“Neuroeconomist Paul Zak has discovered, for the first time, that social networking triggers the release of the generosity-trust chemical in our brains.
The essence of affection. The cuddle chemical. In other words, oxytocin. If these changes apply in the world of social media, the implications for business — for every brand, company, and marketer trying to understand the now intimately networked world — could be significant.”
So, how much oxytocin are you putting into your user guides?
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Many organisations find it hard to know how much time, money and effort to put into supporting their users. There’s a competition, of sorts, between the Technical Support and Technical Publications departments over how much budget they should receive. In some organisations, these departments are also competing, in a way, with content generated by users and others outside the business.
One way of looking to answer this question may be to use Web Analytics from Web based user documentation and call statistics from the Support department to see of there is a self-regulating system in play between all the different forms of user assistance.
Let’s explain what we mean by a self-regulating system, by looking at the ideas of famed scientist James Lovelock. Lovelock argues the Earth is full of many positive and negative feedback systems that lead to a long term balance or equilibrium being achieved. To prove his theory, he created a computer model called daisyworld, to show how these self-regulating systems work:
With the move to Web-based documentation, and the ability to measure its use through Web Analytics, it’s now possible to determine whether there’s a correlation between the amount of documentation and the number of support calls. Where there is a large user base, you may find the number of support calls goes up or down depending on the amount of documentation that is available. You can then decide the most cost effective way for the organisation to allocate its budgets.
It may also be the case that the amount of user generated content developed by users correlates to how much or how little official documentation is available.
Indeed, with enough data, we may be able to identify what level of user assistance, in all its forms, is needed to sustain a typical software application.
Dr Atul Gawande is currently in London, touring the radio stations to promote his book “The Checklist Manifesto“. Dr Gawande is a surgeon in Boston Mass., who has been looking at how to deal with complexity in surgery and elsewhere.
He has discovered that complex systems work, mostly through people using checklists. Furthermore, no matter how expert you were, well-designed checklists could improve outcomes. So, with some assistance from Boeing, he developed a 90 second checklist (download it here) that reduced surgical deaths and complications in eight hospitals around the world by more than 30%.
In the book, he shows how low-cost checklists actually work, why some make matters worse and why others make matters better.
According to The Guardian, Dr Gawande argues that the right kind of checklist liberates rather than stifles professional intuition. A concise sumary of what might go wrong, and what to do if it does, galvanises groups of professionals into tighter teams. Indeed, one of the key factors, included in the checklist, was to introduce everyone in surgical team to each other: it leads to people having the confidence to speak up.
Checklists have long been regarded as beneath the level of serious consideration by methodologists and others interested in the logic of the disciplines. But they are more sophisticated than they appear–and are perhaps the key methodology of those disciplines that really treat theory and practice as equals, e.g., surgery, engineering, neural and public economics, program and product evaluation.
Intellect’s SaaS group has published recently a paper called “The business case for Software as a Service“. The paper lays out the technical and cost benefits of SaaS, together with checklists covering selection criteria, legal considerations and comparisons of SaaS applications to traditional in-house systems.
Cherryleaf made some minor contributions to this paper – so minor we didn’t think they merited our listing as contributors to this paper (a mistake in hindsight).
The report states, SaaS applications are generally easy to use and don’t require a great deal of training and online Help. So why is this?
In part, it’s because:
1. SaaS applications are newlydeveloped applications. This means the developers have been able to build upon the recent developments in usability, when they’ve developed the application.
2. SaaS products typically deal with familiar business tasks, such as finance and sales prospecting. Where a SaaS application does try to explain new concepts or tasks (viz. Google Wave), users can still find they struggle to use the application.
3. SaaS applications can be fixed quickly and are usually subject to continuous improvement. Pilot programmes can be much smaller and quicker to conduct. SaaS applications can be measured and tested more easily, using Web Analytics.
Researchers at Penn State University are claiming people don’t just use Search Engines to find facts – mostly, they’re using them to learn.
Could this influence the way in which e-learning courseware is developed in the future?
The researchers sought to discover the cognitive processes underlying searching. They examined the search habits of 72 participants while conducting a total of 426 searching tasks.
They found that search engines are primarily used for fact checking users’ own internal knowledge, meaning that they are part of the learning process rather than simply a source for information. They also found that people’s learning styles can affect how they use search engines.
From the screen shots on the Techcrunch site, it appears, yes, there will be online Help. It will be initiated by clicking on a ? button in the top right hand corner. In short, it appears Google will be sticking to standard User Interface conventions. What’s unclear is whether the Help pages will be stored locally on the machine or “in the cloud”.