Social Media and BI - Part 3 & 4

Well, due to a change in roles, I will be closing down my blog. Here are the last 2 parts to Social Media and BI - Enjoy! And stay tuned to a future blog on Project and Portfolio Management.

Extending Business Intelligence to Social Media

Web 2.0 applications are revolutionising the way that we interact with the web. Most of the existing Social Media examples mentioned in this article exist as a result of new innovations in web application developments. Web 2.0 doesn’t necessarily refer to a new technological advancement in the Web itself, but rather a group of technologies that have advanced Web usage and turned the web into a development platform for the enterprise. ^{(Ferguson 2007)}  Many of the innovations in Web 2.0 leverage applications that include the ability to read/write on the Web. The World Wide Web inventor Tim Berners-Lee insists that the original vision of the Web was to provide “a collaborative medium, a place where we [could] all meet and read and write” ^{(BBC 2005)} so the term “Web 2.0” is somewhat of an actualisation of that vision.

Some of the innovations in Web 2.0 technologies include:

·      Blogs

·      Wikis

·      Mashups

·      RSS (Really Simple Syndication)

·      Search & Tags

While this is not an all-encompassing list, these technologies are tightly linked with Social Media and increasingly developed in Business Intelligence platforms. These are examples of how BI can be actively extended to include Social Media using the latest Web technologies.

Blogs as an Enhancer to BI

Blogs are an excellent way to share opinions and ideas to a wider community on the Web in an easy-to-use manner. If you are able to open an online bank account, or write an article in a word processor you already have the required skills to create and manage a blog. The usability of a blog, in combination with BI can be very powerful for enhancing the information provided through enterprise BI platforms.

What a blog can do in the context of BI is provide an opportunity for the producers of the dashboards or other type of reports to create a forum for users to comment and share interpretations of the information they are viewing. This type of forum can also be encouraging for analysts and executives alike to become more engaged with the information they are viewing. The dashboard or report with the additional commentary enhances the overall quality of the published information. When a business user creates a report, they may select it and publish it for the explicit purpose to get feedback from the community of users.

Security needs to be a consideration with this type of collaborative environment, but with attention to the different profile of user to be in line with the profiles of the dashboard and report viewers this is an easy hurdle to overcome to add value to distributed information.

How a BI Wiki Can Work For You

Wikis are quite similar to blogs in that many people are able to contribute and extend the information that may be published in a BI platform. The major difference is that with a wiki it is possible to edit what other people may have written. Wikis provide a structured way for a group of people to edit and collaborate on a specific subject area with each person contributing as much or as little as they want to the topic. A wiki (like a blog) can enrich the information provided through an enterprise BI platform by providing a collaboration vehicle to either educate on business practices or performance at a departmental or enterprise level. An example could be a wiki about the common uses and characteristics from a product that a company offers that is linked or viewed through a sales dashboard. The wiki can provide a “FAQ” for the salespeople accessing these relevant dashboards. The salespeople may choose to help edit the different entries as each of the products mature in the marketplace or extend the information regarding their experiences. 

Mashing Up BI Information

Mashups are a simple concept and currently most enterprise BI platforms offer the capability to “mashup” information. The mashup term arose and became popular in the music industry through the introduction of two or more different songs, and two or more different music styles into one musical accompaniment. In a business context, this is the combining of a multitude of different data sources using a variety of different technologies to provide enhanced BI information. The information sources could also include a variety of different Social Media types.

A BI mashup may include geographical representation of sales, with inventory levels, combined with a wiki on the service offerings. This concept is not new, and in a lot of ways this is essentially what business intelligence is. The value comes in taking advantage of new Web 2.0 technologies embedded in many of the BI software vendor offerings to provide business users with multiple streams of information in a self-service environment. The user experience is enhanced greatly, especially when external information such as news, investor information and relevant search capability from the Web is embedded to expand the value of the BI landing page.

