expressed opinion entrepreneur Contributors are their own.
“Data is the new oil” is probably the most overused expression in business 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 improved through analytics, machine learning and artificial intelligence data has the potential to transform businesses and ultimately the global economy.
However, like oil, data has the potential to contaminate entire ecosystems through biased modeling, lack of regulation, and the operational overhead required to turn data into something useful.
All things considered, data can and should be a net positive for organizations creating a strategic plan for how that plan creates value from the data they generate locally and from the data they can access through data collaboration and business tools.
Data has an almost unlimited number of use cases and can vary widely from organization to organization, but there are some core principles that can help you enhance your business and create value from data.
Related: 8 Ways Data Analytics Can Revolutionize Your Business
collection and storage
Sticking to the oil analogy, data is only valuable if you can dig it out of the ground and store it somewhere. Nearly every modern enterprise generates a myriad of data, but the data itself is often ephemeral, meaning it is not considered important enough to be stored anywhere. The thought process often sounds like “We don’t need this data right away, so let’s not pay to keep it anywhere.” This logic turns out to be wrong for two reasons:
- Storage is cheap. With Amazon S3, you can store 1 GB of data for about 2 cents. These costs may be lower if you are using a less flexible storage tier. For most businesses, the total cost of “storing everything” won’t be a significant part of their operating expenses.
- You can’t go back in time. Even if there is no obvious data use case today, that doesn’t mean there won’t be tomorrow. Also, the value of data is often driven by longitudinal analysis of the data, which means that if you wake up in the morning hoping to save it, you may have to wait months to collect enough data to be useful.
Even the smartest product managers, engineers, and analysts cannot predict the future, so businesses should focus on preserving as much optionality as possible by storing every possible bit they generate.
Related: Every business can work more efficiently with better data
collection and concentration
First-party data, i.e. data directly generated by an organization, has always been considered the gold standard of data. While there are stronger assurances about the provenance and quality of data than indirectly collected data, it is often insufficient in building a data-driven organization.
An interesting anecdote proves this, the big tech companies (Facebook, Google, etc.) open sourced many of the AI models they created over the past decade. This suggests that these organizations believe that their strength and competitive advantage come not just from the models, but from the data they feed into those models. Ordinary companies without data assets the size of FAANG companies cannot expect to extract as much value from these models.
To address this, organizations need to consider strategies for acquiring new data and enriching their first-party data assets to build a data reserve that can be used downstream to help drive business growth.
Related: 4 Steps to Becoming a Data-Driven Business
Top-down organizational alignment
Data teams are widely dispersed across many organizations. Each business unit, department, or functional area may have its own data group. One works in marketing, another works in finance, and the other works in supply chain management.
This approach often results in siloed data as well, overlapping data tasks, and a general lack of best practices across the organization. Over the past five years, we’ve started to see the appointment of chief data officers within organizations to help address this challenge. Just as the chief human resources officer ensures that recruiting, recruiting, and cultural practices are not disconnected across the organization, the chief data officer can play a similar role while ensuring that the company adheres to its data governance and security requirements.
In the end, to be fair, “data” is not a strategy. Data needs to be seen as a resource that, when collected, organized and enhanced as part of a broader strategy, can transform businesses large and small.