BI and analytics software packaging and pricing are a Wild West with few common practices among the vendors. Comparing and contrasting vendor prices and negotiating with vendors is challenging because
So how do you know if you are getting a good deal? Here's a best practice and a few price ranges you can use to get you started. First of all, at the end of the day, it's the number of users and user types that are always a common denominator regardless of BI software platform or your particular implementation. Consider the following price ranges for specific user types
Management consultants and business intelligence, analytics and big data system integrations often use the terms accelerators, blueprints, solutions, frameworks, and products to show off their industry and business domain (sales, marketing, finance, HR, etc) expertise, experience and specialization. Unfortunately, they often use these terms synonymously, while in pragmatic reality meanings vary quite widely. Here's our pragmatic take on the tangible reality behind the terms (in the increasing order of comprehensiveness):
"A little prediction goes a long way" wrote Eric Siegel in his popular Predictive Analytics book. True, predictive analytics is now part and parcel of most Business Intelligence (BI), analytics and Big Data platforms and applications. Forrester Research anecdotal evidence finds that open source R is by far the most ubiquitous predictive analytics platform. Independent findings and surveys like the ones by KDNuggets and RexerAnalytics confirm our conclusions (and I quote) "The proportion of data miners using R is rapidly growing, and since 2010, R has been the most-used data mining tool. While R is frequently used along with other tools, an increasing number of data miners also select R as their primary tool."
To jump on this R feeding frenzy most leading BI vendors claim that they "integrate with R", but what does that claim really mean? Our take on this - not all BI/R integration is created equal. When evaluating BI platforms for R integration, Forrester recommends considering the following integration capabilities:
* BI = reporting, querying, OLAP
* BI = all of the above + data visualization / dashboards
* BI = all of the above plus analytics (advanced, predictive)
* BI = all of the above + Big Data
* BI transforms data into info to improve biz performance. It's an uber concept that encompasses all of the above + data mgmt
Business intelligence (BI) is an evergreen that simply refuses to give up and get commoditized. Even though very few vendors try to differentiate these days on commodity features like point and click, drag and drop, report grouping, ranking, and sorting filtering (for those that still do: Get with the program!), there are still plenty of innovative and differentiated features to master. We categorize these capabilities under the aegis of Forrester agile BI; they include:
Market conditions are changing quickly; firms need to make the best possible business decisions at the right time and base them on timely, accurate, and relevant information from business intelligence (BI) solutions. The repercussions of not handling BI change well are especially painful and may include lost revenue, lower staff morale and productivity, continued proliferation of shadow IT BI applications, and unwanted employee departures. Ineffective change management often lies in the process of preparing the people affected by change rather than in planning the technology implementation. Firms that fail to prepare employees for enterprise BI change early enough or well enough will be left behind. They need to implement a multifaceted series of activities ranging from management communication about why change is needed to in-depth, role-appropriate employee training.
Initial business intelligence (BI) ployment efforts are often difficult to predict and may dwarf the investment you made in BI platform software. The effort and costs associated with professional services, whether you use internal staff or hire contractors, depend not only on the complexity of business requirements like metrics, measures, reports, dashboards, and alerts, but also on the number of data sources you are integrating, the complexity of your data integration processes, and logical and physical data modeling. At the very least Forrester recommends considering the following components and their complexity to estimate development, system integration and deployment effort:
CEOs and other senior executives must identify ways to improve their enterprise performance by boosting profitability, raising market share, and leapfrogging competitors. But achieving these objectives is not as simple as just looking at the numbers. What about nonfinancial measures (e.g., customer loyalty and employee satisfaction) that don't show up in financial accounting? How do you quickly and efficiently get the full 360-degree view of your business?
In order to execute their business strategy, business and IT execs need a business-focused, strategic, and pragmatic way to measure their finances and operations -- popularly referred to as business intelligence (BI). Without such measurements -- supported by enterprisewide BI deployments -- businesses can't link operational results to strategy. Organizations will also find it difficult to get a coherent view of their internal and external processes, customers, logistics, operations, and finances.
However, most firms struggle with BI strategies and programs because turning data into information is an open-ended concept. They frequently go in the wrong direction because of traditional (and often outdated) views and approaches and a focus on technology instead of business, which results in BI programs that are tactical and only project-based. What these firms need is an approach to BI that, while staying true to the importance of long-term vision and looking across silos, provides the flexibility to accommodate varying levels of resource commitment and the political, historical, and cultural obstacles that BI programs often face. Think of Forrester's new business intelligence playbook as your BI bible; it should guide your BI decisions every step of the way.
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