Streaming Information with an RSS

Really Simple Syndication (RSS) feeds are widely available in most web browsers and email clients. It enables one click subscription to websites, blogs or BI websites to provide a simple alert that something has been added to the source. From an email client, the alert looks like a new email message that arrived in the business users inbox. Probably the single biggest advantage to the use of RSS feeds is ease of use. Every user in a company is familiar with an email client. Additions to the relevant BI pages can be delivered through the subscription service. This brings us to the other very important feature of RSS in that user doesn’t have to login and access their personalised BI page, but are alerted to changes relating to their function. If they choose to investigate further, they can click on the link and login to do further analysis. This provides more pervasive information in a way that business users can evaluate quickly resulting in a more productive workforce. Subscribers to RSS feeds can select organisational blogs or wikis that get updated daily or with each post so there is a constant awareness of their colleagues activities relating to the business.

Finding and Organising BI Information with Search & Tags

The use of advanced search and tags is another Web 2.0 innovation that found extensive use in Social Media and can be applied in a BI framework to traditional BI data and to the Social Media applications in the enterprise. Tags are a way to visually represent and organise information on the Web as well as provide advanced search criteria. In the context of a BI platform, a business analyst may want the ability to tag to give additional meaning to the information presented in a dashboard or web page. If an analyst produces a report that shows product sales by region, it helps to introduce additional information (even from the accompanying commentary) that can give a more “human” meaning to the information. In this instances tags such as “sales”, “region”, “product X”, “profit”, “market penetration” and “sales utility” can all produce additional information that can be searched on and assist with interpretation of the report. A tag cloud visually represents the information in the web site showing common searched terms or frequency of the words such as in Fig. 5, which shows a tag cloud for this article.

Fig.5 – A Tag Cloud for this Article

The value tag clouds and enhanced search can bring across Social Media and BI is mainly in accessibility and usability of the information. Tag clouds and enhanced search can be used in Social Media elements in the organisation in order to navigate from BI dashboards to Social Media enhancers ultimately developing the information and making it interactive and navigation user-dependant.

Incorporating Social Media into Business Intelligence

As we’ve moved along the gradient in Fig. 4, we’ve explored how BI can be used passively to monitor Social Media and how BI and Social Media can be blended within an organisation to improve the value of the information to the business stakeholders. In the last stop, we extend the BI platform into the Social Media forums to encourage those outside of the organisation to explore and improve BI data and representations of that data.

Open source BI is an example of the use of social media in order to facilitate the development of BI solutions. Eclipse (http://www.eclipse.org/) works with contributors from all over the Web to develop its open source BIRT (Business Intelligence and Reporting Tools). While this isn’t a great example of how Social Media (such as Twitter, YouTube etc) has facilitated specific changes to BI, it does show how a community of users can collaborate on a project using many of the same Web 2.0 technologies to influence the direction of BI software.

A stronger representation providing a looking glass into how Social Media is used to create, share and provide a true interactive community for BI is through public BI galleries such as those provided by software vendor Tableau ^{(Tableau Software 2011)}. Tableau Public offers individuals the capability to create a user account, download Tableau BI software, conduct online training and then get started with creating their own BI visualisations. The creator then uses the Tableau Public site to publish their charts and other visual representations for other visitors to share with Tweets, and Facebook posts. The forum can also be used to promote businesses or even the written articles that were improved with the Tableau visualisations. There are visualisations showing everything from an “Earthquake map of New Zealand” to “Social Network Market Share”. The immediate ROI may not be clear with this type of investment of time in creating these visualisations, but for a company involved in the development of BI software the ROI is extremely evident. With more people trained, using Tableau BI, and embedding the results across the Web, Tableau is creating a real presence for its BI software. It can also use the information from the community of users to determine where to focus development. This really blurs the lines of BI and Social Media and shows how BI can be put in the hands of and defined by the masses.

Conclusion

Social media and BI are in an exciting stage in the Gartner hype cycle ^{(Gartner 2010)} where mainstream adoption could be as long as 5-10 years out for technologies such as collaborative decision making or as soon as 2-5 years away for mainstream use of Web 2.0 and BI. Expect to see more vendors including the capability to reach out and make sense of the background social media noise and be prepared to revolutionise the way you work with others through blogs, videos, wikis and other interactive ways in the increasingly “virtual” office. Embarking on a journey to gain competitive advantage with any new technology is met with risk since the market is still trying to work out what will return the most value in social media.

