3 Ways to Use Data to Increase Your Profits

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is the new oil” is perhaps the most used expression in over the past 15 years – although it does have some merit as an analogy. Data itself, like unrefined oil, has no underlying value or utility. But when refined by analysis and data has the potential to transform businesses and ultimately the global

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Like oil, however, data has the potential to pollute entire ecosystems through biased modeling, lack of regulatory oversight and the operational overhead needed to turn the data into something useful.

All things considered, data can and should be a net positive for organizations that strategically plan for creating value from the data they generate natively, as well as data they access through data collaboration and commerce tools.

Data has an almost infinite number of use cases that can vary wildly from for the organization, but there are some core principles that can help you improve your business and create value through data.

Related: 8 Ways Data Analytics Can Revolutionize Your Business

Retrieve and save

To stick with the oil analogy, data is only valuable if you can get it out of the ground and keep it somewhere† Nearly every modern business generates untold amounts of data, but often the data itself is volatile, meaning it isn’t considered important enough to be stored anywhere. The thought process usually sounds like “we don’t need this data right away, so let’s not spend the money it costs to store it somewhere.” This logic turns out to be wrong for two reasons:

  1. Storage is cheap. Using S3 allows you to store a gigabyte of data for about two cents. Those costs can get even lower if you use a less flexible storage tier. For most companies, the total cost of “storing everything” won’t be a meaningful part of their business expenses.
  2. You can’t go back in time. Even if there isn’t a clear use case for data today, it doesn’t mean there won’t be tomorrow. In addition, the value of data is often determined by a longitudinal analysis of the data, which means that if you wake up one morning and wish you had kept the data, you may have to wait months to collect enough to make it useful. .

Even the brightest product managers, engineers and analysts can’t predict the future, so companies should focus on preserving as much optionality as possible by storing every possible bit they generate.

Related: Any business can work more efficiently with better data

Acquisition and enrichment

First-party data, that is, data generated directly by an organization, has always been considered the gold standard for data. And although the origin and quality of the data have stronger guarantees than non-directly collected data, it is often not enough to build a data-driven organization.

An interesting anecdote proving this point can be seen in the form of large technology businesses (, etc.) open sourcing many of the artificial intelligence models they have created over the past decade. This shows that these organizations believe their strength and competitive advantage comes not just from the models, but from the data they input into those models. Your average company that doesn’t have data assets on the scale of a FAANG company can’t hope to get that much value from those models.

To combat that, organizations must look to strategies to acquire new data and enrich their first-party data assets to build a pool of data that can be used downstream to fuel the business.

Related: 4 steps to become a data-driven company

Top-down organizational alignment

Data teams are widespread in many organizations. Each business unit, division or functional area can have its own data group. One works in marketing, the other in finance and the other in the supply chain

This approach often results in silos of data, overlapping data mandates, and a general lack of best practices across the organization. In the past five years, we have begun to see chief data officers being appointed within organizations to help solve this challenge. Just as a chief human resources officer ensures that hiring, hiring, and cultural practices are not disjointed within an organization, a chief data officer can play a similar role while also ensuring the company adheres to its data governance and security mandates.

Ultimately, it’s fair to say that “data” is not a strategy. Data should be seen as a tool that, when collected, organized and enhanced as part of a broader strategy, can transform businesses large and small.

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