This morning we released the latest version of an annual client-favorite:  “How Companies Improved Their CXi Scores, 2013.”

As we do each year, we compiled a list of brands whose scores went up five or more points in our Customer Experience Index over the past year (in this case between 2012 and 2013). We asked CX leaders from those brands if they’d be willing to tell us what they did to drive those improvements. Finally, we synthesized their answers into a list of best practices that others can learn from.

As you’d expect we heard about a host of projects designed to boost the three aspects of customer experience quality. Here’s just a sampling of what we uncovered:

• Meets needs. Marriott used one of my favorite qualitative research techniques - diary studies - to understand exactly when its guests would need a mobile device during their travels. The firm  identified roughly 300 user needs that a mobile device could fill, prioritized them, and are using the resulting hierarchy as a road map for future investment.
• Easy. Vanguard and Progressive were just two of the brands that said they upgraded web site designs to make it easier for customers to get the information they need online.
• Enjoyable. Days Inns trained more than 20,000 employees in how to make hotel guests feel welcomed.

Forrester research has always identified security as a major impediment to broad scale implementation for cloud, regardless of the model, SaaS, PaaS, IaaS, the adoption rate has been slowed by security concerns. Cloud providers recognize this is an impediment to selling cloud services and in response are strengthening their security controls. In Forrester’s Forrsights® research program we interview over 2000 security decision makers on a variety of security issues and topics. Cloud security tops the list of concerns regarding cloud deployments.

The appetite on the buy-side is very real for secure IT cloud infrastructures. Our research shows a lot of very strong interest in the deployment of private cloud platforms because of the elasticity, reduced cost and cycle times required to deploy solutions in these environments.

This week Amazon Web Services (AWS) announced that AWS GovCloud (U.S.) and all U.S. AWS Regions have received an Agency Authority to Operate (ATO) from the U.S. Department of Health and Human Services (HHS) under the Federal Risk and Authorization Management Program (FedRAMP) requirements. 

Obtaining FedRAMP certification indicates AWS’ focus on providing strong security controls for its cloud offerings. Forrester assumes AWS commercial clients could benefit from this as well by AWS security processes propagating to other areas of AWS’ cloud business.

It’s (long past) time to put the era of One Size Fits All enterprise computing behind us. Providing workers with Standard Issue™ devices and software represents an antiquated paradigm. Instead, segmenting your workforce into different classes of workers – honoring the needs of each type of worker – can help you:

• Save money. Overinvesting in computing power by giving a worker “too much machine” and over-investing in software licenses for applications that won’t be used are common implications of One Size Fits All enterprise computing. You can save money by provisioning appropriate hardware and software to various classes of workers.
• Preempt BYO. While IT departments are coming around to the virtues and values of BYO, managing excessively diverse BYO comes with management costs. You can preempt some types of BYO by providing the right tool to the right worker at the right time… obviating the need for them to bring their own.
• Drive worker productivity and innovation. Innovations like tablets and Chromebooks can empower certain classes of workers to achieve new levels of productivity. Providing the right worker – for example, a traveling salesperson – with a tablet can enable new scenarios and create tangible returns.

As I sit at my kitchen table enjoying the quiet of my house before my kids come home, I know that I will move to my office and shut the door once that tranquility is shattered by their arrival. Then later this evening, once the house is again quiet with the monsters nestled in their beds, I might just take a few calls propped up on pillows in my bed. Yes, I do that regularly. Heck, they call it a laptop, right?  This is the "home" scenario.  On the road, workplaces and spaces vary even more. I really work best from a hotel room, or the hotel bar if I have a good headset on.  None of this is new for me; I have played the role of an itinerant worker for years. But for a long time my employers continued to put my name on a door or cubicle. For me, that has now changed. No more nameplate for me.  Employers are increasingly waking up to the fact that many employees (or "information workers," ugh... hate the term) just don't need or even want a fixed office or space. And, likely more importantly, the employers don't want that either. An empty office is an under-optimized asset. Both demand-side and supply-side forces converge to drive workplace and space diversity.

We hear a lot about empowered employees these days, and the changing nature of work and the workforce. Forrester's Workforce Employee Surveys investigate trends among information workers such as device usage,collaboration practices, workplace preferences and attitudes about their employers.  And, the signs are clearly indicating that the demand for workplace diversity and choice is on the rise:

IBM has just announced that one of Australia’s “big four” banks, the ANZ, will adopt the IBM Watson technology in their wealth management division for customer service and engagement. Australia has always been an early adopter of new technologies but I’d also like to think that we’re a little smarter and savvier than your average geek back in high school in 1982.

IBM’s Watson announcement is significant, not necessarily because of the sophistication of the Watson technology, but because of IBM's ability to successfully market the Watson concept.   

To take us all back a little, the term ‘cognitive computing’ emerged in response to the failings of what was once termed ‘artificial intelligence’. Though the underlying concepts have been around for 50 years or more, AI remains a niche and specialist market with limited applications and a significant trail of failed or aborted projects. That’s not to say that we haven’t seen some sophisticated algorithmic based systems evolve. There’s already a good portfolio of large scale, deep analytic systems developed in the areas of fraud, risk, forensics, medicine, physics and more.