{"id":9445,"date":"2015-08-18T10:30:58","date_gmt":"2015-08-18T15:30:58","guid":{"rendered":"http:\/\/www.mrc-productivity.com\/blog\/?p=9445"},"modified":"2015-08-18T14:59:28","modified_gmt":"2015-08-18T19:59:28","slug":"6-common-misconceptions-of-self-service-bi","status":"publish","type":"post","link":"https:\/\/www.mrc-productivity.com\/blog\/2015\/08\/6-common-misconceptions-of-self-service-bi\/","title":{"rendered":"6 common misconceptions of self-service BI"},"content":{"rendered":"

\"Education\"Summary: Despite it’s growing popularity, many myths still surround self-service BI. These myths can lead to implementations that aren’t as successful as they could be, or flat-out fail. Learn about the common myths\/misconceptions that businesses have about self-service BI, and why they’re false.<\/em>
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Self-service Business Intelligence (BI) is one of the fastest growing trends in the business world. Industry analysts like Forrester and Gartner agree: Self-service BI is exploding, and shows no signs of slowing down. <\/p>\n

Why the rapid growth? Self-service BI offers businesses a tempting benefit: It promises to give business users direct access to data and reporting capabilities. It promises to remove the reporting burden from the IT department, and bring data access directly to the decision makers.<\/p>\n

Who doesn\u2019t want that?<\/p>\n

But, there\u2019s a problem: Self-service BI efforts often go wrong. The business enters the project with high expectations, only to face disappointment. <\/p>\n

Why? Many businesses don\u2019t have a realistic view of self-service BI. They believe some common myths that still surround the topic. These myths can lead to implementations that don\u2019t meet expectations, or flat-out fail. <\/p>\n

Today, let\u2019s dispel these myths. Here are a few of the most common misconceptions surrounding self-service BI:<\/p>\n

1. If we build it, they will come<\/h3>\n
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In a perfect world, end users will flock to the self-service BI tool and immediately begin running their own queries and generating reports. Unfortunately, we don\u2019t live in a perfect world.<\/p>\n

If you give your users a self-service BI tool, will all of them dive into their data and pull out meaningful insights? No. Let\u2019s take a look at two key problems that get in the way of this goal.<\/p>\n

First, few users actually understand the data. As explained below, users cannot gain insight unless they understand how the data was collected, how it\u2019s integrated, and what the various data elements mean.<\/p>\n

\n\u201cOne of the most dangerous myths about self-service BI is the “Field of Dreams” approach to analytics (i.e., “build it and they will come!”),\u201d says Douglas Briggs<\/span><\/a>, Director, Business Intelligence at Washington University in St. Louis. \u201cIt’s deeply tempting to hope that simply by making data available and training business users on reporting tools, they will then dive into the ocean of data and emerge with valuable insights that lead to meaningful improvements in processes and products. While business users *can* do this, it’s only possible when they understand how the data has been made available to them: how it was collected, how it’s been integrated with other data, and what the various data elements mean (beyond merely their labels — what sources they originate from and how they’ve been transformed before they arrive in the analytics environment). This keeps user from combining data in ways that it wasn’t meant to be, leading to conclusions that are nonsensical or (worse yet) reasonable-seeming and yet erroneous! Organizations that deploy self-service BI effectively often make an expert in the data available so that business users can validate their analyses and insights and develop over time their own savvy with the data they need to create real insights.\u201d\n<\/p><\/blockquote>\n

The second reason: Not every user wants to create their own queries and dive into their data. Some users want their reports, and little else. Ideally, they want their reports created by someone else. They\u2019re just not interested in exploring the data. <\/p>\n

Does this mean that self-service BI is a waste? Not at all. Many users will jump at this opportunity. They want to explore their data. They want to run queries. They will become the report creators. Just understand that not every user cares about data exploration. <\/p>\n

2. Self-service BI eliminates the need for IT<\/h3>\n

The goal of self-service BI: Put data in the user\u2019s hands and reduce the burden on the IT department. But, many make the assumption that it shifts 100% of the BI process to the users. <\/p>\n

Is that accurate? Not at all. In reality, you\u2019ll still need the IT department for some tasks.<\/p>\n

For instance, self-service BI will only produce great results if you have clean, well-modeled data. Is that a job for end users? No! You still need your BI team or IT department to set up the data. <\/p>\n

Also, not every report or query will be straightforward. Sure, self-service BI will eliminate a large portion of the reporting requests. But, you\u2019ll still need the IT department for the more complex applications.<\/p>\n

\n\u201cSelf-service BI does remove much of the reporting burden from the IT department,\u201d says Rick Hurckes, Services Director at mrc<\/span><\/a>. \u201cBut, it doesn\u2019t eliminate IT from the equation–and that\u2019s a good thing. The IT department must control the data and the user access. They\u2019re responsible for keeping the data clean, and ensuring that users can only access data they\u2019re authorized to see. The self-service BI tool only acts as a doorway for users to access the IT-controlled data.\u201d\n<\/p><\/blockquote>\n

3. A good self-service BI tool will lead to a successful project<\/h3>\n
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This is a big misconception that we see over and over again. Many organizations assume that they\u2019ll find a BI tool that will fix all of their data and reporting problems. When the project fails, they blame it on a bad tool.<\/p>\n

In fact, many even buy multiple tools when they discover that the first one didn\u2019t fix their problems. After a while, they\u2019re stuck with multiple tools–none of which helped them. <\/p>\n

