Guy Cranswick

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Guy Cranswick is an IBRS advisor who covers Google (Apps and Search), broadband/NBN, Web 2.0 technology, government and channel strategy, including areas of business productivity. Guy has worked in the UK and France as Strategy Manager for Initiative Media and director of European operations for Modem Media (Poppe Tyson), the first online marketing and development company. In Australia, Guy was Senior Analyst at both Jupiter Communications and GartnerG2 covering online technologies and strategy in Asia-Pacific. He has published analytical articles in business and technology media, including the AFR, and was the winner of the Australian Institute of Management 2003 essay prize on the topic of corporate communications.

Conclusion: The range of channel and customer engagement tools needs thorough and continuous evaluation. There are two challenges to this objective. Firstly, the initial impediment is to gather data from various sources. The second problem is to apply a coherent and durable methodology to all of it.

The greater complexity of technologies and increased channel support means organisations must have a path to understand how their technologies perform. The most common assessment of return on investment can be applied to all data sets but it lacks sophistication. Developing a use-case will help establish a secure methodology which will make clearer the real value of customer satisfaction.


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Conclusion: Technology decision-makers have a larger and ever-growing set of technologies to choose from. The creative entrepreneurship driving the expansion of products is generally beneficial to end-users because it stimulates change and helps to drive innovation from the major vendors.

For larger organisations, in most cases, the major enterprise offer will be selected for many reasons, incumbency being significant, along with compatibility. For other organisations, examining the new and emerging vendors’ technologies may unlock a better process. However, assessing all the vendors within a category vertical, each with their own range of solutions, features and technical aspects, can result in a lot of information to process. The most effective method is to apply the principal business objective and assess how it aligns with strategic execution.


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Conclusion: In the last few years the structure and shape of ICT investment have undergone a series of shifts. The results are varied and complex and they reflect wider changes in the investment and use of ICT products.

It is important for organisations to take note of these transitions and to adapt and utilise methods which can improve the efficiency of their ICT portfolios.


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Conclusion: Although automation is actively being introduced through digital transformation projects, it may still be a minor part of the technological mix for a few years. The main reason for the potentially slower progress with automation is the relatively mixed economic background. In some specific instances, it is an obvious option but otherwise its benefits will be ambiguous for some time.

In these foreseeable circumstances it may be that business as usual (BAU) is the overriding strategic principle.


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Conclusion: Automation will overturn the old model of technology in some industries and workplaces. How automation could modify work practice is being explored but it is the ramifications which are obscure. If automation becomes widespread, as credible forecasts claim, it will have multiple consequences which require understanding and response.


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Is a return to the high period of IT investment likely? The same conditions of the long IT investment boom are not present today. This infographic reveals the trends over the next 3 years.


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Organisations can select a model for a particular need however, it is fundamental that the assumptions and the factors that construct the model are realistic and clearly understood. Furthermore, the models should be comprehended by other departments within an organisation, such as finance. A model that is only applied within, and solely has merit for IT, is generally not an altogether useful tool. The outputs and the inferences drawn from them may not convince other parties if the tool is not compatible with cross-department interpretation.


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Conclusion: Technologies which improve the efficiency of the marketing value chain will grow in importance because they can enhance productivity. The technologies are more developed and easier to access. In the mixed conditions of the current business environment squeezing more value is a basic imperative.

The constant themes of marketing, resource allocations and targeting also apply, and with better data tools and analytics it should be easier to gain insights which can be used commercially.


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Conclusion: Automation is understood to facilitate repetitive but essentially simple tasks. In conjunction with general purpose machine intelligence, virtual personal assistants and technologies leveraging artificial intelligence, automation will expand into more operational roles.

As the technologies improve, the potential applications will expand and play a larger marketing role.


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Conclusion: Data overload and the ease of accessing various types of data has created a problem of what to use and where. This is manifested in the choices of analysis which tend to the facile, such as Return on Investment, which can be applied universally even when it is not strictly applicable. Furthermore, the relative priority of some types of measurement, and in which cases, is vague. It is not always feasible to strive for the absolute solution, such as the comprehensive view, and therefore a graded and qualified response is more pragmatic.


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