Five Data Hacks That Will Boost Your Business Processes
CTO of Infostretch, a digital engineering services company that helps enterprises prosper in the digital age.
We’re several years into the era of digital transformation, and the AI revolution is well underway. One thing has become painfully clear: Generating excessive volumes of data has become a byproduct of running a business in this digital age. Even the smallest digital business generates an inordinate amount of data, without even trying.
Dozens or hundreds of applications, in a multi or hybrid cloud format, utilized by a dispersed workforce: It’s no wonder that IT departments are having a tough time sorting out the signal from the noise, even at the most tactical, keeping-the-lights-on level. And that’s before we even look at harnessing data in a strategic way to propel the business forward.
Data management is arguably the biggest pain point that enterprises don’t know they have. It can make or break every digital system or process; it’s sustenance for AI systems. In short, data is the power behind the throne in every digital business. So, we need to give data management the respect it deserves. In this article, we’ll explore five attitude shifts toward data — we can call them “hacks” — that can collectively transform your treatment of, and ultimately success with, data.
1. Treat data as the starting point for everything.
Data is the engine that powers everything in this digital age. And yet, even in some massive corporations that should know better, it can be treated as an afterthought. To stretch the engine analogy, it’s like some businesses are building a car and only work out how and where the engine will fit in after the car has already been built. Naming no names, a certain large technology services company wouldn’t have run into such serious problems with its AI services had data structure and data aggregation been the starting point and threaded throughout its development process.
Even if it’s tiresome to your colleagues or team, keep asking about data. Where’s that data coming from? How are we generating that data? Always remember that the value of data depends entirely on its context and application, so even data gathered and stored on legacy platforms can be infinitely useful if appropriated in the correct way.
2. Save the best and ditch the rest.
Not all data is inherently useful. There’s the temptation to hoard data without having a clear reason why. Outside of certain regulatory or remediation use cases, you don’t need to stockpile data for a rainy day. Instead, be discerning about what data you need to maintain and allow the rest of the data to fall away. Prioritizing the right data simplifies decision-making, speeds up processes and saves costs.
Remember, contextualized data that has defined correlations is worth far more to your organization than isolated data. The former can be turned into useful information, but the latter will do nothing but take up valuable storage space. If your business is drowning in data now, just imagine what that will be like in five or 10 years. There’s no value in being data-rich but insight-poor.
3. Automate, analyze and then automate again.
Through automation, businesses can achieve operational efficiencies, freeing themselves up to focus on bigger challenges that will deliver greater results for the business. It’s tempting to think that you can automate something and never have to think about it again. However, that can lead to businesses, processes or applications becoming frozen in time, while competitors continue to innovate. Instead, business leaders need to treat automation as a process that needs to continue evolving — and your data will give you clues to what needs to happen next.
Provided that you have prioritized the right data and structured it correctly, it can become the driving force for your business to continue refining your processes, becoming more efficient and effective and improving the customer experience.
4. Democratize your data.
At the most reductionist level, every business is a collection of people and processes delivering value to customers. However, in the drive toward efficiency and process improvement, we often see the people part of the business becoming subordinate to the process part; employees can become stuck serving an application or a process, whether it’s fit for purpose or not. Sometimes the training on the new application is inadequate. Sometimes the application itself is inadequate. And all this leads to frustrated people delivering sub-optimal value to customers, which is dangerous to the fortunes of the business.
Data, in whatever form, needs to serve your people and aid decision-making, so that they can better serve your customers. Employee experiences can be personalized to make their jobs easier, just as customer experiences can be optimized to make engaging with your business easier. This experience optimization comes from insight, artificial intelligence and automation, and it starts with data.
5. Allow data to reveal your mistakes.
Celebrating wins is important but the hard part is learning from your mistakes. With evolving digital business models, some missteps are inevitable. Company culture has an important part to play in how a workforce responds when projects don’t deliver as expected. However, data, processes and tools can also help. Understanding — with the help of a data trail — exactly why things went awry ultimately helps to strengthen processes and products. Extending this concept further, we should also allow, where we can, for data to highlight weaknesses before they become problems. This is the thinking behind chaos engineering and the digital twinning of systems, giving your business the leeway to experiment with minimal consequence.
Whatever your business goals, it’s very likely that leveraging data better will accelerate your progress. Back in the ‘80s, when the digital age was in its infancy, Gordon Gecko in the movie Wall Street said, “The most valuable commodity I know of is information.” Switch out “information” for “data,” and we have a rallying cry that is fit for the 2020s. So, let’s treat data right and allow it to serve us and our businesses better.
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