How do you protect the stability of the work you’ve already done while evangelizing experimentation, exploration, and progress within your organization?
The rapid evolution in business intelligence and analytics capabilities is both exhilarating and overwhelming.
We’ve got a few tips for you.
Before you start adding new technologies or techniques into the mix, it’s critical that you first eliminate any unnecessary work or steps in your data processes. We advocate taking a two pronged approach to this effort.
First, ensure your BI/IT team is not a glorified report factory. Much of the advancement in BI and analytics has been to help you make this change. This could mean adopting easier to use visualization tools like Tableau or Microsoft Power BI. Or this might mean giving certain departments access to full stack BI solutions like GoodData or SiSense. Or it might mean a combination of both. Either way, ask questions, get curious and figure out what your business users need to make self-service BI a reality for your organization.
Second, look to the platforms and tools that simplify the entire backend of your Business Intelligence environment without requiring you to scrap the work you’ve already done. While we recognize the benefit of full-stack BI solutions, there are few companies that want to (or even should) put their entire BI environment into a single platform. Most companies have already constructed components of their analytics environments that they don’t want to simply scrap. Or each department has wildly different needs, that a single full-stack provider just can’t meet. Instead, look for the tools that allow for full flexibility to keep the components of your existing infrastructure that are working well, while improving others and filling open gaps. Keboola Connection allows for this agility - simplifying your entire backend by bringing storage, ETL, prep, enrichment and integration together. Take what you need, leave the rest.
If pure prep is your issue, look at Paxata or Tamr, both of which aim to simplify prep enough that analysts or even data savvy business users can learn to do the work themselves. Our recent blog post Using a Data Prep Platform: the Key to Product Agility might help you understand these technologies better and how to integrate them into your current BI environment.
If your particular challenge is making it as easy as possible for your team to ensure it’s getting the right data to the right people, look at Looker. With Looker, “data analysts describe your data, from metrics to data-definitions, while easily exposing all of the data, not just a subset, so every team can ask and answer their own questions.”
If data cleansing and data reliability is the issue, take a look at Trifacta and its data wrangler. It can help your team quickly clean up the data into its most usable format. There are TONS of other tools out there. See below for some advice on how to find the right ones for your organization.
While empowering self service BI can certainly free up some time and resources for your analytics team, keep in mind that it’s the data janitorial work that takes up to 80% of your data to analysis lifecycle. You’ll get greater returns by focusing on that component first.
Your team and your leadership is going to be a lot more excited about experimenting with new tools if you make the process and simple (and cost effective) as possible. At Keboola, we often say that the key to innovation is not just Fail Fast. Fail Forward. It’s also Fail Cheap. If you’ve followed our advice above, you’ve hopefully found some technologies that make bridging connections to new technologies or learning new techniques as simple as possible. For example, with Keboola’s App Store, with just a click of a button, you can bring in dozens of new data sources, apps with complex algorithms like bucket analysis, Natural Language Processing, predictive analytics and a whole host of other data innovations. If you want to learn more, check our blog on Data Monetization and how Data Science can help.
While taking a smart approach to technology adoption can certainly help your business really learn to Evangelize the New in business intelligence, the real innovation is going to come from creating and supporting a culture that encourages data curiosity and innovation. All too often, leadership focuses so much on the day-to-day that they forget to empower their teams to think and dream and strategize about tomorrow. Instead, foster a culture that empowers and rewards initiative and imagination.
Host regularly scheduled learning sessions: Ask individuals on your team or at your company with a particular niche expertise to share their knowledge. Bring in managers from departments that your BI team serves to explain how analytics helps them and what they wish they could do. Allow vendors or partners to give presentations on new technologies or industry trends. Don’t cancel these. Ever. Sometimes not everyone will be able to attend, but eventually your team will know to work around them and get excited for what they might learn.
Have regular team lunches when you can come together and talk casually. Maybe someone on the team can share the details of a project or ask for help with a frustration. Other times you can open up the discussion to suggestions for process changes or shout outs to team members that are killing it. If your team feels like a team, they’ll be a lot more likely to bring up new ideas or technologies.
Empower employees to champion, lead and manage new projects. Give your team an incentive to pitch new projects. Make it clear that if they do the legwork to present the idea and win approval for the project, they can manage its configuration and implementation. When employees have skin in the game, they get motivated.
Evangelizing the New, particularly in business intelligence has its challenges. There’s no doubt about it. But with the rapidly changing analytics landscape, innovation is critical to staying ahead of your competitors. With the tips above, you should be well on your way.
