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SmartData Collective > Big Data > Data Mining > Is Your Company Ready to Deploy Business Intelligence Intelligently?
AnalyticsBig DataBusiness IntelligenceData ManagementData MiningData QualityData VisualizationPredictive AnalyticsUnstructured Data

Is Your Company Ready to Deploy Business Intelligence Intelligently?

Ray Major
Ray Major
6 Min Read
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ImageIs Your Company Ready to Deploy Business Intelligence Intelligently?

You might be surprised by the answer. 

ImageIs Your Company Ready to Deploy Business Intelligence Intelligently?

You might be surprised by the answer. 

Although the majority of data-driven enterprises may have or use BI software or systems, a recent survey we took of IT executives revealed that there is a vast difference between having BI and using BI to the company’s full advantage. There is an even larger chasm between the cost to implement BI and the value realized from those efforts. This is not good news for anyone whose bread-and-butter comes from demonstrating measurable results and ROI. But understanding the reasons why most companies aren’t realizing the full value can help plot the course for the change and make the most of the marvelous tool that is business intelligence.

The survey encompassed more than 60 CIOs from small- to medium-sized enterprises in the United States, in a wide range of industries.  The CIOs were asked to assess their BI platform and usage.  The survey results were used to help them determine two things:

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1) how mature is their current BI deployment in four key areas including data integration, reporting/analytics, collaboration and information sharing/dissemination;

2) how they can derive more value through knowing where they are on the BI spectrum and what it would take to get to the next level.

The bottom line? Most companies are exploring and engaged on some level in the preliminary stages of BI deployment, but haven’t quite made the jump from simple data collection and warehousing to reaping the benefits of a truly holistic BI deployment.

Here’s how we came to that conclusion.

Based on survey responses, scores were calculated using a scale of 0-100, with 0 being the lowest level of maturity. Next, responses were grouped into levels based on these “BI maturity” scores. Finally, descriptions were developed using common characteristics of the businesses that fell within each level. Those level are:

Nascent: 0 – 20

Most companies in this stage are primarily focused on data collection and data organization having the beginnings of a BI system in place. They made the decision to invest in BI and have, or are in the process of implementing data collections systems and other data warehousing solution.

Low: 21 – 40

Companies in this stage generally have data systems in place, having the ability to derive some BI value from basic analytics, and produce historical reports for key individuals. Distribution is mostly limited to a few individuals or departments and their primary focus is on upgrading and enhancing data collection and deriving more value from data assets.

Mid-Level: 41 – 60

Those companies concentrate most efforts on data cleansing, formalizing KPI’s and metrics, increasing distribution and data usage throughout the organization. Companies in this stage are deriving value from BI reporting, analytics and also exploring new capabilities such as predictive analytics.

High: 61 – 80

Companies have formal processes around data and metrics using data to make and support key decisions. C-level executives are fully engaged in BI, focused on better and faster decision-making, cost reduction, empowerment through distribution and collaboration. Most companies in this stage use predictive analytics for forecasting sales and inventory levels. They see BI as a differentiator between them and their competition.

Advanced: 81 – 100

Companies in this stage have aligned people, processes and technology to facilitate optimal metric-driven decisions.  They empower their customers, distribution channels and suppliers with key performance data integrating human collaboration into solving problems exposed through BI, using modeling algorithms to improve products and services having a 360-degree view of their business.

The survey findings revealed a number of trends that inhibit successful use of BI in mid-sized companies.  Overall, the vast majority of mid-sized companies (77% to be exact) are in a nascent or low state of maturity with their current BI deployment.  Fewer than 1 in 5 have integrated data quality into their BI platform which calls into question the very foundation of the decisions being made based on the reports coming out of their BI systems.  About one-third of the companies surveyed are leveraging real-time reporting and predictive analytics which means that they are using BI to look in the rear view mirror (how did we perform last quarter? last year?) as opposed to using BI to monitor current operations or, better yet, to make course corrections based on forecasts of future performance. 

Possibly the most damning finding of all is that for the vast majority of the companies surveyed, BI remains in a silo supporting individual or, at best, departmental-level tracking and decision-making.  Thus, the opportunity to collaborate across the entire enterprise and beyond, with customers, partners and suppliers, is completely missed.

You may be asking yourself, “So why is this important?” 

Because companies with mature BI implementations, namely those who fully leverage the potential of BI to optimize decision-making throughout the extended enterprise, significantly outperform their competitors. 

Deploying BI intelligently starts with assessing your organization’s BI goals – a crucial step that most companies miss.  Linking BI to the goals and key initiatives of your company is what insures the relevance of the decisions made and actions taken based on your BI system.

That leads me to my next post which will cover tactics for linking BI to corporate goals.  Meanwhile, if you are interested in seeing where your company ranks in terms of BI maturity, feel free to check out the Halo BI Maturity Model.

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