Data used to be the exclusive preserve of data scientists, analysts, and senior executives, but all that has changed now. Access to data, and the tools that help you to visualize, analyze, and generally make sense of it, has been thrown wide open over the last few years, making it possible for businesses to transition to being almost entirely data-driven.
Despite this shift, businesses aren’t always integrating that data properly. If you’re still holding on tightly to your control over which of your team members have access to deal directly with your data, it’s time to relax your grip. In most situations, the more people interact with and use data, the better for your business as a whole.
Until recently, most businesses followed a model where certain individuals within the organization would interact with data independently. There’d be a few analysts and data scientists, and certain executives who make high-level business decisions based on the data fed to them by analysts.
But now that model is looking outdated and insufficient for the needs of a truly agile data-driven business. It’s time to build a broader data team that is integrated into your whole business. Next-generation business intelligence platforms make it much easier to collaborate on data-driven projects, so you can reap the benefits of a team approach to data-driven business management.
Taking a team approach to data-driven business management forces you to democratize access to the data and the tools needed to visualize, analyze, and process it.
It’s vital to make sure that everyone can access your data without long, frustrating delays while they try to find the right dataset or locate the newest machine learning model. Dismantling silos and opening up data banks boosts productivity, raises employee engagement, and reduces resentment among those employees who are locked out of the data mines.
The bigger the corporation, the greater the risk that individuals, groups, or whole departments will lose touch with each other. You can end up with different departments working at cross-purposes, or with Sales sitting on data that could resolve mysteries in Product, for example, only no one in Product even knows that it exists. Building cross-departmental data teams removes this risk of data silos and isolated departments.
Data teams also help you maintain focus on critical business challenges and opportunities. Instead of having every department haring off in a different direction, dragging their data to investigate a different issue, your data teams will all be giving their attention to the same problem.
Commoditize your data
Data may be a business’s most valuable raw material today, but just like other raw materials, you can only realize its true value when you process it. Nearly every business is rich in raw data, but you might struggle to commoditize it in a way that fuels smart management decisions.
Scattered analysts, data scientists, and other employees working on your data in disparate areas of the company can’t keep up with the flood of information that gushes into every organization today.
You need coordinated data teams to produce all the valuable predictions and actionable insights that would otherwise go to waste, slipping through the cracks between one individual and the next.
Empower every department
There’s also a risk that business departments and teams that aren’t trained in data science could make a mess of your data projects. If you lavish self-service tools on untrained employees, there’s a big chance that they’ll misinterpret or misperceive data, insights, and predictions.
Business decisions based on these flawed conclusions won’t bring the desired results, which, in turn, may provoke distrust in data and hobble your long-term move to data-driven business decision-making. Gartner famously reported a 60% failure rate for data projects, which was later updated to 85% by Gartner analyst Nick Heudecker. Heudecker added that this high failure rate stems from a lack of skills and the difficulty integrating data projects with existing business processes, among other causes.
The better alternative is to build data teams, with data engineers, database administrators, analysts, and other data workers working alongside other employees. This way, every department can access, manipulate, and model data correctly to answer questions, predict future KPIs, and make good decisions.
Make your business more innovative and agile
When you build cross-departmental data teams, you’re also building in potential for fruitful cross-fertilization with ideas and approaches.
Combining your marketers with data scientists and DevOps workers with analysts makes your business more innovative and agile in responding to change.
Data teams are the key to a successful data-driven business
Converting your isolated data workers into coordinated, integrated data teams is the next phase in transforming your business to be based on smart, data-driven management.
By opening up data silos and creating holistic, cross-departmental data teams, you’ll be able to reduce frustration among your employees, actualize the true value of your data, empower all your departments to base their decisions on data, and make your business more agile and innovative.