The notion of “big data” has revolutionized the way we view business management practices and solutions today. And while the concept is treated as a “new” discovery, big data has actually been around since the early 2000s. In fact, 10 years ago, Birst was one of very few BI vendors on the market trying to make a case for itself as a needed technological solution inside any sized organization. Today, there isn’t an organization that isn’t thinking about it.
That said, business executives in organizations across every vertical are now refining their focus and relying not only on the quantity of data gathered, but also the quality to help improve their bottom lines. It’s no longer a question of how much data an organization has, but what actionable insights it can gather from multiple data sources in order to enable quick intelligent decision-making. This new way of organizational thinking has, as a result, driven executives to adopt a data-driven culture within their organization.
Thanks to the Internet of Things (IoT), nearly every person in this world produces massive amounts of data each day, leading to changes in how often consumers engage with businesses and in what way. It is these advances that have ultimately helped to generate data in huge volumes and at unprecedented speed.
However, according to an Aberdeen Group research report, businesses that do work to automate data processes not only empower the front line by increasing analytical access and acumen, but also form a more agile and flexible organization, decreasing integration and total implementation times overall. In turn, businesses optimize sales, marketing, operations, customer engagement, revenue and more.
To ensure a seamless and successful transition to a data-driven culture, here are top approaches your business should follow:
Hire a Chief Data Officer (CDO)
To convert data into actionable insight and assembling it for the right constituent, so that it provides immediate maximum impact, is no easy feat and businesses shouldn’t expect their CTO, CIO or CMO to perform the job; it’s simply too much. Instead, businesses need a corporate officer that is wholly dedicated to acquiring, managing and using data to improve overall productivity and competitiveness. Lastly, you don’t necessarily have to hire someone new to manage data as a corporate asset. You may already have a CDO at your company; or rather someone understands the value of data and takes ownership of it. This person could be your director of analytics, VP of Operations or someone ready to take the reigns as the person who will make data your competitive advantage. A CDO is not about a creating yet another headcount, rather it’s about assigning ownership of data as your competitive advantage.
Create Policies and Guidelines
After the CDO has run a data audit internally, it is pertinent that company policies and guidelines are crafted around the data analysis. This way, all employees, from executives to the front line, are equipped with repeatable strategies focused on improving specific business challenges previously discovered.
Motivate Employees to Seek Data
Once new company policies and guidelines are in place, the next step for businesses creating a data-driven culture is to motivate employees to seek data-driven answers by offering incentives. By doing this, employees feel encouraged to use tools and find solutions on their own, rather than going to IT.
Bridge the Gap Between Users and IT
Two separate approaches currently exist within organizations—(1) traditional BI solutions and (2) discovery BI solutions. These two types of worlds have not only created a chasm between IT control and end user freedom, but have also brought forth unnecessary problems for both business and IT leaders. Just like the idea that everything will go into one place within the cloud is unrealistic, so too is the idea that legacy BI solutions can keep up with real time demands. As such, instead of pitting traditional BI solutions against discovery BI solutions, companies must adopt a two-tier approach to not only their data, but also the organizational structure around analytics. By doing so, they will increase the effectiveness of both discovery and enterprise BI, while creating a much tighter collaboration between the business users and IT.
This article originally appeared in WIRED Innovation Insights.