The Magical BI Adoption Formula: Embedded BI 

One of the aspects I appreciate about the #BIWisdom tweetchats I conduct each Friday on Twitter is that the participants dont sidestep any issues. Of course, we cant be too long-winded in a 140-character tweet anyway, but often their comments are pithy  like the woman who dubbed embedded BI as the magical BI adoption formula in the recent tweetchat about the embedded BI market study report we recently published. Thats a much faster, bottom-line way to convey what Ive advocated for several years  that it could help get more eyes on the data and is a great way to engage users in BI in the context of a familiar application.

But, of course, there is also great value in having BI instrumentation above the applications. What about top-down BI vs. embedded BI? Is it a non-issue? Are both necessary? Those are the thought-provoking questions I posed to #BIWisdom participants recently. 

Someone tweeted, I submit that companies often think embedded BI has the same ... continued

Is Artificial Intelligence the Future of Business Intelligence?

There is a lot of buzz these days on artificial intelligence (AI) in business intelligence products. At a recent tweetchat of my #BIWisdom group of users, vendors and consultants, a participant asked: Is AI becoming a part of everything we do, the way analytics have been added to apps of all shapes and sizes across the business and personal space?

Although companies tend to overreact to emerging technologies, AI is not a new technology.  One of the tweetchat participants commented that AI is crossing a chasm, either in awareness or approach and that perhaps its evolution to this point is due to the prevalence of data scientists. Another member of the group agreed, tweeting that the data scientists craze has helped more organizations embrace machine learning and AI to get deeper insights. He added that analytics doesnt give enough deep insights.

Learn more about this topic at our upcoming Real ... continued

Introducing The Real Business Intelligence Conference

Many organizations focus upon technology as a means of enhancing user perspective and fact-based decision-making. And, while technology is an important enabler, it’s a relatively small part of the equation. We know that the essential ingredients for success lie with people, process and organization - enabled by technology. We’ve long believed that there’s a need for a fresh in-person forum for business and IT leaders to help achieve success with information, business intelligence and analytics.

Accordingly, the Real Business IntelligenceTM conference is different from others you may have attended because it's NOT about technology. Rather it's focused on strategies for success with business intelligence, analytics, performance management and information management (e.g., people, process and organization supported by technology).

Designed as an interactive executive forum, we’ll be focusing upon topics which enable attendees to help their respective ... continued

Looking Past the Hype of Big Data’s Impact on Business Intelligence

Over the years of our weekly #BIWisdom tweetchats, one of the topics that continues to pop up in our tweeted discussions is big data. The perception of its value in business intelligence has changed over time. In 2015, most participants in our tweetchats observed that a few real use cases existed but adoption of big data was mostly modest and still characterized by hype as much as substance. One of the participants tweeted that “Gartner had predicted we’d be done with the term big data by February 2015, but they were wrong.”

In January 2016 when I asked the #BIWisdom tribe to share their BI resolutions for the year, it was clear that many of their companies were looking to use big data to solve business problems. High on their agendas were:

“Which of our customers are not profitable for us and why?” “What percentage of our customers are experiencing the level of service we intend?”

Five months later, the big data talk among our group revolved ... continued

Advanced and Predictive Analytics 2016

This past August, we released our third annual Advanced and Predictive Analytics Report - building upon our previous years' work and highlighting the ongoing changes to this space.

We define Advanced and Predictive Analytics (APA) as including statistics, modeling, machine learning and data mining to analyze facts to make predictions about future or otherwise unknown events. Our new APA report also introduces the role of citizen data scientist, which describes a role that might be business analyst or BI user but a person who is nonetheless able to generate models for advanced and predictive analytics.

Here are three high level takeaways to keep in mind as you evaluate existing or potential APA investments in your organization:


1. Selective Use: While certain organizations are well-invested in advanced and predictive analytics, overall penetration and current use remains low at just 24 percent (and declined slightly year over year). Coupled ... continued

Best Approaches for Developing KPIs for Business Intelligence

I recently asked a provocative question in one of my weekly #BIWisdom tweetchat sessions: In the age of discovery and cognitive BI, are Key Performance Indicators (KPIs) going to remain relevant?

Someone tweeted a quick answer: If you dont have KPIs, how do you know if youre succeeding? Another participant commented that most places where she has worked had KPIs and it was sometimes part of the appraisal process. 

Some #BIWisdom attendees who are BI users as well as vendors and consultants shared their opinions about whats wrong with KPIs. They mentioned that the average BI user doesnt understand what makes up a good KPI. And most companies have too many KPIs. Or that KPIs are misused and then drive the wrong results. Someone else tweeted about the problem of KPIs using absolutes and not normalizing and that normalizing KPIs helps prevent irrational goals and the resulting bad behavior that can follow.

