As businesses start to look at the role of social media within their organizations on a deeper level, many will develop deeper connections integrating social networking concepts into their daily business processes. An article that was just posted on DashboardInsight discusses this concept further: The Convergence Of Social Media And BI.

• Cost savings – as mentioned above and may include hardware/software, licensing, maintenance fees, etc.
• Time savings – employee production and better decision making
• Process automation – includes the time saved on report/analytics creation

it can be hard to ascertain qualitative benefits of BI.  Companies feel that they are better able to make decisions based on the increase in information visibility, but attaching this to revenue growth and overall productivity is not always easy. For instance, marketers are constantly trying to identify the success of their marketing campaigns.  This may include defining the correlation between individual campaigns and lead generation or online marketing activities or advertisements and an increase in sales.  Unfortunately, it is not always easy to identify where opportunities are generated and the correlations that exist between marketing initiatives and sales.

The same difficulty exists in identifying ROI for BI.  How do organizations define the extra value they incur through BI adoption and calculate ROI to take into account the additional factors that bring added business value beyond the quantifiable BI benefits?

Please share your BI ROI success stories.

Adding to this is the way solution providers like iWay, Dataflux, Kalido, etc. are building broader platforms to address the issues associated with data management and not just one area of data warehousing or master data management.  By combining areas within the realm of data management, organizations can now address their overarching data issues that affect all initiatives related to customer experience, suppliers, partner networks, performance, and the like. Couple this with BI and end user driven applications and businesses can develop a roadmap for successful data management and visibility initiatives.

Overall, what this means for organizations is that solution providers are moving into the realm of full-service solutions.  Whether through acquisitions such as the Oracles, SAP’s, and IBM’s of the world, or through enhancing market offerings, vendors are starting to develop a more holistic approach to effective business driven decision making and its convergence with data management.  As many solution providers offer business user focused applications, the market turns towards the demands of making everything available.  This means that the ability to access information from any vantage point is no longer enough.  Organizations require the ability to access the information they need when they require it, in any fashion to make informed decisions.  Add to this the integration of data management and data governance practices, and businesses can now develop a holistic approach  to data management that will help them achieve the TCO and ROI that has so long been elusive within BI environments.

It seems like organizations’ MDM is paved with good intentions but that many businesses are still struggling with how to move to the next level towards integrating data governance through business process and policy integration with master data management initiatives and concepts. As mentioned at the conference, because technology is so advanced and consumers can get what they want when they want it, the way any organization differentiates itself from the pack is through providing more value to customers through the relationships they build and service they provide.  To just compete on price, or to offer extra incentives, may get a customer to initially try a service or product, but will rarely keep them satisfied.  Consequently, successful MDM initiatives, coupled with data governance offers businesses the first step of giving their customers better service and tailoring offerings to individual needs.  The role of unstructured data will only continue to increase as businesses looking to move to the next stage within their MDM lifecycle look at ways to adapt to the needs of their customers in an ever changing market place.

The first includes the use of text analytics and importing external data sources to gain a broader picture of what is happening within an industry, with competitors, or insights into product perceptions.  The second relates to the idea of integrating social media functionality into business intelligence applications.  The premise behind which, is to make BI accessible to the masses, easily consumable, and increase its overall value proposition.

Lyzasoft is one solution provider that has taken the second concept surrounding social media and ease of use to design and develop their BI platform to create a collaborative and self-service approach to BI using a social media framework.  In a recent interview with Scott Davis, co-founder of Lyzasoft, he discussed some trends that have led us to the ability to the necessity to combine social media with BI to create the business value and interactivity essential for businesses.  The two main shifts are “from a technology perspective that put us in a situation where some things that we used to have to regard as scarce are now regarded as essentially free (i.e. storage space, bandwidth, etc.); and a demographic shift, where we’re seeing the first cohort of people entering the workforce who have been online for their entire lives, have been involved with digital tools and digital communities and that shapes what they are capable of and what they expect. These two trends coupled with the radical increase in the digitization of records and data as a result pose substantial challenges to traditional BI.” Because of these shifts in technology and users, solution providers are starting to integrate this functionality into their products.  Most, however, still are far from developing a social media centric approach to BI in the same way as Lyzasoft.

Overall, Lyzasoft hopes to bring three things to end users.  The first is to enable customers “on their own, to explore, gather, put together, and harvest information. Basically, bring together information from a lot of different sources and stitch together a picture of the interconnectedness of this organism which is the enterprise.” The second is analysis and involves pulling apart, deconstructing, comparing, and the like to gain the insights required to make valuable business decisions. The third is where the social media aspect of Lyzasoft really takes hold. As Scott describes it, “how do we share, communicate, distribute, coordinate, and collaborate on the analysis?” That means developing an interactive framework to let customers interact with one another by posting analyses in blogs, having discussions, sharing information, and the like.

Overall, there are always positive and negative aspects to any solution available in the market.  One of the positives about Lyzasoft is that they have developed a product that provides a true set of differentiators from competitive solutions.

