What do business intelligence consultants mean by “solutions”?

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):

  • Fameworks. Often little more than a collection of best practices and lessons learned from multiple client engagements. These can sometimes shave off 5%-10% of a project time/effort mainly by enabling buyers to learn from the mistakes others already made and not repeating them.
  • Solution Accelerators. Aka Blueprints, these are usually a collection of deliverables, content and other artifacts from prior client engagements. Such artifacts could be in the form of data connectors, transformation logic, data models, metrics, reports and dashboards, but they are often little more than existing deliverables that can be cut/pasted or otherwise leveraged in a new client engagement. Similar to Frameworks, Solution Accelerators often come with a set of best practices. Solution Accelerators can help you hit the ground running and rather than starting from scratch, find yourself 10%-20% into a project.
  • Solutions. A step above Solution Accelerators, Solutions prepackage artifacts from prior client engagements, by cleansing and stripping them of proprietary content and/or irrelevant info. Count on shaving 20% to 30% off the effort.
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What does Business Intelligence integration with R really mean

“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:

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The Forrester Wave™: Enterprise Business Intelligence Platforms, Q4 2013

The majority of large organizations have either already shifted away from using BI as just another back-office process and toward competing on BI-enabled information or are in the process of doing so. Businesses can no longer compete just on the cost, margins, or quality of their products and services in an increasingly commoditized global economy. Two kinds of companies will ultimately be more successful, prosperous, and profitable: 1) those with richer, more accurate information about their customers and products than their competitors and 2) those that have the same quality of information as their competitors but get it sooner. Forrester's Forrsights Strategy Spotlight: Business Intelligence And Big Data, Q4 2012 (we are currently fielding a 2014 update, stay tuned for the results) survey showed that enterprises that invest more in BI have higher growth.

The software industry recognized this trend decades ago, resulting in a market swarming with startups that appeared and (very often) found success faster than large vendors could acquire them. The market is still jam-packed and includes multiple dynamics such as (see more details here):

  • All ERP and software stack vendors offer leading BI platforms
  •  . . . but there's also plenty of room for independent BI vendors
  •  Departmental desktop BI tools aimed at business users are scaling up
  •  Enterprise BI platform vendors are going after self-service use cases.
  •  Cloud offers options to organizations that would rather not deal with BI stack complexity.
  •  Hadoop is breathing new life into open source BI.
  •  The line between BI software and services is blurring
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How To Have The BI Cake And Eat It Too: A (Or The) BI Prediction For 2014

Rather than going with the usual, ubiquitous, and often (yawn) repetitive “top 10 BI predictions” for the next year, we thought we’d try something different. After all, didn’t the cult movie Highlander prove beyond the shadow of a doubt that “in the end there will be only one”? And didn’t the Lord Of The Rings saga convince us that we need one prediction “to rule them all”? The proposed top BI prediction for 2014 rests on the following indisputable facts:
  • Business and IT are not aligned. Business and IT stakeholders still have a huge BI disconnect (after all these years — what a shocker!). This is not surprising. Business users mostly care about their requirements, which are driven by their roles and responsibilities, daily tasks, internal processes, and dealings with customers (who have neither patience nor interest in enterprises’ internal rules, policies, and processes). These requirements often trump IT goals and objectives to manage risk and security and be frugal and budget minded by standardizing, consolidating, and rationalizing platforms. Alas, these goals and objective often take business and IT in different directions.
  • Requirements are often lost in translation. Business and IT speak different languages. Business speaks in terms of customer satisfaction, improved top and bottom lines, whereas IT speaks in metrics (on a good day), star schemas, facts, and dimensions. Another consideration is that it’s human nature to say what we think others want to hear (yes, we all want our yearly bonus) versus what we really mean. My father, a retired psychiatrist, always taught me to pay less attention to what people say and pay more attention to what people actually do — quite handy and wise fatherly advice that often helps navigate corporate politics.
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SAP Takes Another Step Towards Agile BI With KXEN Acquisition

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:

  • Making BI more automated: suggestive BI, automatic information discovery, contextual BI, integrated and full BI life cycle, BI on BI.
  • Making BI more pervasive: embedding BI within applications and processes, within the information workplace, and collaborative, self-service, mobile, and cloud-based BI.
  • Making BI more unified: unifying structured data and unstructured content, batch and streaming BI, historical and predictive, and handling complex nonrelational data structures.
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Get ready for BI change

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. 

 
Why change management is so critical? Most strategic business events, like mergers, are high-risk initiatives involving major changes over two or more years; others, such as restructuring, must be implemented in six months. In the case of BI, some changes might need to happen within a few weeks or even days. All changes will lead to either achieving or failing to achieve a business result. There are seven major categories of business and organizational change:
  • People acquisitions
  • Technology acquisitions 
  • Business process changes 
  • New technology implementations 
  • Organizational transformations
  • Leadership changes
  • Changes to business process outsourcing or IT sourcing 
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How to estimate cost of BI deployment

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:

  • Top down business requirements such number of 
    • Goals and objectives
    • Metrics, Measures
    • Attributes and dimensions
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Streamline Your BI Strategy With Forrester's BI Playbook

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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BI on BI Or How BI Pros Must Eat Their Own Dog Food

 

BI professionals spend a significant portion of their time trying to instill the discipline of datadriven performance management into their business partners. However, isn’t there something wrong with teaching someone else to fly when you’re still learning to walk? Few BI pros have a way to measure their BI performance quantitatively (46% do not measure BI performance efficiencies and 55% do not measure effectiveness). Everyone collects statistics on the database and BI application server performance, and many conduct periodic surveys to gauge business users’ level of satisfaction. But how do you really know if you have a high-performing, widely used, popular BI environment? For example, you should know BI performance

  • Efficiency metrics such as number of times a report is used or a number of duplicate/similar reports, etc
  • Effectiveness metrics such as average number of clicks to find a report and clicks within a report to find an answer to a question and many others
  • Metric attributes/dimensions such as users, roles, departments, LOBs, regions and others
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Ways To Address BI Skills Shortage

Whether you are just starting on your BI journey or are continuing to improve on past successes, a shortage of skilled and experienced BI resources is going to be one of your top challenges. You are definitely not alone in this quest. Here are some scary statistics:
  • “By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills, as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.” (Source: May 2012 McKinsey Global Institute report on Big Data)
  • “… trigger a talent shortage, with up to 190,000 skilled professionals needed to cope with demand in the US alone over the next five years.” (Source: 2012 Deloitte report on technology trends)
  • “Fewer than 25% of the survey respondents worldwide said they have the skills and resources to analyze unstructured data, such as text, voice, and sensor data.” (Source: 2012 research report by IBM and the Saïd Business School at the University of Oxford)
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