Watch Out for Business Intelligence "Gotchas"

When it comes to commentary with valuable real-world insights, I can always count on the participants at my weekly #BIWisdom tweetchats on Fridays. I kicked off a recent discussion with this question to the group: “What are the top five worst practices in business intelligence?”

It took only a few minutes for them to toss out a lot more than five. As I commented then, there are a bunch of successful overachievers who participate in #BIWisdom tweetchats!

I certainly don’t want to minimize the great successes organizations are having with business intelligence. But it’s a fact that some BI initiatives sputter. So let’s look at why a BI initiative sometimes doesn’t fully deliver on its promise. Failures, after all, are very instructive.

So here’s the list we compiled —
Some of the worst mistakes organizations make in BI initiatives

Technology/tools:
" Thinking the BI toolset will make up for not understanding the business
" Thinking BI tools will solve the business problems instead of using BI to solve the problems
" Generalizing solutions or tools for all types of users – BI is not a one-size-fits-all type of solution and many “tend to implement bright shiny objects with no real understanding of whether or not it’s a good fit with their organization”

Data:
" Thinking that data quality is a technical problem
" Thinking that data quality is not everyone’s concern
" Assuming some nice-looking charts from bad underlying data is actually good BI
" Believing the same visualization will work across different datasets
" Assuming that all the data is not relevant and some should be excluded

Insights:
" Having a mindset to shoot the messenger who delivers unanticipated insights
" Being afraid to share BI insights with customers and suppliers; this comment was followed by a tweet that “sharing the insights is a good way to cement ties in the value chain and it’s good business”
" Internal or external billing for every small change to a report, analysis, etc. – “it kills what analytics is about”
" Undertaking projects that depend on looking at the existing reports and recreating in BI with no change
Training:
" Knowing how important training is but still running out of funding for it
" Believing a sales rep who says you don’t need much training – “remember, they make more from license sales”

Implementation/outset:
" Implementing BI technology without use cases
" Being unwilling to disrupt existing processes to gain the BI success
" Not resolving misalignment between IT and business users – “this results in fighting over scheduling priorities and diminished resources”
" Asking questions primarily in retrospect – “it’s much easier if questions come first”
" Not owning the biz problem – “an example: it’s in the data warehouse, so it’s not my job”
" Focusing solutions exclusively upon executives; but a tribe member tweeted that we can attribute this to a sales tactic in earlier days when it was the only way vendors could sell outside of IT since the executive team had the money to buy

Those are the frontrunners among the culprits that erode the achievable value in BI initiatives.

One of the #BIWisdom participants pointed out that many of these issues have the same root cause: lack of trust – either trusting the business users, IT or the BI “experts.” A lack of understanding about technology can breed distrust. And good communications between all involved can reduce misunderstanding up front.

The area of training I agree – recurrent training is essential for success. One of the participants tweeted that schools have finally caught on and are teaching for data enthusiasts. As she observed, these days, “everybody is a data generator and consumer. Computing and analysis are no longer synonymous with IT; they are a common way of life with everyone.” Millennials are changing the way we consume and report data, so a generational change is starting to make a difference regarding the importance of training.

Bottom line: It’s that time of year when the Internet is flooded with articles and blog posts of predictions for the upcoming year. As I often tell journalists and inquirers, I don’t have a crystal ball and don’t make predictions. But I’ll make an exception now – I predict that we’ll see even more success in BI initiatives in 2015 if organizations eliminate these “gotchas” from their practice.

Howard Dresner is president, founder and chief research officer at Dresner Advisory Services, LLC, an independent advisory firm. He is one of the foremost thought leaders in Business Intelligence and Performance Management, having coined the term “Business Intelligence” in 1989. He has published two books on the subject, The Performance Management Revolution — Business Results through Insight and Action, and Profiles in Performance — Business Intelligence Journeys and the Roadmap for Change. He hosts a weekly tweet chat (#BIWisdom) on Twitter each Friday. Prior to Dresner Advisory Services, Howard served as chief strategy officer at Hyperion Solutions and was a research fellow at Gartner, where he led its Business Intelligence research practice for 13 years.