Two statements worth pondering are that:

1) Higher risk means higher reward

2) There is immense value with clever interpretation of social media interactions.

A calculated assessment of your use of social media and BI is a good place to start followed by a way to incorporate passive and active engagement with Social Media to realise value.

Works Cited

Allen, Tom. Harvard Business School. http://hbswk.hbs.edu/archive/1691.html (accessed March 10, 2011).

BBC. Berners-Lee on the read/write web. 09 August 2005. http://news.bbc.co.uk/2/hi/technology/4132752.stm (accessed March 10, 2011).

Chadha, Karan. Can Social Media be the Next Big Lever for Business Intelligence? 07 February 2011. http://www.cmswire.com/cms/web-engagement/can-social-media-be-the-next-big-lever-for-business-intelligence-010118.php (accessed March 10, 2011).

Facebook. Press Room: Facebook. 2011. http://www.facebook.com/press/info.php?statistics (accessed March 10, 2011).

Ferguson, Mike. Web 2.0 and Business Intelligence. 07 September 2007. http://www.b-eye-network.co.uk/view/5913 (accessed March 10, 2011).

Gartner. Employing Social Media for Business Impact: Key Collective Behavior Patterns. White Paper, Gartner, 2011.

Gartner. Hype Cycle for Business Intelligence, 2010. Research Paper, Gartner, 2010.

Humphries, Matthew. Geek.com. 03 March 2010. http://www.geek.com/articles/chips/twitter-and-facebook-generated-9-million-for-dell-last-year-2010033/ (accessed March 10, 2011).

Olcaytocengiz. olcaytocengiz.com. http://olcaytocengiz.com/tag/social-media/ (accessed March 10, 2011).

Solis, Brian. Brian Solis - Defining Social Media. 2007. http://www.briansolis.com/2010/01/defining-social-media-the-saga-continues/ (accessed March 10, 2011).

Tableau Software. Tableau Public. 2011. http://www.tableausoftware.com/public/gallery (accessed March 10, 2011).

Twitter. Twitter About. 2011. http://twitter.com/about (accessed March 10, 2011).

Wikipedia. Wikipedia. 2011. http://en.wikipedia.org/wiki/Special:Statistics (accessed March 10, 2011).

—. WikiPedia Business Intelligence. 2006. en.wikipedia.org/wiki/Business_intelligence .

Yahoo! News. Yahoo! News. 01 March 2011. http://news.yahoo.com/s/mashable/20110301/tc_mashable/cocacola_to_help_maroon_5_crowdsource_a_new_song (accessed March 2011, 2011).

YouTube. YouTube Press Statistics. 2011. http://www.youtube.com/t/press_statistics (accessed March 10, 2011).

 

Social Media And BI - Part 2 of 4

This is a 4 part series that explores BI and Social Media.

Part 2

Part 1 explored the emergence of social media and collaborative decision making. In Part 2  we explore the different role of social media and the scales of engagement.

Customers and Social Media

From the social media statistics quoted earlier, it is easy to see how a walk down the street would reveal customers, people, employees, students that are getting involved in making their thoughts known online in a collaborative fashion. These groups of people are almost all consumers and will play a role in how your company is perceived in the market, develops its products, is serviced by corporate entities and whether they will want to work for you in the future. While it is almost a certainty that they will become involved in social media of some description, the question is how involved? There is a spectrum of engagement in social media that is worth exploring before uncovering the value that these participants can provide since this involvement has a direct relationship with value.

Fig. 3 – Examples of Participant Involvement in Social Media

Referring back to the original examples from the introduction, participants in social media can have a very passive involvement but still contribute to the overall theme or meme and ultimately still have a big impact on how one is perceived depending on how influential this individual is. Twitter has also been renowned as a crowdsourcing vehicle. In crowdsourcing, an individual or company looks to a wider audience (crowd) in order to assist with gathering ideas, content or general assistance in resolving a problem. Although this is off the topic of BI and Social Media, it is interesting to realise how powerful and lateral crowdsourcing and passive Social Media can be. In a more interesting example, Coca-Cola will use a combination of Twitter and Facebook to crowdsource a new song for Maroon 5 ^{(Yahoo! News 2011)}. Fans will be able to provide feedback during a 24 hour period where Maroon 5 will develop lyrics and sounds for immediate feedback. Both Coca-Cola and Maroon 5 will benefit from the exposure and create a new way for them to interact with their customers.

