A common denominator for pricing and negotiating Business Intelligence (BI) and Analytics software

Boris Evelson

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

  • Few vendors publish list prices, so when a vendor tells you you are getting a certain discount you can’t really verify whether the discount numbers are valid or not.
  • Vendors base their prices on multiple variables such as
    • Total number of users
    • Concurrent users
    • User types
    • Connectivity to certain types of data sources
    • Number of CPU cores or sockets
    • CPU clock speed
    • Amount of RAM
    • Server Operating System (OS)
    • Environments such as development, test, QA (quality assurance), UAT (user acceptance testing), production, and DR (disaster recovery)
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Digital Experience Delivery Creates Many Organizational Headaches

Anjali Yakkundi

Forrester recently surveyed 148 technology, marketing, and business professionals with decision-making roles in digital experience (DX) delivery technologies, and asked them about their strategies for the coming 12 months. In our recently published report, one of the more interesting trends we found was the “people” issues remain top of mind for most organizations. Our qualitative and inquiry data backs this up, as we often here that people, process, and cultural issues (not technology issues) have stifled progress towards delivering great digital customer experiences.

Our survey found that organizations were concerned about people issues such as:

  • Dividing up work between different groups. Digital experience has moved from a purely marketing centric function, to a decidedly cross business issue that touches everyone in the organization. This includes technology management, business, marketing, and sales groups. But this cross-business shift toward digital experience delivery presents significant challenges around coordinating work between various groups. Accordingly, this was the number one people-related pain point: 60% of respondents said dividing roles and responsibilities between marketing, technology management, and the business was their top challenge.
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What Do Business Intelligence Consultants Mean By “Solutions”?

Boris Evelson

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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here is a link to the research on managing an application portfolio for value

George Lawrie

http://www.forrester.com/Optimize+LongTerm+Application+Effectiveness+And...

 

 

The self assessment based on your assessment of "what good looks like" wil lbe added shortly.

 

 

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Do you have a large customer service team or a small one? Start here to choose the right vendor solution

Kate Leggett

How do you start to narrow your choices when you are looking for the right customer service solution for your group. Start by asking whether your team is large or small, and whether your needs are primarily phone based, or whether you support your customers over a variety of voice, digital and social communication channels.

 

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The Forrester Wave: Customer Service Solutions For Enterprise Organizations, Q2 2014

Kate Leggett

During the past five years, the customer service capabilities leading vendors has matured as vendors have focused on solidifying the foundational building blocks of customer support capabilities. Vendors have folded new technologies such as social capabilities, business process management, decisioning, business intelligence, and mobility into their solutions to allow organizations to offer more-personalized customer service experiences. Vendors have also focused on different buyers – those that have to support enterprise-size teams who respond to inquiries primarily over the phone channel, and those that have to support small to mid size teams  who support multichannel operations.

This maturation makes it, in a way, increasingly challenging to be confident of your technology choice. In The Forrester Wave: Customer Service Solutions For Enterprise Organizations, Q2 2014, we pinpoint the strengths of 11 leading vendors that offer solutions suitable for large and very large customer service agent teams. Here are some of our key findings:

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Large Chinese Enterprise Targets Improved Agility

Gene Cao

State-owned enterprises (SOEs) in China face a quickly changing competitive landscape — one that their existing technology strategies can’t keep up with. To address this challenge, organizations are migrating from earlier-generation BI architectures, technologies, and organizational structures to new models and approaches. My “Chinese State-Owned Enterprise Targets Improved Agility” report, scheduled to appear later this month, describes the experience of a typical large Chinese SOE, the China National Cereals, Oils, and Foodstuffs Corporation (COFCO), which leveraged a BI-led program to jump-start the transformation of its technology management capabilities.

COFCO is China’s largest supplier of agricultural and food products and services, including oils, rice, wine, tea, and various other products, and is expanding into real estate, shopping centers, and other industries. COFCO is a large B2B trader with many technology stakeholders, and its headquarters couldn’t quickly collect or analyze data from branches or business units, delaying the company’s response to and decisions about market changes. Major obstacles included siloed operations centers and business units; inconsistent data management rules that complicated centralized data governance; and other process and people challenges.

To address these issues, COFCO decided to redefine the position of technology management in the organization and review its technology agenda and planning. It evaluated and selected BI as the most compelling project to deliver quick business outcomes that would convince business executives to further invest in the transformation. Best practices that COFCO implemented include:

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Asian Banks Are Adopting Cloud Computing, But Best Practices Are Scarce

Michael Barnes

Ahead of the publication of my full report in mid-April, I wanted to follow on from my recent blog post and expand on the topic of cloud adoption in the Asia Pacific (AP) banking sector. Despite some views to the contrary, all AP banks will ultimately leverage cloud-based services and capabilities; most already do. The real challenge is mapping workloads, processes, and data to the various flavors of cloud approaches — in other words, it’s still a portfolio management exercise.

Legacy application architectures and inflexible software licensing practices will certainly influence, and potentially hinder, cloud adoption. But while banking regulations will continue to heavily influence cloud strategies, they don’t forbid them. Senior technology and business decision-makers in the AP banking sector should therefore consider the following:

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What does Business Intelligence integration with R really mean

Boris Evelson

“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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How is an earthquake triggered in Silicon Valley turning your company into a software vendor?

James Staten

A movement that began in Silicon Valley, is starting to have profound impacts on corporations throughout the world that are far from obvious but critical to your success and maybe even your company’s survival. This is a massive shift that all CIOs need to start preparing for - a seismic shift that is documented in my latest report released to clients this week. 

As we enter the age of the customer we are leveraging cloud, mobile and big data technologies to build better and more complete experiences with our customers. In doing so we are creating new digital experiences, radically different interactions, and redefining what our companies do and how they should be viewed. Nike’s FuelBand is both a device and a collaboration solution (that’s why Under Armour bought MapMyFitness). Siemens Medical’s MRI machines are both a camera (of sorts) and a content management system  Heck, even a Citibank credit card is both a payment tool and an online financial application. Any company that is embracing the age of the customer is quickly learning that you can’t do that without software. 

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