Get ready for BI change

Boris Evelson

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

Boris Evelson

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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The Google Glass "Shopping" Experience

Mike Gualtieri

What’s it like to get Google Glass? It’s fun. It’s unique. Watch this special episode of Forrester TechnoPolitics to get an inside look at the Google Glass “shopping” experience in New York City. This may be a preview of how Google plans to create a high-end shopping experience to outdo Apple stores. You may also be interested in Google I/O 2013 Conference: A Great Time To Be A Developer.

 

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Why Is Customer Service So Hard to Get Right?

Kate Leggett

This post originally appeared on DestinationCRM.com

Good customer service is the result of the right attention to strategy, business processes, technology, and people management. This seven-part series focuses on customer service technology—and explains the what, why, how, and when of the technology.

We’ve already reviewed the core technologies for customer service in Part 1 of this series. Let’s now focus on why these technologies impact the quality of service delivered.

One reason that good service is hard to deliver is because the contact center technology ecosystem is really complex, and it has grown more so over time as new communication channels and touch points have become available.

There’s a constant churn of vendor mergers and acquisitions as customer service sectors consolidate (for example, the acquisition of knowledge management vendors, or social listening vendors by CRM vendors) that create support risks beyond the control of customer service planners.

There are new service delivery models, such as more extensive managed services and cloud-based offerings, which present new opportunities for customer service organizations, but it’s not clear that they truly help the enterprise transform its overall customer experience.

There’s the organization problem, where companies struggle to align customer-facing organizations that own the various customer service touch points that historically have not shared the same objectives, reporting structure, funding, business processes, data management strategies, technology, or culture.

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IaaS Supply Is Beginning To Create Increased Demand - It's Time To Enable and Manage IaaS Access To Inspire Innovation

Michael Barnes

I recently wrote about the need for IT organizations to embrace SaaS to maintain relevance and help drive business value. This quarter, I’ve set my sights on IaaS. In my forthcoming report, “IaaS Adoption Trends In Asia Pacific”, I explain in detail why my advice remains the same.

Internal IT resistance to expanding IaaS usage based on security, data management, and availability/performance concerns are certainly valid. But project-driven, opportunistic IaaS usage will continue to grow across the region as business decision-makers rationally seek out public cloud-based services that meet needs not met by internal IT.

IT decision-makers failing to consider all service-provisioning options will see their credibility wane and their control usurped by the inevitable emergence of shadow IT, driven by clear business demand. On the positive side, as usage expands internally, I’ve already seen Asia Pacific organizations begin viewing IaaS as a mechanism to fuel innovation based on easy access to cloud-based compute resources. Put another way, IaaS supply is beginning to fuel increased demand.

Some key recommendations for encouraging IaaS-related innovation while minimizing risks:

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Part 1: Testing Tools Market Landscape: Agile Keeps It Alive, Vital, and Dynamic

Diego Lo Giudice

I just finished my new report on the Agile testing tools landscape. I’ll point Forrester readers to it as soon as it publishes. But there are few things that have struck me since I took over the software quality and testing research coverage at Forrester and which I would like to share with you in this preview of my findings of the testing tools landscape doc.

My research focus area was initially on software development life cycles (SDLCs) with a main focus on Agile and Lean. In fact, my main contribution in the past 12 months has been to the Forrester Agile and Lean playbook, where all my testing research has also focused. Among other reasons, I took the testing research area because testing was becoming more and more a discipline for software developers. So it all made sense for me to extend my software development research focus with testing. But I was not sure how deep testing was really going to integrate with development. My concern was that I’d have to spend too much time on the traditional testing standards, processes, and practices and little on new and more advanced development and testing practices. After 12 months, I am happy to say that it was the right bet! My published recent research shows the shift testing is making, and so does the testing tool landscape document, and here is why:

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Ask These Four Questions When Buying Site Search

Anjali Yakkundi

“Search is often your last chance to keep a customer on your website before they go elsewhere to find the same product or content.” I love this quote (courtesy of the president of a digital agency). It shows us exactly why we should think of site search beyond its status as an IT-funded afterthought. Your customers need search in order to find a named item or piece of content. Or they rely on search because they can’t find what they need through the site’s menu structure. When looking to source site search solutions, organizations are faced with many options from mostly niche players and a few large vendors. How do you make sense of this? I recommend you begin narrowing the site search field by asking yourself these four key questions:

  1. Do your existing tools have sufficient bundled search capabilities? Many web content management and eCommerce vendors have embedded open source search capabilities into their core product (e.g., IBM, Intershop, hybris, Ektron, Sitecore) and some have innovated search experiences based on the open source framework. This makes it potentially unnecessary to buy a standalone search solutions. But be careful. For some solutions, embedded search only indexes and processes customer queries. It doesn’t allow for more advanced search features like merchandiser consoles or business user support for different ranking models. 
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What Is Customer Service Technology?

Kate Leggett

This post originally appeared on DestinationCRM.com

Good customer service is the result of the right attention to strategy, business processes, technology, and people management. This seven-part series focuses on customer service technology and explains the what, why, how, and when of the technology. Let’s start at the beginning: What is customer service technology?

The contact center technology ecosystem for customer service is a nightmare of complexity. At a high level, to serve your customers, you need to:

  1. Capture the inquiry, which can come in over the phone, electronically via email, chat, or SMS, and over social channels, like Twitter, Facebook, or an interaction escalated from a discussion forum or a Web or speech self-service session.
  2. Route the inquiry to the right customer service agent pool.
  3. Create a case for the inquiry that contains its details and associate it with the customer record.
  4. Find the answer to the inquiry. This can involve digging through different information sources like knowledge bases, billing systems, and ordering databases.
  5. Communicate the answer to the inquiry to the customer.
  6. Append case notes to the case summarizing its resolution and close the case.
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How The Obama Campaign Used Predictive Analytics To Influence Voters

Mike Gualtieri

The Obama 2012 campaign famously used big data predictive analytics to influence individual voters. They hired more than 50 analytics experts, including data scientists, to predict which voters will be positively persuaded by political campaign contact such as a call, door knock, flyer, or TV ad. Uplift modeling (aka persuasion modeling) is one of the hottest forms of predictive analytics, for obvious reasons — most organizations wish to persuade people to to do something such as buy! In this special episode of Forrester TechnoPolitics, Mike interviews Eric Siegel, Ph.D., author of Predictive Analytics, to find out: 1) What exactly is uplift modeling? and 2) How did the Obama 2012 campaign use it to persuade voters? (< 4 minutes)

 

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What Did We Hear At This Year’s Customer Experience Forum? An AD&D Perspective

Anjali Yakkundi

This year’s Customer Experience Forum just wrapped up, and two days and 20 client meetings later I’m back at Forrester’s headquarters. I’ve had a moment to think about the questions clients asked me, and as an application development and delivery (AD&D) analyst, it was great to see that attendees were interested in bridging the customer experience strategy with their technology strategy and decision-making process.

When thinking about those issues, the top three questions I was asked during the forum included:

  • What vendor can help us support personal experiences? I got this question a lot, and each time I found myself repeating that moving to deeply contextual experiences isn’t solved by just one technology or one vendor. Many technologies (including those you may already have in place) support a contextual strategy, and they each work together to deliver a deeply contextual experience. These include (among others) tools like AB/multivariate testing; web content management; eCommerce platforms; recommendations engines; customer analytics; and site search. And when it comes to mobile apps, it’s not always a sourcing story as you’ll likely need to build applications that take contextual inputs into account (e.g. location).
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