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Have you Opened Your Business Intelligence Treasure Chest?

November 2, 2014

It happened so fast …. With one foot in the trap, it looked like he had utterly failed in his mission. … It all started nineteen years earlier when ….

Everyone likes a good story. Especially marketing teams in today’s leading businesses. They know that effective storytelling enhances brand and knocks down barriers to sales.

Similarly, it’s becoming a powerful way to distribute data and information in business intelligence initiatives. Several business intelligence vendors even promote storytelling as a needed component of data discovery.
So, with the participants in one of my recent Friday #BIWisdom tweetchats, we explored what’s happening today with BI storytelling. I started the discussion by stating that I think it’s about applying context to BI-derived content and that I see storytelling as an integral part of a broader collaborative capability.
Several agreed that storytelling is “sharing” and thus part of collaboration to bring people “through a data-driven journey” or bring the “results of statistical analysis into others’ workflows.”

Therefore, others added, collaborative features should be an integral (and easy to use) part of BI tools. But someone pointed out most BI tools today focus on the quantitative and technical areas, not experiential areas.

The discussion turned direction when a participant tweeted that storytelling is independent of any BI technology. “It’s a craft or an art, which is poorly understood and needs formal constructs,” he said. “That’s what bugs me,” someone else tweeted. “Vendors may add features to aid in storytelling, but it still needs the craft, the art of storytelling.”

One suggestion was that it might help if companies create a data template based on a narrative structure and enhancement of interactivity to enforce the story understanding. But someone countered that with an opinion that storytelling is both graphic and narrative but not necessarily interactive.

So what does the BI storytelling craft encompass? The #BIWisdom tribe’s opinions were that it must include all or most of these elements:

• Be a highly condensed story with a beginning, middle and end that is relevant to the listeners
• Have a hero — someone who accomplished something notable or noteworthy
• Incorporate a surprising element, something that shocks the listeners out of complacency and shakes up their model of reality
• Stimulate an “of course” reaction and the listener should see the obvious path to the future; get the listener “from there to here” while believing they found their own way
• Embody the desired change process
• Inform and also motivate the listener to take action or want to know more
• Create a personal connection between the listener and the message in order to change the listeners’ opinion or inspire them to undertake difficult goals to improve things

That’s a tall order.

“Should storytelling be one of the main skills of a data scientist?” asked a tribe member.
Another stated it requires good analytical skills with a good balance with visual and narrative storytelling capabilities.

Is this combination of skills available broadly? Is storytelling an innate talent, or can people be trained to become great storytellers? Can technology make a BI business user a skilled storyteller?

What do you think?

Bottom line: Just as collaborative tools don’t make organizations collaborative, data storytelling tools don’t make users good storytellers. Does that mean that data storytelling in BI tools is a red herring? I don’t think so. I believe it’s a necessary — albeit today immature — feature set that will evolve to become more effective. And people can improve their storytelling skills with training.

Storytelling is like the surprise in a treasure chest — the key to buried riches in business intelligence outcomes. If your organization hasn’t opened this treasure chest yet, don’t continue to overlook it.
The bottom line, though, is the aftermath — what happens after the data is initially presented. The carefully crafted story will not only be insightful but will also cause a reaction that leads the listeners to take action. And therein lies your buried treasure or ROI.

Howard Dresner is president, founder and chief research officer at Dresner Advisory Services, LLC, an independent advisory firm. He is one of the foremost thought leaders in Business Intelligence and Performance Management, having coined the term “Business Intelligence” in 1989. He has published two books on the subject, The Performance Management Revolution — Business Results through Insight and Action, and Profiles in Performance — Business Intelligence Journeys and the Roadmap for Change. He hosts a weekly tweet chat (#BIWisdom) on Twitter each Friday. Prior to Dresner Advisory Services, Howard served as chief strategy officer at Hyperion Solutions and was a research fellow at Gartner, where he led its Business Intelligence research practice for 13 years.

