Why Democratizing Data Is a Great Catalyst for Business Growth
Published: August 4, 2016
Author: Paco Darcey
The idea of sharing information across corporate department lines is not new. Business analysts and business intelligence application vendors have been warning of the dangers of disparate data sources for years. Recently, many companies are evolving from compartmentalized information management to more transparent practices.
Business executives aren’t just pre-packaging “sanitized” reports, either. In many cases, they are leveraging analytics tools that provide up-to-the minute business performance data. Executive dashboards of data visualizations are available on mobile devices, laptops, and desktops much more broadly than ever before.
In this post, we’ll break down best practices and options for accessing and using data across an organization: how to share it, how to present it, how to achieve confidence in it, how to take action on it, and more.
Cautious Information Sharing, Not Anarchy
Defining access rights based on roles and responsibilities is still necessary for good information governance. Analytics giant Informatica cautions against letting data democratization go too far, which can create security vulnerabilities, data leakage, and other problems. Like any good democracy, data democracy requires well-defined policies, stakeholder alignment, and accountability.
A company’s ability to share data across the entire organization depends a great deal on:
- Company size
- The nature of company data being shared, whether it be related to financial, production, marketing, or project performance
- Whether a company is publicly traded or private
- Corporate structure, and how long the firm has been in business
Collaborative data sharing based on a “need to know” basis is the best way forward. Product managers can benefit from visibility into customer service metrics, and sales or marketing executives should know about inventory statistics.
Create a Buzz with Data Visualization
It’s likely not a surprise that a large enterprise, high-end business intelligence vendor like Informatica would focus on the potential dangers of democratizing data. But Domo, the Utah-based analytics company, is a newer entrant to the space that has grown quickly under the direction of CEO Josh James; their focus is on making business performance data accessible as widely as possible, in real time. Their Buzz platform gives privileged employees, executives, and boards of directors current information from hundreds of data sources.
Domo, and other solutions like Good Data, Microsoft Power BI, and Tableau (editor’s note: we use Tableau) are developed to make analytics easy to understand at a glance. Domo Buzz takes it a step further by enabling users to have online chats about the data right in the interface. Instead of playing phone tag, or going back and forth on e-mail, conversations can happen in context, and decisions can be made with confidence.
Companies thrive when individuals and teams communicate effectively across the organization.
Building Confidence in a Data-Driven Culture
Many companies invest in analytics solutions, but they don’t get the value they are looking for. For other companies, their idea of data sharing is for an executive to print out a chaotic Excel spreadsheet, drop it on an employee’s desk, and say, “This looks bad to me; we need to fix it. Good luck!”
One of the many problems with this scenario is that by the time the problems within the spreadsheet are understood and solved, three other business challenges can arise as a result of data that is presented in a way that doesn’t inspire confidence to act. Sharing data in a pie chart, bar graph, or other graphical representations, and pulling from multiple data sources, inspires trust that the information is reliable enough to act on.
Take the classic scenario of an executive, standing in front of a flip chart with an upward or downward trending line graph. There is usually no question about the reliability of the data based on who is presenting it. But until the data behind the upward or downward trend is shared with all those who can act on it, the executive’s team is either looking for an exit because they don’t know how to “fix it” or they are high-fiving each other.
In short, businesses grow when their employees and executives can act on reliable data.
Removing the Human Element from Analytics (in a Good Way)
Big data and analytics have never been mistaken for a warm, fuzzy system because they remove the emotion from business and present the cold, hard facts. In the enterprise information world, business intelligence is Mr. Spock. (Or Mr. Data, if you’re a TNG person, but that’s too easy.)
With spreadsheets, pivot tables, and manually generated/distributed reports, there are many opportunities for human error, intentional manipulation of the numbers, or stakeholders not receiving the reports when they need it.
When people, processes, and technology are put in place to democratize data effectively, reliable information can be scheduled for role-based or designated distribution. It can also be accessed on an ad hoc basis and discussed by those in the “circle of trust”.
Creating an Environment for Effective Data Sharing
Over the history of business intelligence, data has been stored in many forms:
- Data warehouses, factories, and marts
- Blobs or lakes of data
- Data layers
- Permission-based, structured, or virtual data repositories, connected to a broad ecosystem of information
The right data collaboration engine for your business could come from Domo, Tableau, Informatica, Microsoft, or any of the analytics players in the industry. Just like any engine, it’s not only the manufacturer which determines the performance; it’s:
- How the data is maintained
- The skill of the data “driver”, analyst, scientist, or other users
- The quality of the fuel and “lubricants” you use – or, in this case, the quality of the data which goes into it
Just as you wouldn’t share your car keys with anyone who asks for them, the first steps you take in defining your data democratization roadmap should be:
- Who needs access to what data?
- How and where should they be able to access the data?
- When privileged users have access to information, and how can they discuss it with others to take action on it?
- Why haven’t we implemented a data-sharing culture sooner, and why have we struggled with these bottlenecks for so long?
ComputerWeekly has declared 2016 the year of data democratization. Time will tell if they’re right, or if businesses are quite ready for liberated data.
What do you think? Tell us about it in the comments section below.