Moving along the spectrum to a more collaborative style of social media is YouTube. Subscribers and users of YouTube have a more active engagement with Twitter in that rather than simply tweeting thoughts to a wider community there is the opportunity to truly interact with the other users in a meaningful way by commenting on uploads, viewing videos, uploading videos and developing user profiles to create a true web presence and identity. The value in a collaborative type of social media is not so much on an individual contribution, but rather on the aggregation and analysis of a group of people sharing common ideas. If you were to search on YouTube for “funny cat videos” and only 1 video were displayed with a funny cat, this might be interesting (and hopefully humorous) but the impact to what you might do from a marketing and sales perspective would likely be minimal. The reality is that a search on YouTube using these key words returns over 755,000 results with the top funny cat video being viewed almost 50 million times! This isn’t necessarily an indication that you should move into the business of making funny cat videos, but knowing this content and these categories can be mined from collaborative Social Media networks can be powerful in devising the next marketing campaign or investment in social causes such as the Royal Society for the Prevention of Cruelty to Animals (RSPCA) in the event where funny cat videos are in favour.

In the most involved category of Social Media are examples like Wikipedia where a community of users is actively creating, editing, reviewing and sharing ideas to create something that the world can benefit from. These active participants are quite different from the majority of passive contributors. These are people that have a vested interest and are emotionally attached to the outcomes and products produced. The Wikimedia Foundation operates some of the largest collaboratively edited reference projects in the world, including Wikipedia and the extent of involvement is a clear indicator that people are willing to contribute online to something they believe in. Understanding that there is a massive community that is willing to actively participate is a first step. The next is to use expertise location techniques (potentially evolving into your BI platform) to understand who in the community of customers may be willing to become contributors to the betterment of your product or service. An electronics manufacturer found that there was a customer who understood its products as well as the engineers who designed them.^{(Gartner 2011)} By identifying this talented individual and proposing they become involved with online help the company was able to better serve its customers and reduce customer service costs.

Using BI to Deliver Value from Customers Using Social Media

The story of the poor beggar is a reminder of what can happen when we don’t notice what simply standing up and doing things differently can find. A poor beggar sat on a box for years and asked for money from passer-bys. One day a rich man asked, “What’s in the box you are sitting on?” Surprised and somewhat annoyed the beggar stood up and looked inside the box he had been sitting on for years. To his surprise it was filled with gold. To look inside the box and discover how much gold is there for you, it is useful to refer to a framework for an outward-looking model of Business Intelligence and Social Media.

                                   

Fig. 4 – Applying BI to Social Media and Social Media to BI

The spectrum in Fig. 4 represents ways in which to engage the Social Media content to add value and accumulate knowledge about customers, suppliers, partners, investors and other stakeholders in order to achieve a competitive advantage. Broadly speaking depending on the application of technology, the type of industry, external stakeholder involvement and a variety of other factors will determine the actual value that your organisation will receive. One of the biggest challenges of using BI with Social Media information is the unstructured nature of the data. I will try to address these questions through each topical area.

Moving from left to right (passive to active) across the spectrum, the categories can be summarised as:

·      Using Business Intelligence to Analyse Social Media

·      Extending Business Intelligence to Social Media

·      Incorporating Social Media into Business Intelligence

Using Business Intelligence to Analyse Social Media

Any marketer will get excited at the prospect of uncovering information about her customers. Even better, in the sales department the rising and extensive use of Social Media such as Twitter and Facebook have contributed $9 million ^{(Humphries 2010)} to the top line at Dell through its more than 3.5 million followers in 2009. So the big question is “How can I mine this information to turn it into more sales, higher customer satisfaction, lower costs and decreased customer churn?” A good starting point is to start using business intelligence analytics to identify the major trends in the market that you are interested in.

