By next year, the amount of data that has been created in total will be somewhere in the region of 40 zettabytes (40 trillion gigabytes), with a great deal of this created within the last couple of years. Your business is of course contributing to this “global datasphere”, and at an accelerating rate.
Yet, with 95% of businesses needing to manage their unstructured data, and more than half (57%) suffering because of slow or poor access to data, it’s clear that it is not being used to its fullest potential.
Accessed and used correctly, data holds all the information you need to meet and achieve your organizational objectives. It can allow you to make improved, data-driven decisions across every business function. It can enable you to understand what your customers need, want, and may desire in the future. Data can help you deliver smarter products and services, tailored to individual requirements. It can enable you to streamline business processes and operations.
For some organizations, like Uber and Airbnb, the monetization of data is their entire business model. But even for other businesses, who do not consider data as their primary reason for existence, it is still one of their biggest and most valuable assets.
Data on its own, though, is fairly useless. It’s how you understand it and use it that can have an impact.
It’s a little like standing in the middle of a city library. You know that all the information you require is there, but you don’t know in which books, where to find them, and how many books you’ll have to read in order to learn everything you need to know.
For most businesses, it gets even more complicated than that. If you consider that each channel through which your company collects and creates data (such as your website, your social channels, your operational systems, and so on) is likely to be separate, or siloed, then that means the data you seek could be in an uncountable number of books, across dozens of libraries.
To be able to leverage and use this data, you’ll need a strategy. And this means establishing how it needs to be governed: what data you need, how you’ll store it, how you’ll access it, and how you’ll be able to analyze it. And, perhaps most important of all, how to put it to use.
Before considering an investment in data, scientists and data management technologies, the first step with a data strategy is to establish what you hope to achieve from it. Are you seeking to identify and develop new products and services? Do you want to automate processes? Deliver personalized experiences for your customers? Any data strategy should align with your business goals, and your aims to achieve them.
Data silos are one of the biggest obstacles to a unified and coordinated data strategy. Different datasets, in different formats, in different systems and in different departments means “dirty” data and fragmented insights. The lack of a single source of truth hinders the accuracy of your insights, as well as the ability to develop cross-functional decision making and initiatives.
With a data governance model in place, defining people, processes and technology, this can enable enterprise-wide alignment of vision, along with a greater understanding of the different needs, capabilities and priorities of different departments.
More interesting still, a greater ability to acquire, process, and gain value from data means the foundations are in place to experiment with and deploy technologies like AI and machine learning. With large volumes of structured data needed to develop prototypes, training models and algorithms, plans to implement artificial intelligence projects are not only feasible, but more likely to be accurate, unbiased and effective.
In the big data era, it isn’t necessarily the biggest or the wealthiest companies that will survive. It will be those with the ability—and the willingness—to adapt, transform and innovate. This demands the ability to access, understand, and use data. A data strategy is vital for readiness now, and preparedness for the future.