Art of BI: Collaborative BI ZigZag – BIWisdom Response

By | In Art of BI, Big Data, Business Intelligence | February 21st, 2014

I was recently pointed to a blog post by world renowned author and all around BI guru, Howard Dresner. Okay, I follow Dresner on Twitter and often simply review his #BIWisdom tweetchats after they’ve happened. One day I’ll actually participate in a session but this particular session he wrote about was just too much in my perview to not respond; even if is after the fact.

Based on Dresner’s post, during a recent #BIWisdom tweetcast someone chimed in with the question “every year we hear collaboration BI will take off — but has it?”. It goes on to list a few comments from other attendees that I’ll address in this post as well.

When I speak to people about the idea of collaboration in Business Intelligence it usually begins by me explaining that in its simplest form Collaborative BI is the ability comment or annotate a report or a dashboard in a BI System. The conversation expands from there and I’ll explain a few of those clarifying points in this post. Collaborative BI is indeed on the move and any half-stepping contributing to its lack of ubiquity in BI tools is due to a lack of education on the topic. This education should first describe what Collaborative BI is not; because that is where most of the confusion seems to lie.

Taking the angle of describing what Collaborative BI is not is sometimes more direct to relay the perception of the idea. Collaborative BI is not Social BI. Social BI is a coined phrase that is currently attributed to conducting analytics on social networking systems and sites such as analyzing tweets per topic in order to make better CRM decisions. Collaborative BI is not social networking although there are synergies between an enterprise social network system as a communication channel and collaborating within a BI system. And just to clarify by BI system we’re referring to any BI vendor tool, ex: Oracle BI, MicroStrategy, QlikView, YellowFin, and I’m sure there are a few other BI systems on the market.

Collaborative BI is the means to communicate persisting knowledge and provide feedback within Business Intelligence systems in order to collectively make better business decisions.

A last point of clarification here would be that Collaborative BI is a idea in which functional expectations that will evolve over time. Relating this to the world of BI, I would say that the use of terms such Collaborative BI is similar to how the term Distributed Business Intelligence (BI) was once used. In the past there were fat client BI tools that did not have the ability to burst/send a report via email from the BI tools and the tools were limited to desktop/workstation installation only. When the idea of Distributed BI came along, giving a thin client web-based experience was a phenomenal leap of adaptation for BI by providing dashboard portals, 24×7 access to reporting, and integration for bursting emails, etc. with relative ease. Now, there isn’t a BI system produced that doesn’t consider Distributed BI – it is now the cost of entry and a prime expectation of a BI tool.

So, let’s answer some of the #BIWisdom tribe’s responses. One participant stated, “Collaboration must have a foundation in the business; it’s not something that can be pushed from a BI tool.”. My response to this statement would be true but not true. If both the business and IT staff that support the BI tools understand that Collaborative BI is part of the BI Tool’s functionality then they’ll be on their way to achieving Collaborative BI while holding hands on a windy walk exchanges sweet words of success. What I mean by this is that if there is a set of functionality that can be leveraged within the BI tool that a business user uses on a daily basis, it will be a mere extension to the work they already are doing. Collaborative BI is not a drug to be pushed onto the users, it is merely an extended capability of the BI tool. And once, they start using it and seeing value in capability of Collaborative BI then it might seem like they are hooked on it and can’t do without it.

The other responder had a more even tone with the statement, “Collaboration is a business issue, not a BI issue. Technology is a facilitator, not the solution.”. The problem here is that the phrase Collaborative BI is again broken apart to only state part of the byproduct from the idea of Collaborative BI, Collaboration. Yes, Collaboration is ultimately a people issue. However, if given Collaboration tools, inside of the BI environment (Collaborative BI, get it?) then users will be facilitated with the productivity tools assisting with the overall collaboration solution. Email doesn’t solve the collaboration solution either and there is no silver bullet.  But when it comes to analytics, having the persistent, context aware, collaboration efforts within the BI tool itself makes a lot more sense then using an email system that is inherently disconnected from the BI application in which you’ve invested to help make the best possible decisions about your business.