The challenge is easily recognisable. There is an immense amount of information and interactions. The volumes that were referred to in the introduction is incredibly vast, and arguably the information largely not useful for the business purposes of your organisation. The data is fluid, and not meaningful unless the context of the text, video or sound is fully understood. If I did a search on Twitter for “Coca Cola” and “happy” one might think that the responses would all be positive for the brand. Having done the search, it is true that generally these encapsulate a trend of loyalty to the brand such as “Coca Cola makes people happy” from one Tweet. On the other hand there is another that states “Happy Mardi Gras(: tonight's the last night for Coca Cola for me :(“ These reveal two very different messages about the brand.

Social Media Intelligence (SMI) tools are developed and evolving to make sense of Social Media in the context of your company and its initiatives. Karan Chadha of Infosys summarises the key functions of SMI tools^{(Chadha 2011)} :

·      Geographic and Demographic Bucketing: An insight like “half the people liked this new launch and half didn't” is far less useful than an insight like “most of the teens liked it and most of the middle aged didn't.” These kind of bucketed insights empower companies to prepare segment specific strategies.

·      Knowing the Influencers: Among millions of participants on the social space, there are a few who drive conversations and play a critical role in shaping opinions. For instance, a few social activists can frantically post all over the social space about environmental unfriendliness of a new product and thus influence opinions of many. Several SMI tools provide this feature of identifying such opinion leaders giving companies a chance to foster relationships with them.

·      Red Flag Alerts: Several SMI tools provide red flag alerts when a situation demands an immediate action. For instance, a company comes up with a new version of its free-to-download music player software having a critical bug. An SMI tool, by analysing comments over Social Media space will raise a red flag thus alerting the company. This insight gives the company an option to immediately fix the bug and put it back thus preventing a widespread loss of face.

Tying this back as a passive approach to monitoring Social Media interactions, it is important to evaluate the type of monitoring that will be most useful and provide the highest return on investment in your industry. Even though the technology to understand human languages at a meaningful level is still in the future, the high-level classification of interaction types as they pertain to business functions can provide immediate value.

Social Media And BI - Part 1 of 4

This is a 4 part series that explores BI and Social Media.

Introduction

In this digital age, there is virtually no way to escape it. Facebook reports they have more than 500 million active users ^{(Facebook 2011)} ,  Twitter boasts over 95 million tweets per day ^{(Twitter 2011)} , and YouTube announced that it passed 2 billion views per day ^{(YouTube 2011)} … Almost a year ago! Wikipedia has had almost 500 million page edits ^{(Wikipedia 2011)} by contributors since its founding. The message is clear. Social media is here to stay and it is a tool that you should capitalise on. In 1999 it was Microsoft who completely changed their strategy in order to capitalise on the latest trend. Up to that point, Bill Gates was stuck on the concept of PC-based solutions and arguably saved his company by recognising the importance in this evolving technology. That technology is famously the internet and the flip-flop on strategy to leverage the web rather than fear it changed the world we live in today. This is an example of what could have happened if Microsoft had missed what was seemingly an obvious goldmine of opportunity.

It is a prudent exercise to revisit some terms that happen to be the topic of this paper. Since both of these areas are constantly evolving (just like the English language), it is acceptable to select one that is in the spirit of the concepts and supportive in a way that allows this evolution to occur. It is a certainty that these terms are widely misinterpreted and misused in businesses today.

I have chosen a 2006 Wikipedia definition of business intelligence. If you were to search the term today you will find that it has changed and has become much narrower and focussed on systems and software. The earlier definition captures a broader meaning behind business intelligence in an organisation. This definition also doesn’t limit the information to what can be found inside the systems of a company, but describes it more broadly as incorporating information from other sources such as those found in social media.

Business Intelligence (BI): is the process of gathering information in the field of business. It can be described as the process of enhancing data into information and then into knowledge. Business intelligence is carried out to gain sustainable competitive advantage, and is a valuable core competence in some instances. ^{(Wikipedia 2006)}

Social Media: is the democratization of content and the understanding of the role people play in the process of not only reading and disseminating information, but also how they share and create content for others to participate. It is the shift from a broadcast mechanism to a many-to-many model, rooted in a conversational format between authors and people. Social media describes the online tools that people use to share content, profiles, opinions, insights, experiences, perspectives and media itself, thus facilitating conversations and interaction online between groups of people. These tools include, message boards, podcasts, micro-blogs, lifestreams, bookmarks, networks, communities, wikis, and vlogs. ^{(Solis 2007)}

Fig.1 - Social Media Collection and Classification ^{(Olcaytocengiz n.d.)}

The definition on Wikipedia and even generally in the social media field is still on a journey as the wider populations become more in tune with the impact this will have on every person wired to the web. Again, the concept of a broader definition that allows growth and incorporation of other ideas is useful to bear in mind as these concepts are communicated to the business.