I asked for the groups opinions on how to ... continued

Collective Insights 2016: Three Takeaways

In April, we published our inaugural Collective Insights research report, which builds upon our view of Collaborative Business Intelligence by adding an important, emergent dynamic to the mix: user governance. Where collaborative business intelligence is a process that develops a common, shared understanding that improves decision-making, user governance - the policies and controls for directing content creation and sharing - improve information consistency and accelerates that group-based decision-making.


Here are three high level takeaways to keep in mind as you evaluate the collaboration and user governance initiatives in your organization. 
 
1. Collaboration is Important: A solid majority (65 percent) considers collaborative BI either "critical" (21 percent) or "very important" and say collaboration does translate to BI success. Collaboration (14th) and governance (11th) rank above the middle of 30 topics under study at Dresner Advisory Services ... continued

Cloud Computing and Cloud BI 2016: Three Takeaways

In March, we publishd our fifth assessment of the cloud BI arena, which finds us at a period of expectation leveling. Attitudes toward cloud BI and cloud generally remain at mid-tier importance among BI priorities. Sentiment has cooled slightly from the blue-sky days, consistent with maturing technology markets.

Here are three high level takeaways to keep in mind as you evaluate the cloud and cloud BI initiatives in your organization.  

1. Slow March to Public: Across five years of data, actual use and favorable attitudes toward future use of public (multitenant) cloud BI have steadily increased and future. plans for public cloud BI use now slightly eclipse private cloud use. Industry support has likewise shifted toward public cloud year over year. Future cloud BI investment will also be slightly higher for public than for private cloud models; few plan decreased cloud BI investments in any model.

2. Cloud BI Still Looks Like BI: Regardless of ... continued

Examine the DNA in Your Business Intelligence Implementation

The media and news outlets over the past few years have highlighted powerful results from DNA research and studying the genetic features, components and characteristics of human cells, viruses, etc. Have you ever thought about the DNA of a business intelligence implementation? It’s not a far-fetched idea. Medical practitioners’ ability to diagnose diseases early on or diagnose a person’s genetic susceptibility to certain diseases has greatly improved thanks to DNA research. Why not apply the thinking to BI “DNAcomponents” that result in a success or failure?

I define a failed BI initiative as one that doesn’t reach its full potential. The implementation phase is fertile ground for a potential BI failure. In fact, a poor approach to BI implementation is one of the most-often cited factors by respondents in our annual Wisdom of Crowds business intelligence market studies.

So it was no surprise to me when a participant in one of my recent Friday #BIWisdom ... continued

End User Data Preparation: Three Takeaways

Our latest report on end user data preparation is our second assessment of the landscape and is already one of our most popular reports. We define end user data preparation as “a self service capability for end users to model, prepare, and combine data prior to analysis.”

The “end user” in this case usually sits at the decision-making end of the business and demands creative autonomy to manipulate internal and external data resources free of IT dependency. These roles draw a bright spotlight and more than a little executive scrutiny.

As you review the current state and future needs for end user data preparation in your organization, here are three high level takeaways to keep in mind as you dig into our latest findings.

1. Tip of the spear: Though it sits somewhere in the middle of business intelligence technology and initiative priorities, end user data prep consumers are key players in optimizing organizational initiatives through their analysis, ... continued

Collaborative Business Intelligence is a Diamond in the Rough

Here’s a serious number: $31.5 billion a year. Unfortunately, it’s not a revenue growth indicator. It’s how much Fortune 500 companies lose per year because of not sharing knowledge, according to an IDC study. Consider that $31.5 billion in light of the necessity for idea/insight sharing in the Digital Age, “Sharing Economy,” and innovation happening through the Internet of Things, and it’s easy to see that the number could quickly grow even larger.

The goal of collaboration is to improve an outcome; collaboration results in decision-making information (and even solutions to business problems) that are greater than one person can create. Certainly this is essential in this new business world where human-performed work is quickly becoming more knowledge based and sharing business intelligence and experience is a key to success in innovation and agility,.

So why the $31.5 billion annual loss? Why isn’t collaboration happening more? I posed this question to my ... continued

Are BI Vendors Missing the Boat for Customer Success?

There are moments when you realize that you discovered something important. That happened to me recently after I spoke with business intelligence vendors that have customer success programs – yet their customers remain unhappy. Of course you could make a case that the customers didn’t train their users well enough on the BI tools or that the implementation wasn’t smooth or they had bad data.

