Occasionally one of the problems that can doom an analytics project is a new technology that emerges and makes the project obsolete before it is even implemented. This happened to me once when we were using an older and heavily modified version of Business Objects and then we got access to Tableau.
At the time, the flexibility of Tableau made our Business Objects business dashboard obsolete before we even completed the design phase of the project. The data visualization and the ease of use of Tableau Desktop at that time was miles ahead of anything our IT team could build around Business Objects. As a result, countless hours and dollars were lost, but in the end at least the business requirements we had established could be done by end users in Tableau.
Another example of how a new technology might impact your project is when a new version of the database you are using comes out. One that requires some much QA and/or testing to meet internal guidelines, that when it is finally approved it is hardly useful any more. This can often be the case with big companies that have long vetting processes to use new version of software. You’d be surprised how many Fortune 500 companies are still running internal version of Windows XP because using 8 or 10 has not been approved yet.
Modifications done in house to off the shelf solutions can also make new versions incompatible. I have seen this happen with both Cisco and Teradata databases, where internal development of data flows and data structures to be so rigid, it was impossible to use updated versions of the same databases.
You can also come across situations where developers and IT teams are ordered to use something else because changes in a vendor relationships or a new strategy from the CTO. In the end you have to adapt and either sacrifice, lose, or give up on what you have put into the project so far.
As the number of data collection and storage options grow, the complexity of data models surge and the types of business intelligence solutions increase, the likelihood of a big analytics projects being impacted by new technology. A good analyst has to stay up to date on what’s hot and new, in order to not advocate the use of something that is on its way to being a dinosaur.
To help me stay current, I follow several blogs and belong to a dozen analytics themed LinkedIn groups. I also try and attend at least one big industry conference a year as an attendee as well. And finally I read a lot. I end up going through 3-4 analytics themed books a month. If you are facing a situation where you are worried your project might fall victim to a new technology, let’s talk about it. I can help you figure out a solution to keep you and your project on the cutting edge.
The key to using analytics in a business is like a secret sauce. It is a unique combination of analytics talent, technology and technique that are brought together to enrich and empower an organization. A successful analytics culture is not easy to create, but DMAIPH can show you how. Contact DMAIPH now at firstname.lastname@example.org or connect with me directly so we can build a strategic plan to turn your company into analytics driven success story.
Analytics Culture – The key to using analytics in a business is like a secret sauce. It is a unique combination of analytics talent, technology and technique that are brought together to enrich and empower an organization. A successful analytics culture is not easy to create, but DMAIPH can show you how. Contact DMAIPH now at email@example.com or connect with me directly so we can build a strategic plan to turn your company into analytics driven success story.