In Fig. 1 there is a visual representation of some of the growing number of social media services available for individuals to present their views, thoughts, images, feelings and tastes to a wider audience. Social media truly represents a shift from institutional control to consumer control. This shift is why companies are so interested. If you follow the audience, you follow the money. If you are able to understand the habits and behaviours of this audience (whether they are an employee or customer), the ability to unlock value is certainly not that far behind.

The convergence of business intelligence and social media is focused on gathering and making sense of information published by social media networks. The value of this analysis can generally be examined from an internal (employees) or external (customer/supplier/partner) perspective. Gaining knowledge from the social interactions of all individuals that touch your organisation will give you a competitive advantage…if you are doing it better than your competitor that is!

Collaborative Decision Making

One of the emerging concepts that looks to unlock value within an organisation using business intelligence and social media is collaborative decision making (CDM) platforms. Every company is organised around workgroups often loosely defined functionally. In addition to the segregation based upon roles and function, there is a physical separation as well. Sales people sit with sales people, finance mingles with finance and product development are locked away somewhere from everyone else. I am always reminded of Tom Allen’s “30-meter rule” ^{(Allen n.d.)} when I think about lost potential in a company due to the low likelihood of interaction due to spatial or role-based reasons. In Allen’s studies, he found that engineers and scientists whose desks are more than 30 metres apart have a communication frequency of almost zero. Incredibly, it was found that the relationship between the volume of communication between co-workers was in inverse proportion to the distance they sat from each other at work. This study was completed before the rise of email and social media and could be used to explain why water-cooler talk seemed to be so invaluable. This demonstrates the natural tendency of humans to feel limited by distance. CDM platforms provide a means to have a “virtual water-cooler” to enhance overall communication.

One of the pre-suppositions of CDM is that an enhancement of the overall communication and collaboration in a company is a valuable thing. In instances where sales communicate regularly with Product Development, Marketing aligns and talks to Sales and Finance regularly visits IT. According to Gartner “CDM improves the quality and transparency of decisions by bringing together the right decision makers and information, assisted by the relevant decision tools and templates, to examine an issue, brainstorm and evaluate options and agree on a course of action.” ^{(Gartner 2010)} There should be countless examples how an organisation’s effectiveness can be improved by the introduction of CDM platforms.

CDM platforms combine business intelligence with social networking, collaboration, decision tools and workflow to help make and capture better decisions. Social networking in this instance refers to making use of social media such as wikis, vlogs, forums and blogs to enhance an organisation’s interactions. Social networks have evolved to include multi-dimensional connections with real conversations between users. 

There are at least two ways in which BI and CDW are converging. Software vendors are increasingly enhancing their BI platforms to include elements of social media, while others have built their solutions with social media in mind. Lyza (www.lyzasoft.com) provides a way for business analysts to complete analysis such as querying a data source and producing a dashboard, which is not uncommon for any BI tool. The difference is that the dashboard or other information can then be disseminated to what Lyza calls its “Lyza Common” where members in the workgroup can then blog, rate, forward, search and comment on the business intelligence results. The applications for this approach to BI can be profound. The users of the information are able to play an active role in enhancing the output through social commentary. Analysts can respond to the feedback. Users of the information can participate in the shaping of the information and identify any shortcomings in the information that was provided. In a way, it really personalises the delivery of BI from the perspective of an end consumer of the information and the analyst who is delivering it as an information caretaker. This is a radical approach to BI and over the next 18 months as vendors provide more options; other unexpected benefits will surely emerge. One example that comes to mind is when a project manager used BI to deliver project-tracking metrics to her team. In an environment where deadlines and internal expectations are paramount, it is vital to have honest, open communication with the team. The project manager utilised social media to provide a forum for the team to anonymously submit feedback on the timelines and tasks to understand if the goals were achievable. In a perfect world the team would have open channels of communication, but this allowed individuals that were non-confrontational in nature to stream feedback across multiple regions to the project head allowing her to have a clear understanding of the project status from the team.