The concept of online privacy and the ability to communicate within private communities is limited by the fact that online social communities collect information about members, whether or not they share that information more broadly. Consequently, companies will use profiles to identify types of customers they are interested in targeting or offer free products to people based on profile preferences or online conversations.  Granted, this is great for marketing campaigns and trying out new strategies, but becomes a little bit over done when looking at the expectation of privacy that people no longer have.

Social media analytics gives companies the ability to gain a broader view of an organization’s market and potential customers.  Because marketing activities are so hard to measure, this new way to evaluate product “buzz” and develop collaborations between social media and marketing activities can help companies develop more formalized structures to measure the success of their marketing campaigns and develop a more targeted approach to marketing by developing a more personalized approach to marketing in general.

On the other side of things, people who may want to remain anonymous may be slowly losing that option. Obviously this involves discretion from the side of social networkers themselves, but the fact is that more and more companies are using solutions and applying analytics similar to Attunity360 to identify data collaborations between online conversations and associated information about the people participating in those conversations. As these solutions become more popular, the way businesses develop and manage their marketing activities will change to directly target consumers based on their online profiles and information available.

1. Identifying the business purpose – Any BI project or data warehouse evaluation needs to start with a business pain or the identification of a gap within the business.  Whether this includes the ability to identify trends over time, increase analytics capabilities, or meet compliance requirements, it is impossible to successfully implement a data warehouse without defining a business need. 

1. Data sources – Looking at where data comes from and how many sources are required may affect overall solution choice. In addition to the purposes behind implementing a data warehouse mentioned above, many companies require a full view of what is happening within the organization that the use of operational systems doesn’t give them.  For instance, information related to customers and their overall lifecycle might reside in multiple systems.  Within a data warehouse, this data can be consolidated so that decision makers can see customer actions over time and link them to marketing campaigns, identify general trends in demographics, or identify potential gaps in operations.

1. Data volumes – How much data and how often data needs to be updated can affect solution choice.  Some data warehousing solutions are optimized for larger data sets, while others pride themselves on query performance.  There really is no one size fits all solution when it comes to data warehousing so organizations should try to match their business requirements to the solutions available in the market without trying to implement something that is outside the scope of their needs.

1. Outputs – Identifying the output required means looking at whether the data warehouse will be used as a business intelligence back-end, to stream operational data for general analytics, or to perform extensive analytics.  Information requirements for general reporting or dashboards will be different than those used for predictive analytics or risk identification and mitigation.

These four items don’t represent all of the considerations when looking at a data warehousing solution, but do identify some preliminary requirements that should be considered to identify the right solution for the organization.

Overall, unlike other companies that take awhile to get their act together regarding planning and publicly announcing their roadmaps after an acquisition, SAP tends to get the ball rolling fairly quickly – with a good example being their acquisition of Business Objects a couple of years ago.  The interesting area for those in BI will be how much of Sybase’s database solutions remain independent or end up being slowly integrated into the SAP stack.  Even though Business Objects is still technically it’s own entity in relation to product offerings, their focus in relation to marketing and product design is heavy integration with SAP and a focus on providing solutions for SAP data.

Looking at the acquisition more broadly, Prakash Kannoth, Technology executive at ITQuadrant recently posted a blog on ebizQ mentioning the importance of mobile infrastructure and CEP technologies.  Consequently, this will probably be the areas of most benefit to SAP over time.

Dashboard Purpose

By starting with the business pain, decision makers can limit their dashboard choice to one that meets their specific business requirements.  For example, some companies require operational dashboards to help them manage their call centers, whereas other businesses use dashboards to make sure that overall performance is on track and to flag potential discrepancies in set metrics.

Current IT/BI Environment

What currently exists in-house may affect the organization’s dashboard choice.  Some dashboards integrate easily with many data sources, while others base their platforms on Microsoft integration.  This means that some solutions may not be available to organizations depending upon their current IT environment.  In addition, companies with a mature BI infrastructure may want to continue to expand their current platform because it falls within their comfort zone and current framework, as opposed to evaluating the best alternatives.

Data Sources

Aside from technical environments that may become inhibitors to selection choice, it is important to note that not all dashboards are created equally.  Some enable decision makers to combine disparate data sources within one chart, while others may offer the ability to compare separate data sources on the same dashboard, but not within the same chart, graph, or chart.  Consequently, organizations should look at what types of data they are using and whether data from multiple sources have to be combined to gain the desired insights.

Timeliness

When the information is required may change the overall solution choice.  For instance, some dashboards stream data from operational systems regularly to help managers look at information in near real-time, whereas other dashboards grab data from the data warehouse and represents aggregates of information to identify sales over time, or to monitor key performance indicators.

End User Interface

The last consideration is the type of people using the dashboard.  Depending on who will be accessing the data, what interactivity requirements they have, and their level of technical savvy, the solution choice will differ.  Luckily, solutions exist for all types of end users.  Some businesses want their employees to develop their own analytics and general dashboards, whereas others require tightly controlled access to information.  Either way, depending on what information people access, how comfortable they are interacting with technology, and changing needs over time, the type of solution will be affected by who is accessing the solution.