In a recent survey conducted by SAP, 86 percent of business decision makers said that they believed the majority of employees would need to become data geeks in the near future. The reasoning is that with data becoming more and more accessible, employees are going to need to acquire the skills to sift through and analyze data to get anything out of it — even if that’s not what they’re employed to do.
There’s some truth in that statement: Data is increasingly available to employees of every level, and it’s important that they’re able to get the most out of it. However, trying to turn every employee into a data geek is like trying to water houseplants with a garden hose — you’ll only end up drowning them.
The Importance of Smart Data
Data geeks are a vital part of any company — that’s why 91 percent of those same decision makers singled out their companies’ data scientists as the best source for analysis of big data. But “data scientist” is more than just a title; it’s an occupation that comes with its own special training suited for specific types of people. And, of course, not every employee is equipped with the training and mindset of a data scientist.
No matter who’s looking at it, it’s easy to be overwhelmed by irrelevant data. Requiring employees to become data geeks can create a “pull” paradigm that forces users to go searching for answers. Often, they end up finding more questions, requesting more reports and dashboards, and sitting on an overload of information that needs to be continually monitored and checked, which prompts them to give up altogether.
By the same token, leaving everything in the hands of a few data scientists doesn’t work, either. This can bottleneck the whole analysis process, leaving employees in other areas waiting too long for time-sensitive insights that will be stale by the time they’re handed down. Data that’s actionable at 8 a.m. on Monday might not be useful by Tuesday.
The solution isn’t to put all data in the hands of all employees; it’s to ensure that the right data is delivered to the right people at the right time. The old way of doing things, in which reports were presented periodically to executives for analysis, is dead. A new wave of plug-ins, integrations, and platforms is ensuring that users are being pushed relevant data, not being left with mounds of information to sift through.
Getting Data in the Right Hands
Your employees shouldn’t be data geeks; they should be department-specific geeks. For example, if they’re in sales, they should have access to their sales funnel; if they’re in DevOps, system and application performance are important. Once your employees have their fingers on the pulse of the data that helps them do their jobs, the rest takes care of itself — provided you adopt systems that deliver that data in a timely, digestible manner.
Data and BI platforms should be accessible enough for the average sixth-grader but contain enough data to effectively inform every employee across your organization. It’s a delicate combination of back-end complexity and front-end simplicity. Here are a few things to keep in mind when setting up these systems to ensure that your employees are actively engaged with the data they need:
1. Use affinity models. The first question that probably comes to mind is: How do your IT leaders know what data is relevant to each employee? Each department has its own needs, and there may not be enough overlap with IT’s processes to give your tech team a clear picture of where information should be distributed. Furthermore, users themselves often don’t know which metrics are important to them or what may impact their world. This is where affinity models and social proof come in handy.
Take into account what each employee’s peers and bosses are looking at, and have your data experts push metrics forward based on this. It’s extremely effective not only in gauging relevancy, but also in encouraging collaboration within a department.
2. Encourage collaboration. Rather than pressuring employees to know everything about business intelligence on their own, business leaders should encourage discussions on the data-point level. This way, not only is the specific expertise of each employee being used to its full extent, but the data is also given better context, turning it into more than raw numbers and helping it become actionable.
3. Utilize push notifications. Rather than wait for users to find data for themselves, your data analysts and programmers should set the company’s systems up to alert employees of relevant data changes. These alerts should be focused on metrics that affect the daily cost of doing business.
For instance, sales management should be made aware of any changes in the pipeline that could affect quarterly results. If you’re in healthcare, employees should be alerted to regulatory thresholds so you’re not being penalized for missing targets and goals such as readmission rates. And everyone should receive alerts triggered by hidden outliers — more granular data points that may be overlooked during simple reporting.
Data geeks definitely have their uses, but they’re not suited to every position in your company. By trying to turn everyone into a data scientist, you diminish the value of employees who don’t fit that bill. On the other hand, by focusing on smart data that’s pushed out to the right people, you can turn everyone into a more productive part of your workforce.