Bringing a new analytics suite into a business is far more complicated than simply installing it on a bunch of PCs. Leaders must figure out which departments will benefit the most from such toolsets, and distribute accordingly.
There’s also the small matter of making sure the organization adjusts culturally to the introduction of analytics. Software firms might brag that their products are “plug and play,” but the reality is people need time to integrate new tools into their existing workflow.
First things first: Before an analytics suite rolls out to the company at large, managers must familiarize themselves with its capabilities. Overcoming that unfamiliarity can prove a huge challenge, and requires time that must be built into a schedule.
Second, the rollout must have focus. To quickly introduce analytics throughout a whole organization is a recipe for chaos. Instead, it’s better to pursue achievable scale: start small (with coordinated pilot tests) and roll things out at a comfortable pace, focusing on those departments that stand to gain from analytics in a significant way. Adopting analytics tools can require a redesign of customer-service workflows, a distribution of new apps, and training for everybody who interacts with the new software.
Which departments can benefit the most from analytics? That depends on which departments actually do heavy data analysis (i.e., number-crunching). If a robust tool can replace most of the manual spreadsheet work in a particular department, it should be considered a prime candidate for early adoption.
Every company is different, so determining which departments can best benefit from analytics should be done on a case-by-case basis. It can be easily assumed however, that departments such as finance and customer service (which need dashboards, metrics and trending) and human resources (which has reporting and compliance needs) are good candidates. But this may still differ from company to company.
Building an Analytics Foundation
While people have talked about data-driven cultures for years, actually creating one is more actionable than ever, thanks to a new generation of powerful, relatively low-cost tools.
Companies now have a wider set of options for spurring analytics engagement among critical employees. A training “boot camp” for end users is a common solution; partnering power users with those new to the analytics software also works, and will help managers and departments see the added value in an analytics framework.
The success of an in-house analytics program also hinges on communication. Channels that allow employees to share the excitement of analytics with colleagues and leaderships are a major way to root cultural change. Newsletters, email, and other tools can help in this aspect.
Those departments that aren’t as data-centric, meanwhile, can rely on either IT or a dedicated analytics department (or outside firm) to prepare reports without having to invest too heavily in new tools.