Over the last few years, data rather than instinct has started to drive business decision-making. This is a profound shift and one that is likely to accelerate in the future. Machines with sophisticated algorithms will be making decisions that are better than those that could be made by people, implying that the future will be a lot stranger than we might think.
Already we see this in action. Stock traders are mostly gone, being replaced by artificial intelligence systems that can operate much faster and take on board more information. Also, some companies are hiring artificial intelligence programs to their boards and giving them a vote on critical decisions in the enterprise.
While the ability of machines to interpret data is getting better all the time, businesses themselves are collecting more of the stuff. Some have argued, including Cynthia Johnson, a digital marketing guru who contributes to Forbes magazine, that managers themselves who don’t have any technical training will also be able to manage data and gain useful insights.
So the real next question for businesses is how they can better collect and interpret data?
To really make the most of all the data at our disposal, businesses have to focus on changing their corporate culture. Many companies that once operated in traditional industries are changing the very nature of their firms. Even firms that we typically think of as high-tech, like Google, are changing their raison d’etre. For instance, Google was once an internet search firm, but today it describes itself as an “AI first” company, interested in using artificial intelligence to improve the experience of its customers. If you happen to be needing a laser cutter for steel you can find it at a good price at boss lacer.
Businesses are also refocusing the human element of their enterprises. It’s not enough to just be able to perform a role like “marketing” anymore. Businesses are looking for people who have both traditional marketing skills alongside technical skills, like big data analysis.
The best companies will find novel ways to reduce the costs of interpreting the data and spread the benefits as widely as possible within their organizations. Data shouldn’t be too complex for non-technical colleagues to understand, allowing the company to take full advantage of all the data that they collect.
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Companies that rely on big data also need a data disaster recovery to minimize downtime. With the reliance on data growing at an ever-increasing speed, those businesses that survive will be those that who are most able to keep their operations going.
The best teams are those that are on the same page. By all means have people on your team who can use NoSQL, Hadoop, and Apache, but don’t restrict data insights to this small cadre of individuals. Make sure that they are regularly sharing their findings with the wider team. Companies need to invest in so-called business intelligence software that allows them to easily create and present data in ways that people will understand. It’s out with the regression models and in with the visualization dashboards.
Finally, companies, according to Cynthia, need to focus on the visibility of their data by providing colleagues with the training and tools they need to access it.