Why not? BI failures<\/span><\/a> rarely stem from the tool itself. <\/p>\n

In reality, BI success depends more on the data quality, data control, and business processes than anything else. Those are the foundational elements. It\u2019s like building a house. If you build a house on top of a weak foundation, the quality of the house itself doesn\u2019t matter. The weak foundation will eventually destroy the house.<\/p>\n

Business Intelligence is the same way. If you struggle with your foundational elements, no BI tool will be successful. A great tool applied to bad data\/processes will not succeed.<\/p>\n

4. The tool should be \u201cplug and play\u201d<\/h3>\n

Some organizations assume a BI tool should \u201cjust work\u201d out of the box. They treat it like a simple piece of software–just install it and go. In reality, this is nowhere near accurate. Self-service BI requires a great deal of planning and preparation before it\u2019s ever deployed.<\/p>\n

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\u201cThe biggest misconception I see is companies assuming BI platforms being plug-and-play,\u201d says Ryan O’Donnell, Director of Marketing at Avalara TrustFile<\/span><\/a>. \u201cAssuming integration will be quick and easy is a flawed approach. Companies need to dig in and read the docs to understand how to set up their BI platforms correctly from the start. Failure to do so results in wasted time as engineers have to go back in and make changes \/ updates after release.\u201d<\/p>\n<\/blockquote>\n

The big problem with the plug-and-play myth: It ignores the importance of clean data. Data that hasn\u2019t been scrubbed, or even set up properly, will destroy a BI project. Users won\u2019t be able to create the reports they need, or (even worse) will create inaccurate reports.<\/p>\n

In my experience, the most successful self-service BI projects aren\u2019t accidents. They\u2019re the result of proper planning and data organization before the tool is ever deployed.<\/p>\n

5. Users will understand how to use it<\/h3>\n

The rise of mobile apps has created unrealistic expectations with business software. Some users expect they can just pick up a tool and start using it. They expect that all software should be self-explanatory.<\/p>\n

\n\u201cEvery individual within an organization may not be at the same competency level to first understand the platform, and second to go about creating a compelling data story or answer critical business questions about revenue, gaps, performance, product offerings, deals and more,\u201d explains Anees Merchant, Senior Vice President – Digital, for Blueocean Market Intelligence<\/span><\/a>. \u201cTo be successful, business stakeholders need to be coached throughout the development plan and adoption process.\u201d\n<\/p><\/blockquote>\n

In reality, a good self-service BI tool isn\u2019t something your users can just pick up and start using. While many expect them to provide \u201capp-like\u201d simplicity, self-service BI is infinitely more complex than most mobile apps, and provides far more capabilities. It requires proper training–both in the tool, and the business data. <\/p>\n

6. All self-service BI tools are essentially the same<\/h3>\n

This may seem obvious, but I\u2019ve actually heard this one a few times from different IT leaders. They believe that any self-service BI tool they purchase will provide the same features. <\/p>\n

In a way, they\u2019re half right. Yes, all BI tools will let you create basic reports and dashboards. But, after you get past the basics, you\u2019ll find some significant differences.<\/p>\n

For instance…<\/p>\n

Does it offer mobile capabilities?<\/p>\n

How well does it integrate with your current systems?<\/p>\n

Does it let users upload spreadsheets, and export to Excel?<\/p>\n

What security features does it offer?<\/p>\n

Many of these \u201cextra\u201d features get ignored, but can make or break a project. I know of a company who had to cancel a big BI project because the tool they were using didn\u2019t offer multi-tenant security. They went into the project assuming it was included, and discovered that fact halfway through.<\/p>\n

The truth is, self-service BI tools will provide similar reporting options. But after that, they differ greatly.<\/p>\n

Summary<\/h3>\n

While this list could certainly go on, the points listed above are some of the common myths surrounding self-service BI. What do you think? Would you add anything to the list? If so, please feel free to share in the comments.<\/p>\n","protected":false},"excerpt":{"rendered":"

Summary: Despite it’s growing popularity, many myths still surround self-service BI. These myths can lead to implementations that aren’t as successful as they could be, or flat-out fail. Learn about the common myths\/misconceptions that businesses have about self-service BI, and why they’re false.<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"default","ast-global-header-display":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","slim_seo":{"title":"6 common misconceptions of self-service BI - mrc's Cup of Joe Blog","description":"Summary: Despite it's growing popularity, many myths still surround self-service BI. These myths can lead to implementations that aren't as successful as they c"},"footnotes":""},"categories":[8],"tags":[10,102],"class_list":["post-9445","post","type-post","status-publish","format-standard","hentry","category-education","tag-business-intelligence","tag-self-service"],"_links":{"self":[{"href":"https:\/\/www.mrc-productivity.com\/blog\/wp-json\/wp\/v2\/posts\/9445","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.mrc-productivity.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.mrc-productivity.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.mrc-productivity.com\/blog\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.mrc-productivity.com\/blog\/wp-json\/wp\/v2\/comments?post=9445"}],"version-history":[{"count":9,"href":"https:\/\/www.mrc-productivity.com\/blog\/wp-json\/wp\/v2\/posts\/9445\/revisions"}],"predecessor-version":[{"id":9462,"href":"https:\/\/www.mrc-productivity.com\/blog\/wp-json\/wp\/v2\/posts\/9445\/revisions\/9462"}],"wp:attachment":[{"href":"https:\/\/www.mrc-productivity.com\/blog\/wp-json\/wp\/v2\/media?parent=9445"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.mrc-productivity.com\/blog\/wp-json\/wp\/v2\/categories?post=9445"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.mrc-productivity.com\/blog\/wp-json\/wp\/v2\/tags?post=9445"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}