I brought up this issue in one my recent Friday #BIWisdom tweet chats, where participants include vendors, customers, analysts and consultants. Their immediate reaction was similar to the aftermath of a storm. Quiet. The usually boisterous group with quickly tweeted opinions was quiet and didn’t tweet for a few minutes. I could almost hear their minds churning through their thoughts. Their initial tweets finally came, and it was easy to see that neither customers nor vendors had much experience with customer success programs.

“What is the definition of what a customer ... continued

6 Things to Know When Increasing User Adoption of BI

Wouldn’t it be great if every time we start a new endeavor experts pave the way to our success with a list of “never do this” and “always do this” advice? Especially when an endeavor appears deceptively simply but has hidden pitfalls. That’s the case with efforts to gain deeper penetration – increase user adoption – of business intelligence solutions within an organization. And there’s a lot of that going around these days.

Some companies have found their footing with BI after initial projects to see if it delivers on its promises and now are off and running. Others started out with just executives and management as users and now want to spread BI across the organization to gain even greater beneficial insights. And a third segment are completely new to BI and want to make sure their implementation and user adoption are successful.

In a couple of sessions of my Friday #BIWisdom tweetchats, I asked participants to share their real-world kernels of wisdom on ... continued

Internet of Things Makes Some Aspects of BI More Crucial

My favorite latest sensor, trakdot.com, lets me know where my luggage is when I land from an air flight. It’s just one in a myriad of devices in the Internet of Things, which delivers vast amounts of diverse information concerning surroundings, people and various assets. The IoT’s opportunities for businesses are exciting, and it’s already clear that sensor data is and will continue to be a game changer in many areas.

The Internet of Things makes business intelligence solutions and analytics essential, so we decided to explore the IoT implications in one of my recent #BIWisdom tweetchat sessions. We started with this question: What does the IoT do to BI corporate infrastructure?

Someone tweeted that it will challenge many legacy setups that were “built in knee-jerk fashion.” Another commented that the data preparation / modeling stage will be more crucial than ever before.

Then came another question: “Is the IoT a way that Hadoop will finally be ... continued

Collaborative Computing and BI,2015: Three Takeaways

Recently we published our fourth annual Wisdom of Crowds Collaborative Computing and Business Intelligence Market Study.

At the highest level, collaborative support for group-based analysis remains a mid-tier BI priority in 2015, behind dashboards and data warehousing, yet ahead of topics including cloud BI, big data and social media analysis. A majority consider both collaborative BI and enterprise frameworks, at minimum, important.

Collaboration is integral to most business activities. Today, organizations have more tools and channels by which to collaborate than at any time in history. Our report documents – from traditional to contemporary – the many ways individuals share business intelligence in group collaboration. We asked users and the industry to explain what they prioritize and what makes them successful. We pay special attention to collaboration features baked into BI software and the extensions and frameworks that support group projects and ... continued

Cloud Computing and BI 2015: Three Takeaways

Cloud-based business intelligence is now an ingrained practice at many organizations – maybe even your own. More than half of the respondents to our 2015 Cloud/Cloud BI study agree that cloud BI is important, very important or critical to their operations and planning. More than half use or plan to use cloud BI in the near future.

But other organizations are plainly and sometimes painfully stalled. The “great wave” of cloud BI is almost surely going to arrive piece by piece and not universally. Right now, private cloud models are preferred but some departments crave public cloud solutions. Organizations are wrestling third-party data that sometimes arrives with its own tools and analytics. Standards and security are known and unknown hurdles to adoption.

Here are three takeaways to keep in mind as you evaluate cloud BI in your own organization:

1. Cloud BI is still BI. Interest in cloud BI features is increasing, but, public or private, users want ... continued

Will 2015 be the Year for Operational BI & Hybrid EDW?

Tweets flew back and forth quickly at one my recent Friday #BIWisdom tweetchats. The tribe really got into sharing their opinions of where BI is today – thanks to hopes for advancements in 2014 that were achieved or remain unfulfilled – and opinions about what BI technologies organizations will invest in during 2015.

Here are their top observations regarding what’s gaining buzz for growth and investments for 2015:

- Natural language processing (NLP)
- Infographics
- Streaming BI due to the Internet of Things 
- In-memory analytical sandboxes sitting above a hybrid EDW with traditional and non-traditional sources
- Operational BI

The #BIWisdom group took off on a discussion of operational BI. Someone questioned whether it will get bogged down in big
data hype and whether it can progress on its own. Another tweeted that “operational BI teams with data providers and
data integration (DI) tools are the next bastion of BI ... continued

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
" ... continued

Have you Opened Your Business Intelligence Treasure Chest?

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 ... continued

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 ... continued