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Dresner's Point: Organizations Need to Eliminate Data Sheep in BI

Perhaps a tag with “some assembly required” should be attached to business intelligence analytics tools.

We just released in July our Advanced and Predictive Analytics Market Study report in our Wisdom of Crowds series, and I wanted to explore the topic in more depth in one of my recent Friday #BIWisdom tweetchats. Our market survey found that awareness of the importance of BI analytics is high (90 percent), but adoption of analytics tools is in the early stages of deployment even though many of the tools have been available for decades.

I asked the tweetchat tribe about the current challenges that BI analytics face (from the users’ point of view) and, as usual, they tweeted a variety of opinions.

Several agreed that the biggest challenge is there are too many solutions and thus a lot of hype, which leads to confusion. Someone else commented that it’s not there are too many tools but rather that organizations haven’t found the right ones for their industry or segment specificity.

A dominant viewpoint among the group held that a lot of the analytics tools don’t scale or perform the way they were “told and sold,” especially when it comes to accessing multiple data sources. That comment generated a resounding thumbs-up response from several in the group. One person asked how it’s possible to “see through the PR fluff to the truth.”

Cost factors into the challenges too. Several agreed that user-based, per-seat license costs are too high. Another tweeted that license is never the biggest cost but is the first one looked at and often a driver. For that reason, vendors often discount license fees. But they rarely discount services such as implementation, maintenance and support, which are also significant.

The challenge that rose to prominence in our tweetchat is the lack of training and support for analytics tools. As the #BIWisdom tribe observed:
" A big challenge is data literacy. Users can see their stats but might not know what they mean.
" Companies are scrambling for analytics talent, and software companies are touting “everyone an analyst.” But not everyone is a data analyst. However, most users need to know how to adjust two or three key variables for better output. Data fluency among users is needed. Not everyone needs to be fluent in “talking” directly to the data, but every user needs a basic understanding. So a stratified approach is needed.
" Breeding a lifetime of data analysis starts with good training and support.

Most of the group agreed that education is playing a huge part in converting traditional data users to BI, but they dismissed the notion that it’s happening quick enough for the shift to analytics and predictive analytics.

And everyone agreed that all business people need education on critical thinking to become analytically driven. One of the tribe summed up the discussion: users lacking the ability to think critically are a big BI challenge for organizations today.

Bottom line: Organizations need to avoid what I call “data sheep” – creatures with a total reliance on software tools to present analysis and data. People still need to think. Knowledge of how to create a BI plot, for instance, and which type to use, is appropriate even if a tool automates it.

Sheep need the guidance of shepherds. Training in the principles of data analysis is necessary for BI analytics success, regardless of the tool. Also, even if a tool is ideal for an organization, the company culture will likely need to adapt, which requires education.

My opinion – and not stated sheepishly – is that all obstacles that stand in the way of business insights and users need to be minimized. The best way to achieve that is through training and support.

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Howard Dresner is president, founder and chief research officer at Dresner Advisory Services, LLC,  an independent advisory firm. He is one of the foremost thought leaders in Business Intelligence and Performance Management, having coined the term “Business Intelligence” in 1989. He has published two books on the subject, The Performance Management Revolution — Business Results through Insight and Action, and Profiles in Performance — Business Intelligence Journeys and the Roadmap for Change. He hosts a weekly tweet chat (#BIWisdom) on Twitter each Friday. Prior to Dresner Advisory Services, Howard served as chief strategy officer at Hyperion Solutions and was a research fellow at Gartner, where he led its Business Intelligence research practice for 13 years.

Dresner's Point: Mobile BI on the Move

“If I’m at Starbucks doing business intelligence via WiFi with my laptop, is that Mobile BI? If so, if I do the same thing at work, what is that?” That question started the discussion at one of my recent Friday #BIWisdom tweetchats.

