Collaborative Business Intelligence
By: Adam Pringnitz
Do you ever walk into a meeting to review data with upper management and the information you bring is completely different from what they are seeing? I know I have done this, and it makes for an awkward discussion, much less getting your feet back under you to move forward confidently. Thoughts start running through your head… “Did I get my data wrong?” “Did my boss have the wrong data or interpret it wrong? I can’t call them out in front of everyone!”
Research conducted by Shawn Rogers, formerly an EMA Analyst, lays it out the best. He says “Two heads are better than one.” It may be an old saying, but it is still true today. In today’s fast paced, economically challenged environment, making better decisions is not just a “nice-to-have,” it is vital to the very survival of businesses.” Every piece of a business needs data in order to make informed decisions. In a manufacturing environment, Management needs to know what profits are looking like for the year and if they have the additional funds for investment, Sales and Marketing needs to know how conversions are looking and if marketing efforts are paying off, or Production needs to know the amount of orders processed from past years to plan for order increases based off trends to plan for necessary production hours. Most of this data that is generated, or insights created based off this data is often stored on the user’s personal computer, generally not shared with others except for in a meeting. What if there was a way to share the insights and data in one central location so Management can see where marketing dollars are being invested and how they are working compared to profits month over month or Sales is able to track an increase in sales demand month to month compared to previous years and compare that to production hours worked?
Fortunately, there is a way for this to be possible. Collaborative business intelligence is the merging of business intelligence software with collaboration tools, including social and Web 2.0 technologies, to support improved data-driven decision making. While this is not a new technology, as the workforce continues to decrease and gaps are not filled from the Baby Boomers to Millennials, the work and collaboration will need to be picked up and completed with less workers. There will be a larger need for collaboration going into 2019 and further. According to Monster.com, with 75 million Baby Boomers marching inexorably toward retirement, it’s clear that employers will need more than one workforce plan for replacing exiting workers. The Bureau of Labor Statistics projects that the labor force rate will continue to drop through 2022. During the years 2002-2012 the labor force grew by 0.7 percent annually, whereas it’s expected to grow by 0.5 percent from 2012-2022. (Toossi, n.d)
There are many brands that offer a software for businesses to invest in and have the analytics, data, and insights in one location right at their fingertips. Brands like Logi Analytics, datapine, and Yellowfin are just a few of the many brands available. They allow users to gather their data, place into a central location and allow access to anyone they want to use that data. Each brand offers their own added values and benefits like putting insights into presentations and adding their own comments to that specific graph or create a shareable link to that chart to send out to anyone they feel needs access.
The next time you walk into a meeting be prepared. Collaborate with other departments often, gain that knowledge of information they might have to share. Two heads are truly great than one and don’t get yourself into a predicament where you might have to prove your boss wrong. Get all the facts so everyone is on the same page and set the company up to be prepared to do more with less. Best of luck on your collaboration of business analytics now and into the future.
Mitra Toossi, “Labor force projections to 2022: the labor force participation rate continues to fall,” Monthly Labor Review, U.S. Bureau of Labor Statistics, December 2013, https://doi.org/10.21916/mlr.2013.40.