I recently hosted an Executive Roundtable in Singapore along with my colleagues Dane Anderson and Tim Sheedy. The theme of the session was “From Systems of Record to Systems of Engagement - Understanding the New Mobile Imperative for IT Leaders".

The discussion centered on the fact that mobility doesn’t simply mean another device for IT to support. Instead, mobility is driving a clear and permanent link between virtual services and physical activities. In other words, mobility is part of a broader set of technologies – including social, cloud, and advanced analytics – that are creating ubiquitous and information-rich Systems of Engagement.

The above broad themes made for great discussion. And there was general agreement among the CIOs present that mobility would drive significant business transformation. But there was also a common set of concerns that emerged among the group:

·         Deploying new technology (including mobile apps) with limited budget or relevant skills. And more broadly, how to prioritize mobile strategies relative to other IT (and business) initiatives. Ultimately the challenge for CIOs is how to align business requirements with budget realities, particularly as user expectations continue to rise and change management becomes a critical issue due to condensed release cycles. A critical first step is to better define your mobile strategy using a simple framework for prioritizing mobile applications and features.

Some markets and industry sectors in Asia Pacific (AP) were clearly early adopters of big data initiatives, but interest has now spread to almost all subregions and verticals. The reason is simple: More and more organizations now understand the value of data for not only addressing customer demands and expectations but also for responding to changing market dynamics and improving operational efficiency.

The common link across all big data initiatives is an interest in using more types of data, from more sources, to enable timelier, better-informed insights. With that in mind, we’re seeing two common use cases driving big data awareness and investment across industries:

Demand-driven, customer relationship-oriented initiatives

These initiatives are a response to increasing customer expectations for more personalized service. Typically centered on improved customer insight and engagement, organizations are seeking ways to better access and leverage customer data to improve understanding, more effectively personalize relationships, predict behavior, and ultimately deliver improved value via increased customer intimacy. Specifically, the sheer volume of readily available and increasingly accessible data that organizations can leverage — such as location data from mobile devices, apps and personal data on customer preferences and relationships from social networking sites — is driving big data initiatives. Early adopters typically include telcos, retailers, banks, insurance firms, and citizen-oriented eGovernment initiatives.

Supply-driven, efficiency-oriented initiatives

Amazon Web Services (AWS) held its first global customer and partner conference, re:Invent, in late November in Las Vegas, attracting approximately 6,000 attendees. While aimed squarely at developers, AWS highlighted two key themes that will appeal directly to enterprise IT decision-makers:

• Continued global expansion. AWS cites customers in 190 countries, but the company is clearly pushing for greater penetration into enterprise accounts via aggressive global expansion. AWS now has nine regions (each of which has at least one data center), including three in Asia Pacific: Tokyo, Singapore, and Sydney. 
• An expanded services footprint within customer accounts. The major announcement at re:Invent was a limited preview of a new data warehouse (DW) service called Amazon Redshift — a fully managed, cloud-based, petabyte-scale DW. As my colleague Stefan Ried tweeted during the event, with a limit of 1.6 petabytes, this is not just for testing and development — this is a serious production warehouse.

I’ve participated in cloud events in four different countries over the past two weeks. Attendees were primarily senior and mid-level IT decision-makers seeking guidance and best practices for implementing private clouds within their organizations. Regardless of the country of origin, industry focus or level of cloud-related experience, one common theme stood out above all others during both formal and informal discussions – the importance of effective communication.

The key takeaway – don’t get dogmatic about terminology. In fact, when it comes to cloud-related initiatives, choose your words carefully and be prepared for the reaction you’re likely to get.

‘Cloud computing’ as a term remains over-hyped, over-used, and still often poorly understood – because of this, typical reactions to the term are likely to range from cynicism and doubt to defensiveness and derision and all the way to outright hostility. Ironically, the fact that it’s not a technical term actually creates more confusion in many instances since its meaning is so general as to apply to practically anything (or nothing, depending on your point of view or perhaps your level of cynicism).

At all four events over the past two weeks – and in fact in nearly all discussions of IT priorities I’ve had over the past six months – CIOs and other senior IT decision-makers have consistently made clear that ‘cloud computing’ as a general objective or direction isn’t a top priority per se. However, they are unanimous in their belief that data center transformation is essential to supporting business requirements and expectations.

Demand for mobility is rising dramatically, but IT support is not keeping up. Over the next 12-18 months, we expect a majority of Asia Pacific (AP) organizations to begin to feel the pain of poor mobility strategies. Now is the time to define and manage mobility as part of a broader end-user computing strategy – this must include desktop virtualization initiatives, including (but not limited to) virtual desktop infrastructure (VDI). But while server virtualization is now accepted as a fundamental design principle and part of any data center implementation or refresh, that doesn’t mean desktop virtualization will follow suit. Long touted as a means to simplify desktop provisioning and management – and hence improve the efficiency and effectiveness of an organizations’ end-user computing strategy – over the past decade desktop virtualization has been driven primarily by CIO’s desire to lower hardware costs – by delaying or skipping PC refresh cycles – simplify application provisioning, and increase compliance and control of desktop infrastructure in areas like data security and patch management. Desktop virtualization doesn’t adequately address all end-user computing requirements since it’s essentially focused on eliminating the client device from the equation. This is particularly true for VDI. Thin (e.g. ‘dumb’) clients won’t work in a world where a growing percentage of users – not just information workers – are mobile and expect access to key resources but also expect those resources to be optimized for the particular device they’re using. With the explosion in device usage and changes in end-user expectations, IT is being forced to expand its focus around end-user computing from ‘control’ to ‘engagement’. Desktop virtualization will remain a key component of many organizatons’ end-user computing strategies, but its role will remain