When the tweetchat tribe tried to level set what this booming area of business intelligence really is, we found some differing opinions.

Mobile BI supports the transient workforce, someone tweeted. No, it’s mobile because it uses mobile devices and the device facets (GPS, camera), most agreed. Example: a static BI report delivered to an iPad is Mobile BI. But another member tweeted that the Microsoft Surface Pro 3 blurs the lines, so we can’t define Mobile BI by devices; it’s just any portable workflow.

My opinion? Mobile BI allows taking fact-based insights/information on a mobile device with you to a decision point.

Our annual Wisdom of Crowds Mobile Computing / Mobile Business Intelligence Market Studies reveal a multi-year trend of growing interest in Mobile BI as well as growing sophistication on the part of users.
Almost a year ago at another of my #BIWisdom tweetchats, I asked participants for examples of where they saw Mobile BI in use. Two folks observed that they saw Mobile BI only in discrete pockets and use cases. Having said that, one added that some of the use cases were strategically critical.

The group in my recent #BIWisdom tweetchat reported they see people interacting with Mobile BI at airports, on the bus, in stores, at a supply chain distribution center, while waiting on elevators in an office building in New York City or getting real-time data on the trade floor. One of the #BIWisdom group said his client can track 30 percent of sales directly to the use of Mobile BI for sales productivity.
Someone commented that being able to take BI everywhere and have continuous accessibility makes up for the slower data speeds on a mobile device. But another wisely tweeted, “Other than the fact that I can do BI most anywhere, what does Mobile BI bring that traditional BI can’t?” One of the group said it’s the ability to interact directly with surroundings. He shared an example: GPS to filter location, then taking a picture of a store shelf for collaboration.

However, someone else questioned whether that means that collaboration must be a part of mobile BI for it to be successful. The group pondered whether mobile BI means moving from “just reporting” to “true insight” that is based on a collaborative event but decided that there are definite use cases where mobile BI adds value without collaboration.

Bottom line: In late 2013, the cost of deploying mobile hardware was prohibitive to many companies. Security was also a concern, according to our Wisdom of Crowds market study. At that time many of our survey participants stated they wanted to use Mobile BI only to view (and select and filter) information, not interact with it.

Today security is still the top obstacle to greater use of Mobile BI. Regional regulatory issues (especially in government, healthcare and banking), are also prominent concerns for Mobile BI. Even so, Mobile BI is moving up in critical priority. It’s also morphing significantly with new-generation IT infrastructure. Undoubtedly there will be security breaches – some big. That’s why it’s critical that organizations put security policy/programs in place.

Our Wisdom of Crowds market studies reveal that mobile is about new use cases and new UXs; it’s not about porting desktop BI to an external device. Most existing BI is too data dense to fit on a mobile device, so a lot of design rethinking is required. But I believe that the maturity of uses cases and benefits are more important for growing success than the maturity of Mobile BI technology.

Mobile BI is definitely on the move in user penetration and in vendor support. Already it’s no longer a market per se; it’s a feature.

Here’s what I’m watching for:

" I expect we’ll see an intersection of Mobile BI, Cloud BI, and Collaborative BI.
" All needed business intelligence features will be available on mobile devices.
" Eventually “Mobile BI” will become just “mobile” and “mobile” will just become apps in the same way that “Big Data” will eventually just become “data.”

Howard Dresner is president, founder and chief research officer at Dresner Advisory Services, LLC, an independent advisory firm. He is one of the foremost thought leaders in Business Intelligence and Performance Management, having coined the term “Business Intelligence” in 1989. He has published two books on the subject, The Performance Management Revolution — Business Results through Insight and Action, and Profiles in Performance — Business Intelligence Journeys and the Roadmap for Change. He hosts a weekly tweet chat (#BIWisdom) on Twitter each Friday. Prior to Dresner Advisory Services, Howard served as chief strategy officer at Hyperion Solutions and was a research fellow at Gartner, where he led its Business Intelligence research practice for 13 years.