While there is importance in finding ways to improve and deliver BI within the social network at the office, there is also value in applying BI to the CDM platform and other means of communication within the business, which highlights the other intersection. Learning how departments and functions relate to each other at a macro level can help drive internal operational strategies. For instance, if customer satisfaction with a product is at a low as determined from feedback surveys, the obvious next step is to discover why customers aren’t happy with the product. Is it the quality? Expectations of what the product could deliver? Using the latter example, assuming the customers weren’t provided with a product they were expecting, then how can we work towards resolving this issue and why did the problem occur in the first place? By applying BI to the social interactions, one can create a social map of the interactions to determine where the problem might exist.

Fig.2 – Internal Social Network Analytics

In the simplified example in Fig. 2 using business intelligence to monitor the social media has uncovered that Product Development is regularly in contact with Customer Service rather than marketing. This could be for a variety of reasons including that because of dissatisfaction with the product, customer service representatives are often in contact with the Product Development team to solve or query the issue. The real opportunity and a way to future-proof new innovations is to improve social interactions between Product Development or potentially with the customers themselves. It is increasingly common for expert users of a product to either advise Product Development teams or become part of Customer Care. Regardless of the approach, this demonstrates the value of having this type of information readily available to a business embarking on a social media initiative.

Part II in 2 weeks....

Gartner Information Management Summit : Feb 22nd & 23rd

This is a re-post of a note from Gartner. I thought these were interesting trends. Make sure you attend the Summit to find out more!

As technology, market and management trends begin to transform BIIM and analytics, understanding and embracing these impending changes is critical in order to improve performance and your organization’s success. According to Gartner, there are four trends that BIIM and analytics leaders need to embrace, which are highlighted in this month’s e-newsletter. You can learn more at the upcoming Gartner Business Intelligence & Information Management Summit, 22 – 23 February, Sydney, Australia.

Four key BI predictions to help organizations plan for 2011 and beyond

1. By 2013, 33% of BI functionality will be consumed via handheld devices.
   
   Current adoption rates and the broad availability of mobile devices are promising to quickly generate a strong wave of mobile BI users. At first, mobile BI will consist largely of existing reports and dashboards ported to the mobile device. By 2012, organizations and vendors will develop mobile analytic applications for specific tasks or domains. Mobile BI will significantly expand the population of BI users to include a more mainstream audience and this opportunity will attract significant investment.
2. By 2014, 30% of analytic applications will use in-memory functions to add scale and computational speed.
   
   By 2014, 30% of analytic applications will use proactive, predictive and forecasting capabilities. The growing use of sophisticated analytic functions will accelerate the growth of the performance management and the analytic application market. Packaged applications will incorporate data and text mining, forecasting and regression, optimization, scoring and simulations using complex business rules and data modelling. As the speed-of-response and data volumes increase, organizations will look for columnar data repositories and in-memory online analytical processing that is faster and easier to architect.
3. By 2014, 40% of business analytics expenditure will go to system integrators, not software vendors.
   
   The growth of user-driven initiatives, external information sources and the integration of unstructured content make the traditional approach of buying products almost exclusively from software companies and system integrators increasingly risky and potentially uncompetitive. Buyers can now evaluate total packages and select a lead provider, often a service provider to deliver it.
4. By 2013, 15% of BI deployments will combine BI, collaboration and social software into decision-making environments.
   
   Organizations are starting to piece together collaboration technology, social software and BI to create collaborative decision-making environments. These efforts will continue to grow as organizations start to more proactively manage, capture and optimize decision processes and outcomes to improve performance beyond the decision inputs such as BI.

For a comprehensive look at Gartner recommendations for these predictions and today’s hottest BI priorities, join us in 2 weeks!

For full details on the comprehensive agenda program, visit gartner.com/ap/bi.

3 WAYS TO REGISTER:
Online: gartner.com/ap/bi
Phone: +61 2 8569 7622
E-mail: apac.registration@gartner.com