn’t that be great? — but there are pitfalls that all organizations should watch out for.

Three decades into the data revolution, my fellow technologists and I find ourselves asking an existential — and rather distressing — question: What happened to the promise of customer 360? The ability to get more customer data was supposed to fundamentally change the relationship between customers and brands. Companies were going to be able to offer targeted, meaningful engagements that would multiply average deal size and slash time to close.

OKRs have taken corporate planning by storm — and for good reason. As a system for organization-wide goal-setting, OKRs make executive KPIs tangible and actionable, not just for the leaders, but for everyone in the company. They have become increasingly common in all types of businesses because they are simple and effective. For the company’s data champion, they also offer an unparalleled opportunity to get everyone speaking a common language of metrics.

Globe Telecom, one of the largest providers of digital services in the Philippines, was operating in a saturated market with limited opportunity to expand. Any strategy for growth depended on nurturing customer relationships and fostering lifelong value with each customer. For Globe Telecom, getting customer data was never the problem — telecom companies produce terabytes of data every day.

To IT leaders, it’s obvious that data strategy deserves a special place at the table for any discussion about strategic business initiatives. However, for CMOs and CROs like myself, who must justify and weigh expenditures against bottom line impact, investing in customer data typically looks like a red-ink proposition.

Data may be everywhere, but it isn’t free. It takes a lot of work and infrastructure to turn raw data into useful insights. Research suggests that the cost of handling data is only going to increase, by as much as 50% over five years. The same source suggests that part of that cost comes from confusion — users may spend up to 40% of their time searching for data and up to 30% of their time on data cleansing. The issue here is data trust.