Dresner's Point: Can You Have Self-Service BI and Governance Too?

I know what you’re probably thinking after reading the title of this blog post: the two are obviously a clash of interests, successful BI requires governance, there’s no middle-of-the road approach and one side will have to sacrifice its interests. You’re probably also thinking it poses a serious management challenge.
The dilemma requires some business intelligence wisdom, so I tossed the question out to the BI users, vendors and consultants in one of my Friday #BIWisdom tweetchats after a participant tweeted that he had observed a “quantum shift” to self-service in BI delivery this year.

I asked, “Self-service is important, but what about governance? Can you do both well?”

Their opinions:
- “Yes, you can, but it’s definitely a challenge. And self-service requires even stronger governance.”
- “You have to focus on value creation and shape governance to not get in the way of agility.”
- “Governance involves multiple parallel processes; and the processes need to support, not hinder, the business.”

Those processes and roles of governance include standards, policies and procedures for steering, organizing, implementing and executing BI initiatives. And it involves validating the data and ensuring data security – or as one of the tribe tweeted, “processes to stop people from doing the bad things they are tempted to do with data.”

One of the group commented that it’s important to have tools that “liberate data (for the right reasons); but there are too many tools that, at the same time, also expose the data to abuse.” Another person agreed, tweeting that departmental data discovery tools enable line-of-business user insight, but some centralized control needs to be maintained.

The group agreed that the major part of governance is security control. But they debated what should be controlled. Is it just a matter of who can see what, when, and having the proper security profiles to control that issue? Is it a matter of keeping data locked down until it’s requested and the user and data are vetted? Someone tweeted that this doesn’t seem to align with the intent of self-service BI functionality.
Another tweeted that It’s important to have democratized access to the data and not have it locked up in silos but freely available to the lines of business that need it. And someone responded that there’s nothing wrong with centrally controlling data to ensure proper usage. But another participant commented that there is currently no easy way to transform and load small amounts of data into self-service tools.

The tweets about the role of governance regarding security ignited an important question, especially when considered in the realm of self-service BI: Does governance also cover data quality? After all, bad data leads to bad decisions. The #BIWisdom tribe concluded that data quality will always be an issue in BI, and good MDM practices can mitigate the issue. Several tweeted opinions that it’s important to expose bad data. And one of the tribe pointed out that there is “no such thing as bad data; there is only bad information. The same data can be turned into useful information in a different use case.”

They concluded in agreement that the the central problem of governance is ownership of the data and the BI initiatives. And most companies don’t have a formal way of approaching this. Therein lies the crux of the matter. Where there is no ownership, there is no accountability.

Bottom line: From my years of studying successes and failures in business intelligence governance, I recommend that organizations first evaluate how their various stakeholders might use, and could benefit from, the information the data yields. Leadership need to consider risks and vulnerabilities along with advantages and then develop a comprehensive approach to governance – including self-service functionalities. It’s also important to keep in mind that, even in a self-service mode, the information/insights may be applicable and cross over to multiple areas of the organization.

As I’ve seen time and again, the best way to take this comprehensive approach is to establish a BI Competency Center (BICC). The top activities for a BICC, according to respondents in our annual Wisdom of Crowds Market Studies are analytical model development, database design/management and project management. I believe that user education also should be a primary objective for a BICC.
So, yes, you can do self-service and governance well. If the BICC (or other non-siloed governance mechanisms) is effective and relevant to the enterprise business, self-service BI functionalities won’t be a vulnerability.

