Making the most of mountains of data

Businesses should capitalize on the data they already have by addressing quality concerns and building a proper infrastructure


We live in interesting times for anyone who loves data. Technology allows us to collect information associated with nearly every aspect of our lives, and the possibilities for tracking, measuring and optimizing that data are virtually endless.

We can use software to generate and analyze data about our fitness, our sleep, our energy use or our spending – we can also use past behavior to map out our futures.

If you're a business leader, though, there's a good chance that you're feeling a little underwhelmed by the results of your attempts to harness the power of data. Even though companies constantly talk about "big data" and invest in analytics tools, Forrester Research reports that up to 73% of business data is never analyzed. In some cases, this wealth of tools is part of the problem.

Most organizations are in an optimal position to improve productivity by reducing the time employees spend accessing data through various systems. The cross-culmination of information and data is not only counterproductive, but it also exposes reporting and analytics to all types of human error in data gathering, sharing and analysis.

The importance of starting small

A lack of understanding about how to properly collect, read and apply data is costing companies untold amounts of money in the form of lost revenue opportunities, quality issues and decreases in productivity. On the other hand, some companies are able to take advantage of data to minimize costs and drive revenue. Spotify used this power to upend the music industry, for instance, and Facebook used it to jumpstart the growth of social media – which has changed commerce forever.

Constant advances in AI have made analytics software more powerful and attainable for companies of all sizes, and many potential use cases remain largely unexplored. We have only started to scratch the surface when it comes to using automation for real-time reporting, for example, but recent developments in statistics and reporting capabilities promise to provide business leaders with more accurate data – and much faster than in the past.

These capabilities have not evolved overnight, of course, and data won't transform your company immediately. If you're one of the many businesses amassing huge amounts of third-party data but have yet to capture its value, aim to start small and move forward one step at a time. Depending on your current status, consider building a strategy around these three objectives:

Develop an infrastructure for handling data

Any company that plans to capitalize on its data must have a fully integrated enterprise resource planning (ERP) system in place. You'll want to be able to collect and store information in a single database that feeds other areas, which will eliminate wasted time and improve productivity. An ERP system should allow you to automate data flow and many other backend processes – it should also ensure that you're able to receive knowledge in real time.

A secondary infrastructure change to consider would be a move toward a cloud-based, service-oriented architecture. You need easy online access to data with intuitive functionality and real-time reporting capabilities; pulling data directly expedites turnaround times and allows for faster analysis.

Take care of data quality issues

Data must be accurate and clearly structured before you can analyze it effectively. Bad data renders your machine-learning (ML) tools and personnel investments useless, and it can ultimately lead to errors that harm your business.

There are relatively few industry-specific standards for data quality and it's up to business leaders at the forefront of data analysis to lay the groundwork for them. Regularly measuring data quality, cleaning your databases and formalizing processes that streamline the flow of data from source to output are essential steps to guarantee a useful and sustainable data analytics practice.

Use third-party data to improve customer service

An abundance of customer data is a marketer's dream because it can help marketers create messages that are specifically targeted to the people receiving them. Personalizing customer engagement isn't just a marketing tactic – it's also good business. Putting customer needs at the center of messaging and other aspects of your business, such as product development and hiring, will inevitably drive loyalty and benefit your retention efforts.

Moreover, orienting your company's operations around meeting customer needs is a surefire way to differentiate yourself from your competition. You can take the insights you gain from your data analysis and apply them to the creation of improved customer experiences. You can also use information from nearly every interaction your company has with customers to inform that experience. It sounds difficult, but ML makes it possible.

If you're starting to doubt whether your piles of data are as valuable as you were led to believe, you're not alone. Most companies are struggling to figure out how to make sense of seemingly endless amounts of customer information and doing so will take time. As long as you put together a road map that includes the three steps above, you can begin making progress toward a future where your data gives you an undeniable edge.

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