Although it’s difficult to measure the return on investment for many business initiatives, measuring improvements in efficiency is rather straight-forward. All organizations have repeatable processes, be it answering help desk phones, preparing for industry marketing events or returning items to stock. Any repeatable process can be measured and improved; however, many don’t see the same repeatability in data analysis. Static spreadsheets are updated with this month’s data, or a roll-up report is created by aggregating data from many other reports. Tools like Excel as versatile as they may be and certainly pervasive are often used beyond their intended purpose. Using tools that recognize data and work flow not only allow for repeatability and version control, but they can also identify new opportunities to reduce cycle times for data analytics.
This 2017 webcast was led by Jim Knapik of Level Education from Northeastern University, an Innovation Leader partner, and hosted by Scott Kirsner of Innovation Leader.