Howard Dresner is president, founder and chief research officer at Dresner Advisory Services, LLC, an independent advisory firm. He is one of the foremost thought leaders in Business Intelligence and Performance Management, having coined the term “Business Intelligence” in 1989. He has published two books on the subject, The Performance Management Revolution — Business Results through Insight and Action, and Profiles in Performance — Business Intelligence Journeys and the Roadmap for Change. He hosts a weekly tweet chat (#BIWisdom) on Twitter each Friday. Prior to Dresner Advisory Services, Howard served as chief strategy officer at Hyperion Solutions and was a research fellow at Gartner, where he led its Business Intelligence research practice for 13 years.

Dresner’s Point: Don’t Overlook the Zigzagging of Collaboration & Text Analytics

Missed the boat. Didn’t gather enough steam. All that glitters isn’t gold. These pronouncements are often the verdict when technology evolves quickly and some functionalities or features don’t grab a strong enough hold quickly enough in the market. But applying that verdict to collaboration BI as well as social media and text analytics would be a mistake, even though they haven’t met expectations.

Collaboration BI

At one of my weekly #BIWisdom tweetchats this month, collaboration, social media and text analytics turned up in a discussion about 2013 BI predictions that didn’t pan out. The tweets started with one of the tribe commenting that “every year we hear collaboration BI will take off — but has it?”

I commented to the group that our annual Wisdom of Crowds® Business Intelligence Market Study revealed in 2013 that collaboration in BI is hotter than ever, but it declined somewhat in favor of email as the preferred collaboration tool.

That was quickly followed up with a participant’s tweet that she saw two new BI products this month that offer collaboration as their core feature.

Then came a bunch of opinions from the group on why collaborative BI is difficult to adopt. Here’s their collective viewpoint:

• “Collaboration must have a foundation in the business; it’s not something that can be pushed from a BI tool.”
• “Collaboration is a business issue, not a BI issue. Technology is a facilitator, not the solution.”
• “True BI equals transparency. It tends to let the skeletons out of the closet.”
• “Many adoption issues are related 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.”

I agree! In fact I wrote a book about the Achilles heel in BI performance: success requires change management, not just technology.

Text analytics and social media

These two aspects of BI products have bagged some successes, yet our 2013 Wisdom of Crowds® Business Intelligence Market Study indicated a failing interest in both social media and text analytics. I asked the #BIWisdom tribe of buyers, vendors and consultants for their opinions on the factors behind this finding.

Here’s their real-world wisdom:

The value

• “Analysts have said there is more to be gained in ‘dark data’ around the enterprise than in social media data/sentiment.”
• “But what analysts say and what business wants sometimes differs. It’s a question of perspectives and relative value.”

The technology

• “I’m not sure the state-of-the-art technology is good enough yet.”
• “Text analysis and social media require extra effort, which increases the time to value. Vendors need to automate and decrease that effort.”
• “I tested a social analytics tool; I was less than impressed. It was keyboard based and turned up a lot of false positives.”
• “This needs more machine learning algorithms than most tools use today. Social analytics that lack natural language and sentiment analysis are of very limited value. Keywords won’t cut it.”
• “In text analytics the ability to combine analysis of text + numbers is key.”
• “Point-in-time relevance is an important component of using text and social media data. The data gets stale too quickly. Need speed.”

The demand

• “We keep hearing from clients that they want it!”
• “Companies want it but aren’t really sure what they need. I think it will be like CRM in the 1990s, a distracting shiny object until it’s better understood.”
• “It’s not like ERP data analysis, but we find the interest is still there. The question is how to do it well.”

Bottom line: What can we conclude from the fact that adoption of BI collaboration, social media and text analytics fell short of expectations in 2013? Don’t count them out of the picture. Although their journey to greater adoption zigzagged over the past year, customers want these functionalities to help create greater value as they build on their prior business intelligence successes. In fact, text analytics had a strong showing in the #BIWisdom group’s plans and aspirations for 2014. These three functionalities in BI technology are not yet in the ninth inning. Look for an upswing in adoption.

