{"id":9565,"date":"2015-09-29T10:50:19","date_gmt":"2015-09-29T15:50:19","guid":{"rendered":"http:\/\/www.mrc-productivity.com\/blog\/?p=9565"},"modified":"2023-03-13T16:15:34","modified_gmt":"2023-03-13T21:15:34","slug":"5-problems-that-create-unintelligent-business-intelligence","status":"publish","type":"post","link":"https:\/\/www.mrc-productivity.com\/blog\/2015\/09\/5-problems-that-create-unintelligent-business-intelligence\/","title":{"rendered":"5 problems that create \u201cUnintelligent\u201d Business Intelligence"},"content":{"rendered":"

\"Education\"Summary: Many businesses adopt Business Intelligence solutions with high expectations–only to be disappointed with the results. While many blame the problem on faulty software, the reality is, a successful BI project relies on a number of important factors. In this article, we explore 5 such factors that commonly hold back BI implementations.<\/em>
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photo credit: geralt<\/a> via pixabay<\/a> cc<\/a><\/figcaption><\/figure>\n

We\u2019ve seen a Business Intelligence (BI) explosion in the last few years. More organizations are adopting BI solutions to get a clear view of their business data.<\/p>\n

How quickly is BI growing? From 2013 to 2018, analysts expect BI spending to increase<\/span> by $100 Billion. The BI industry as a whole is growing at a 16% rate every year.<\/p>\n

With all of this growth, you\u2019d expect massive analytical improvements in businesses across the globe. As they invest in BI, their agility and decision making should improve…right?<\/p>\n

The problem: For many businesses, BI doesn\u2019t provide the expected results. It doesn\u2019t give them a clear view of their business. It doesn\u2019t offer the instant answers they expect.<\/p>\n

In short, their Business Intelligence isn\u2019t very \u201cIntelligent.\u201d<\/p>\n

Why? For some, it could be a matter of inflated expectations. They assumed their BI solution could deliver results beyond its capabilities.<\/p>\n

For others, the problem varies. The fact is, many critical elements go into a successful BI implementation. If you\u2019re stuck with BI that doesn\u2019t quite meet your needs, or isn\u2019t \u201cintelligent\u201d, here are some of the most common causes:<\/p>\n

1. It doesn\u2019t really fit your business<\/h3>\n

One common underlying problem found in \u201cunintelligent\u201d BI solutions: They\u2019re incomplete. Businesses try to work with a solution that doesn\u2019t really fit their business 100%.<\/p>\n

What causes this problem? Miscommunication is a common culprit. Details often get lost in translation (or overlooked) during the requirements gathering phase. When the IT department tries to implement a solution based on incomplete requirements, the solution will never fit the business.<\/p>\n

What\u2019s the answer? As explained below, the requirements gathering process shouldn\u2019t be a one-time process. It must be an open dialogue.<\/p>\n

\u201cThe biggest reason why BI fails is that companies don’t do proper requirements gathering,\u201d says Heather Cole who is President and CEO of Lodestar Solutions<\/span><\/a>. \u201cOften times, IT might interview the business, create a list of requirements, and they start building. BI needs to be a collaborative project between IT and the business. IT is still running projects via a waterfall method, which doesn’t work in the ever changing business environment of today. Both IT and the business should be educated on Agile\/Scrum methodologies and all BI projects must be run in some form of agile method, so there is constant communication between the business users and IT.\u201d<\/p><\/blockquote>\n

2. The data isn\u2019t clean<\/h3>\n
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photo credit: ATMDepot<\/a> via pixabay<\/a> cc<\/a><\/figcaption><\/figure>\n

It\u2019s a problem I see all too often. A business implements a best-of-breed BI solution and expect it to solve their data problems. But, they ignore their data quality.<\/p>\n

How important is data quality? Well, imagine that your BI solution is a shiny sports car. It\u2019s expensive, powerful, and comes with all the bells and whistles. Now, imagine that you filled the gas tank with dirty water instead of gasoline. Is that car going anywhere? Of course not.<\/p>\n

That\u2019s how important data is to your BI success. Messy, unorganized data creates all types of problems, from slow reporting to incomplete or inaccurate results.<\/p>\n

\u201cBI systems depend on good quality data with no way to capture that data automatically,\u201d says Andy Byrne, CEO of Clari<\/span><\/a>. \u201cFor example, looking at the sales world again, traditional BI systems pull data from the customer relationship management (CRM) system. But CRM data is notorious for being terrible because sales reps hate taking time from selling to update their CRM. On the other hand, sales reps live in customer meetings and in email. For BI to work in that environment, it needs to automatically capture all the email and calendar information. Systems that do that can show exactly what reps are doing and, more important \u2014 because meetings and email exchanges are with customers \u2014 how engaged and enthusiastic customers are.\u201d<\/p><\/blockquote>\n

3. You have blind spots in your data<\/h3>\n

In any BI project, you must account for two important data differences: The type of data you collect, and the amount of data being collected. Let me quickly explain why that\u2019s important.<\/p>\n

The type of data you collect varies depending on where it\u2019s stored. Sometimes data lives across different systems. Sometimes the data lives in a cloud host. These are often stored in different formats. This isn\u2019t typically a big issue, since your BI solution should provide data blending or ETL capabilities to connect this data from multiple sources.<\/p>\n