The last two comments listed on the Dresner post make solid points into the end user mentality behind adopting Collaborative BI. However, here again there is a slight disconnect into both what Collaborative BI is and to what extent it can actually engage business users and drive transparency. Those comments were “True BI equals transparency. It tends to let the skeletons out of the closet.” and “Many adoption issues are related [to] a cultural shift. The technology highlights how poor change management is in many organizations. Prior to implementing the collaboration technology, the lack of change management was hidden below the surface.” If we look at Collaborative BI as a tool within a tool (i.e.: within the BI system) as the definition implies, then the culture shift simply becomes using the tools that you’ve been given as you use the main BI system today.

The one commenter was spot on when she stated that “True BI equals transparency. It tends to let the skeletons out of the closet.”. Collaborative BI actually facilitates this because it can create accountability and visibility. To explain those two byproducts a bit future, I’ll use BITeamwork the Collaborative BI framework solution currently available for Oracle BI as an example. BITeamwork has taken several ideas from social networking such as the “Like” button from Facebook. When a user creates a comment in the BI system (remember Collaborative BI is within the BI System) other users can then mark their approval of the comment or appreciate its value and insightfulness by clicking a “Vote” button. Comments are then aggregated and shown by ranking on a “Most Helpful Comments” section of the BI portal. Users gain respect for their insights, they are awarded by their peers for contributing and thus more likely to contribute again. This creates a feedback loop, creates ownership, and increases the frequency by which users access the BI system.

Another example from BITeamwork for accountability is the ability to notify users when a comment is authored. So, let’s say a sales manager leaves a comment in a table cell of a revenue by sales rep table of a dashboard report. Once the comment is created several reps are notified by email immediately as part of the BITeamwork Collaborative BI solution. Since this is the single enterprise BI solution, those who were notified are accountable to respond (reply), or take action on the comment. As an advanced Collaborative BI solution, this type of communication could also be extended to the larger enterprise communication outlets such as enterprise social networking systems such as Chatter, Yammer, or WebEx Social. Collaborative BI tools should be able to notify those systems as well from within the BI tool as enterprise social networking continues to gain adoption.

I’ve completely left out the technology and technical inner pinnings of a good Collaborative BI solution. This was done on purpose as that is best suited for another conversation. What I will state, and what we’ve found out as thought leaders of Collaborative BI is that the glue that holds Collaborative BI together is context. Without context all you have is words scattered about your BI system. There is a tremendous amount of focus and effort required to technically integrate collaborative functionality within an already robust BI system. And for the last few years when the idea of Collaborative BI was a whisper, most BI vendors had their development budgets otherwise allocated. And perhaps this is truly why Collaborative BI has not taken off like a SpaceX payload. Perhaps the remedial attempts at Collaborative BI, using a simple text box on a dashboard with no features and no context, by some BI Vendors, simply left an ill taste on the palate of even the most non-discerning users. Context tell us which filters were used when a comment was created, it allows us to create a bookmark to a particular perspective – perfect if sending as a link to a Salesforce Chatter group, it allows cell comments to actually have reference to the analytics as the collaborator intended it to be seen. Without context there is no Collaborative BI.

In closing, let us not forget why companies spend millions of dollars on their BI systems in the first place. It is not just to look at a bunch of pretty charts and graphs only to say that “we have a BI tool”. BI is an investment which is made in order to make better decisions about the business, find competitive advantages, and save time conducting analytical inquiries. The more that the intelligent people within the organization can corroborate that investment and provide input, feedback, and opinions about your data and metadata, the more we will understand how valuable Collaborative BI is to the enterprise. Organizations should continue to add as many quantifiable metrics to their BI ROI as possible and Collaborative BI provides a new set of metrics to lean on. Finally, since Business Intelligence is a program, Collaborative Business Intelligence is simply the next step of user engagement, insights, and productivity in that program. Collaborative BI is the next step that every mature BI implementation should seek out with great eagerness.

Based on this type of banter from Drenser’s tribe, I’ll make more of an effort to join the weekly #BIWisdom tweetchats on twitter.

Apologies for the length of this post, I didn’t have time to make it shorter.

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Christian Screen
Christian is an innovator in analytics and data warehousing design, best practices, and delivery. With more than fifteenyears of decision support and data warehousing with key experiences at Office Depot HQ, Sierra-Cedar, and Capgemini, he oversees the Oracle Analytics Practice which includes the technical development and delivery of Oracle BI collaboration software, data warehouse solutions, Oracle BI/EPM projects, and packaged analytics solutions at Datavail.

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