November 22, 2019 - Data has become a critical resource for modern businesses – the fuel that drives product development, sales, marketing, infrastructure, human resources and a thousand other aspects of corporate success.
It’s also a critical component for any company using IoT technology. After all, IoT technology is what produces much of the critical data being used in modern business.
But, a lot of companies struggle with integrating data into decision-making and workflow. In fact, numerous studies have shown that the problem starts at the top, with C-suite executives ignoring data in favor of instinct, their “gut,” or gambling on the long-shot bias. A recent study by KPMG shows that 67 percent of CEOs ignored insights from data analysis because it contradicted their own intuition.
Yet that’s often the wrong call. Nucleus Research, for example, contends that analytics pays back over $13 for every dollar spent. As long as you’re using the data properly, that is.
It’s not too late to fix the data problem in your own organization. Here are some tips you can use to build a data-driven corporate culture.
Keep the focus on key use cases
Eventually, everyone in your organization and at every level should turn to analytics to make decisions. But one step at a time – you can’t expect everyone to embrace a new way of doing business until they see some success stories.
Work with your data scientist or analytics manager to define a handful of key use cases in which making decisions with data can result in some unambiguous wins. Then you can use those to expand and extend your data program throughout the organization.
Developing a data-driven culture means helping your people become data-literate – and to make referring to data second nature.
You might start by creating an analytics division that makes “house calls,” delivering training and consulting with any manager or department that needs help integrating data into their decision workflow. But you’ll need more than that.
Ensure everyone is using the same data source
Successful organizations ensure that the entire business pivots around a single source of data, for example – don’t let individual divisions source and manage their own datasets, so there’s no doubt which data is the authoritative source, and there’s no opportunity for redundant, conflicting, or contradictory numbers.
Just as importantly, the data fields, metrics, and analytics reports need to be well-defined and easily understood by all. Consider making a thorough and comprehensive online data guidebook a top priority for your data science division.
Deploy data across the entire organization with the right tools
You should be sure that you’ve invested in a business intelligence portal that’s easy to use and makes the data available to everyone.
A centralized portal is essential to instilling the value and importance of data throughout the entire organization.
Wage war to stomp out intuition
It doesn’t matter how good your data and reporting is – how thorough the analytics – if it doesn’t get used to actually make decisions, it’s a waste of money and your data campaign will fail.
Often, the bottleneck in converting to a more data-centric culture are the experienced senior managers and thought leaders in the organization who drive decisions based on their anecdotal experience.
In other words, data might be discussed, but it’s the “Highest Paid Person’s Opinion (HiPPO)” that ultimately rules the day. As the Financial Times points out: “HiPPOs can be deadly for businesses, because they base their decisions on ill-understood metrics at best, or on pure guesswork. With no intelligent tools to derive meaning from the full spectrum of customer interactions and evaluate the how, when, where and why behind actions, the HiPPO approach can be crippling for businesses.”
But more than anything else, remember that culture often flows from the top down.
You need to have confidence in the data and use it to implement strategy. Your actions will inform others, and you’ll be on your way to a business that takes action based on measurable metrics, not anecdotes, instinct, and long shots.