However, you must still account for the differences in the amount of data being collected across various departments. As explained below, these differences can create blind spots, which lead to faulty analysis.<\/p>\n

\u201cA key challenge to BI projects is understanding the blind spots of the collected data,\u201d says Heinrich Hartmann, Chief Data Scientist at Circonus<\/span><\/a>. \u201cThere will be parts of the company where high volumes of precise information are easy to collect, e.g. sales processes and accounting, whereas data from other parts of the company may be harder to quantify, e.g. human resources. As a consequence, all analysis of this data suffers from a selection bias, that is also commonly found in observational studies in health and social sciences.\u201d<\/p><\/blockquote>\n

4. It\u2019s not maintained\/no one owns it<\/h3>\n

Many people get involved during the planning, building, and implementation of a BI solution. The IT department, business users, and executives all have input in the process. Sometimes the business even brings in outside consultants to help out.<\/p>\n

But, what happens after the solution is rolled out? Is the project over? Not at all. The problem is, once the solution goes live, no one takes charge of its growth and adoption.<\/p>\n

Many businesses fall into this trap. They focus so much effort on implementation, but forget about what happens once it\u2019s built. Who owns the solution once it\u2019s live? Who is in charge of ensuring that it grows and adapts to the business? Who will drive education and adoption? As explained below, much of the real BI effort occurs after the solution is rolled out.<\/p>\n

\u201cMany organizations use a build it and leave it approach,\u201d says Pavan Singh, Senior Manager, Information Management & Analytics at Firmex<\/span><\/a>. \u201cThey use contractors\/consultants, and implement a solution in a long period of time. Once the platform is complete, they leave. The company does not spend any additional time on education, mentorship and focus on helping the power users\/users utilize the business intelligence tool. Also the company many not spend time on adding more data and reports onto the platform on a regular basis.\u201d<\/p><\/blockquote>\n

5. Users aren\u2019t using it<\/h3>\n

\u201cAlthough some BI environments are designed to be ‘self serve’ they can sometimes be overwhelming and complicated for end users to create\/modify reports,\u201d explains Singh. \u201cIf they do not have support and help from a competency center, or if it takes a long time and a lot of bureaucracy from IT in order to make changes, then there is a high likelihood that the end users won’t use the BI platform.<\/p><\/blockquote>\n

User adoption is one of the biggest challenges facing Business Intelligence today. How bad is it? A recent study<\/span> puts BI adoption rates among employees at 22%. It goes without saying, but a solution that isn\u2019t adopted will never give you the results you expect.<\/p>\n

Why are adoption rates so low? It usually boils down to one of three problems:<\/p>\n

1. The users don\u2019t like the solution:<\/strong> Sometimes, a BI tool gets selected without input from the users. When it\u2019s finally rolled out, the users find that it\u2019s confusing, or doesn\u2019t meet their needs. When this happens, they will likely revert back to the old way of doing things.<\/p>\n

2. The users were not properly trained:<\/strong> Other times, a BI tool is implemented without proper user training. If users don\u2019t understand the tool, and how it will help them, they won\u2019t use it.<\/p>\n

3. The users don\u2019t want to change:<\/strong> You\u2019ll run into this problem in every company. A handful of users will resist any new technology. They think that the old way works just fine. To combat this problem, training must be practical. You must not only explain how the tool helps them, you must demonstrate how the tool can solve a problem that they\u2019re facing. For instance, build a sample report they need. Demonstrate its usage in their environment.<\/p>\n

Summary<\/h3>\n

These are just a few reasons why your BI solution might not meet expectations, but there are plenty more. If you would like to add anything to this list, I\u2019d love to hear it. Feel free to share in the comments.<\/p>\n","protected":false},"excerpt":{"rendered":"

Summary: Many businesses adopt Business Intelligence solutions with high expectations–only to be disappointed with the results. While many blame the problem on faulty software, the reality is, a successful BI project relies on a number of important factors. In this article, we explore 5 such factors that commonly hold back BI implementations.<\/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":"5 problems that create \u201cUnintelligent\u201d Business Intelligence - mrc's Cup of Joe Blog","description":"Summary: Many businesses adopt Business Intelligence solutions with high expectations--only to be disappointed with the results. While many blame the problem on"},"footnotes":""},"categories":[8],"tags":[10],"class_list":["post-9565","post","type-post","status-publish","format-standard","hentry","category-education","tag-business-intelligence"],"_links":{"self":[{"href":"https:\/\/www.mrc-productivity.com\/blog\/wp-json\/wp\/v2\/posts\/9565","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=9565"}],"version-history":[{"count":8,"href":"https:\/\/www.mrc-productivity.com\/blog\/wp-json\/wp\/v2\/posts\/9565\/revisions"}],"predecessor-version":[{"id":14678,"href":"https:\/\/www.mrc-productivity.com\/blog\/wp-json\/wp\/v2\/posts\/9565\/revisions\/14678"}],"wp:attachment":[{"href":"https:\/\/www.mrc-productivity.com\/blog\/wp-json\/wp\/v2\/media?parent=9565"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.mrc-productivity.com\/blog\/wp-json\/wp\/v2\/categories?post=9565"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.mrc-productivity.com\/blog\/wp-json\/wp\/v2\/tags?post=9565"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}