Howard Dresner is president, founder and chief research officer at Dresner Advisory Services, LLC, an independent advisory firm. He is one of the foremost thought leaders in Business Intelligence and Performance Management, having coined the term “Business Intelligence” in 1989. He has published two books on the subject, The Performance Management Revolution — Business Results through Insight and Action, and Profiles in Performance — Business Intelligence Journeys and the Roadmap for Change. He hosts a weekly tweet chat (#BIWisdom) on Twitter each Friday. Prior to Dresner Advisory Services, Howard served as chief strategy officer at Hyperion Solutions and was a research fellow at Gartner, where he led its Business Intelligence research practice for 13 years.

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Dresner’s Point: Ready for the “2014ization” of Business Intelligence?

I don’t like making predictions, so rest assured this is not another of a myriad of predictions articles that hit the media annually. Instead, let’s kick start the year with some definite plans and aspirations of companies in the business intelligence sphere. A great place for an insightful, real-world view of BI trends is my weekly #BIWisdom tweetchats with BI customers, vendors and consultants.

What is your organization planning to try to achieve in 2014? When I recently asked the #BIWisdom tribe this question, their tweets made it immediately clear that their companies are gearing up for achieving even greater value from business intelligence than they have to date.

Plans Include:

• More mobile BI
• More BI demos with real-life applications
• Get more into mobile BI as it helps to reach the masses and get closer to “Information Democracy”
• Explore the sharing potential of BI and the power to integrate additional sources at any point in the BI stack
• BI methodology is big on our checklist for this year
• Get up to speed with some of the specialized tools in the BI stack; it’s hard to keep up with the toolsets released so far for data integration, data quality, data management and data security
• Migrating to current versions of BI software; for innovations in BI software you need the newest versions. Examples: user empowerment and the speed of getting answers (not just reports)
• There is a growing interest in data that tells stories; keep up with advances in storyboarding to package visual analytics that might fill some gaps in communication and collaboration
• Monitor rumblings about trend to shift data to secure storage outside the U.S. due to the NSA revelations
• Expand basic BI to more users (not just multi-page dashboards, but targeted BI); mobile BI will certainly drive the expansion
• Have BI super-users engage with others to expand the penetration of BI among users
• Increase use of self-service products to provide more value and increase adoption of BI tools

Aspirations:

• More predictive analytics to learn more about Big Data
• Expand more into embedded BI
• Do more with text analytics; there’s a lot to mine from text analysis

Location intelligence:

The group also tweeted about a new thrust in business intelligence functionality — location intelligence or location analytics. Will it have legs in 2014, I asked? Definitely, they responded.
One person tweeted: “I’m close to this topic and see activity and a lot of interest growing in this area.”
Another tweeted, “Through the use of location analytics organization can see new patterns in their data that graphs and charts don’t reveal.”

Mobile and location are intertwined — two sides of the same coin — so it should have legs this year. Here at Dresner Advisory Services we’ll publish a report on our first Wisdom of Crowds® Market Study on Location Intelligence in February 2014.

Bottom line:

The #BIWisdom tribe’s tweets aren’t mere hopes. These folks are not punching above their weight. They have experienced success with BI so far and are building on that success to mine for greater value.

Judging by their comments, we have new BI trends to monitor as we watch the “2014ization” of BI unfold. Which trends will rise to prominence?

I’d love to know what plans and aspirations your company has for 2014. Please post your comment.

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Howard Dresner is president, founder and chief research officer at Dresner Advisory Services, LLC, an independent advisory firm. He is one of the foremost thought leaders in Business Intelligence and Performance Management, having coined the term “Business Intelligence” in 1989. He has published two books on the subject, The Performance Management Revolution — Business Results through Insight and Action, and Profiles in Performance — Business Intelligence Journeys and the Roadmap for Change. He hosts a weekly tweet chat (#BIWisdom) on Twitter each Friday. Prior to Dresner Advisory Services, Howard served as chief strategy officer at Hyperion Solutions and was a research fellow at Gartner, where he led its Business Intelligence research practice for 13 years.