Social business intelligence is a convergence of several trends: It's business intelligence plus knowledge management, plus social networking and collaboration, plus social media monitoring and analytics, all combined into a new interface in the business intelligence environment.
Enterprise Apps Today recently caught up with James Kobielus, senior analyst at Forrester Research, to discuss what you need to know about social business intelligence.
Enterprise Apps Today: With the rise of social business intelligence, do you see a fundamental change in BI solutions?
Kobielus: Social business intelligence is about bringing more collaboration into your own BI experience. Traditionally, BI has been about reporting, dashboards and ad hoc queries, and it's been about the ability to track key business performance and metrics. Traditional BI has been focused on delivering intelligence from data warehouses and other databases, rather than directly from the other users.
Social BI is bringing a collaborative experience into your BI environment, which means that more and more of the BI tools that are available today are allowing users to ask questions of each other and quite often to link those questions to specific reports or visualizations that are presented in their BI environment.
So, to answer the question, it's really not so much of a fundamental change as a long-running trend in the BI industry to bring more of this collaborative capability into the core experience. What we're seeing now is that there's more of an uptake of more Facebook or Twitter style interfaces within the BI tools generally.
Enterprise Apps Today: What does social business intelligence have to offer companies? What are the benefits of incorporating social data into BI analysis? What are the challenges?
Kobielus: In addition to bringing more of a social networking style interface to the BI arena, social BI is also bringing a broader range of types of data from different sources into the BI environment. The big new growth area is in bringing unstructured and semi-structured information from social media sites into the overall BI and analytics environment. One of the many reasons to do this is that social networks like Facebook and Twitter are goldmines of customer intelligence. Companies can find out what their customers really think about them, about their products, or whether their customers even think about them at all. By mining tweets, status updates and blogs, marketing and brand management professionals everywhere are investing heavily in the backend tools that can essentially crawl and apply natural language processing to all of this social media information.
What everyone is doing, or wants to do, is to be able to take that intelligence in real-time and bring it into the data warehouse to be correlated with other sources of customer intelligence and then deliver it downstream to their traditional BI environment. Additionally, the information can be delivered to predictive modeling tools that can be used to do some heavy-hitting data mining to look for historical trends. Bringing social data into business intelligence analysis helps deliver a 360-degree, intimate portrait of customers, their demographics and their psychographics, to get a better idea of how they might react to various sales strategies.
Companies need to decide what social web sources and social data they actually require to feed into their various key business decisions, whether those decisions are related to marketing, promotions or pricing. Another challenge will be implementing the appropriate backend tools to discover this information, to crawl it, to process it, to do the essential language processing, sentiment monitoring and so forth.
Incorporating that intelligence into a data warehouse can be a huge challenge. A typical data warehouse with no more than 10 terabytes of storage capacity isn't going to hold hundreds of terabytes or even petabytes of fresh market intelligence that can potentially stream in from social media on a daily basis. How much of that data can you afford to incorporate into your data warehouse for delivery to your BI application? What percentage of all that intelligence sourced from the social web do you choose just to ignore because you have no place to store it or maintain it?
A typical BI user who is only doing historical reporting but is considering moving into data mining and predictive modeling on social web intelligence should first ascertain if they have the right tools, and the talent to work with those tools. Establishing a predictive modeling effort is a major undertaking, and bringing social data into the mix adds a whole new universe of predictive modeling tools. If you haven't been paying attention to what's been going on in the advanced analytics market in the past few years, you probably have the wrong tools to do this kind of analysis.
Enterprise Apps Today: What are the inherent risks associated with social BI?
Kobielus: Social BI in one core sense is the collaborative knowledge-sharing interface on Business Intelligence. Traditional BI is all about the data, the single source of truth — the current official customer records and the financial records that are all in one place on the data warehouse.
The inherent risk associated with BI is if key decisions are based not only on the official reference data pulled from the data warehouse and their BI tools, but also from information pulled from other areas. If decisions are made on information that is not the official, sanctioned version of those records, there is a very great risk that an inadvertent mistake could result in a bad decision, with dire consequences. The whole notion of the single version of truth, which is what the data warehouse is set up to store, manage and deliver downstream to the BI tools, can be compromised.
Enterprise Apps Today: Are enterprises dragging their heels when it comes to implementing social BI, or are they beginning to embrace the idea?
Kobielus: Many enterprises are still dragging their heels when it comes to implementing social BI. In many ways, social BI is still a forward- or future-looking approach. Most BI in the world is not social, but rather pulls the data from a data warehouse, as opposed to enabling person-to-person knowledge sharing. There is already some implementation of social BI because collaboration functionality is already incorporated into some of the leading BI tools. However, collaborative use of social BI capabilities is not yet a widespread practice in the business world. Enterprises are still evaluating social BI, and some early adopters are using quasi-Facebook interfaces within BI tools.
Enterprise Apps Today: What does an organization need to consider to prepare for social BI implementation?
Kobielus: They need to know whether their own established BI vendor is incorporating, or plans to incorporate, social BI interfaces into their product, and if so, when and which social features. I don't see many business users abandoning their current BI vendor because its offerings lack social capabilities. They need to know that this is not necessarily something that you need to jump ship on immediately. Rest assured that most BI vendors have or will have social functionality in their product in the next year or so.
BI as a space continues to evolve, overlapping significantly with other well established spaces. There's no clean delineation where traditional BI leaves off and social BI picks up because traditional BI is a moving target. Every couple of years it adds an additional layer of functionality that used to be bells and whistles but now is inherent. I think the social interface in the next year or two will become pretty much standard everywhere. Already, many of the leading tools, such as IBM Cognos, Qlikview, Microsoft PowerPivot, and TIBCO Spotfire, have already incorporated social BI functionality.
For more on enterprise uses of social media, see Who is Leading in Social CRM?