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Author: Frank Gilbane (Page 41 of 74)

Big data and decision making: data vs intuition

There is certainly hype around ‘big data’, as there always has been and always will be about many important technologies or ideas – remember the hype around the Web? Just as annoying is the backlash anti big data hype, typically built around straw men – does anyone actually claim that big data is useful without analysis?

One unfair characterization both sides indulge in involves the role of intuition, which is viewed either as the last lifeline for data-challenged and threatened managers, or as the way real men and women make the smart difficult decisions in the face of too many conflicting statistics.

Robert Carraway, a professor who teaches Quantitative Analysis at UVA’s Darden School of Business, has good news for both sides. In a post on big data and decision making in Forbes, “Meeting the Big Data challenge: Don’t be objective” he argues “that the existence of Big Data and more rational, analytical tools and frameworks places more—not less—weight on the role of intuition.”

Carraway first mentions Corporate Executive Board’s findings that of over 5000 managers 19% were “Visceral decision makers” relying “almost exclusively on intuition.” The rest were more or less evenly split between “Unquestioning empiricists” who rely entirely on analysis and “Informed skeptics … who find some way to balance intuition and analysis.” The assumption of the test and of Carraway was that Informed skeptics had the right approach.

A different study, “Frames, Biases, and Rational Decision-Making in the Human Brain“, at the Institute of Neurology at University College London tested for correlations between the influence of ‘framing bias’ (what it sounds like – making different decisions for the same problem depending on how the problem was framed) and degree of rationality. The study measured which areas of the brain were active using an fMRI and found the activity of the the most rational (least influenced by framing) took place in the prefrontal cortex, where reasoning takes place; the least rational (most influenced by framing / intuition) had activity in the amygdala (home of emotions); and the activity of those in between (“somewhat susceptible to framing, but at times able to overcome it”) in the cingulate cortex, where conflicts are addressed.

It is this last correlation that is suggestive to Carraway, and what he maps to being an informed skeptic. In real life, we have to make decisions without all or enough data, and a predilection for relying on either data or intuition can easily lead us astray. Our decision making benefits by our brain seeing a conflict that calls for skeptical analysis between what the data says and what our intuition is telling us. In other words, intuition is a partner in the dance, and the implication is that it is always in the dance — always has a role.

Big data and all the associated analytical tools provide more ways to find bogus patterns that fit what we are looking for. This makes it easier to find false support for a preconception. So just looking at the facts – just being “objective” – just being “rational” – is less likely to be sufficient.

The way to improve the odds is to introduce conflict – call in the cingulate cortex cavalry. If you have a pre-concieved belief, acknowledge it and and try and refute, rather than support it, with the data.

“the choice of how to analyze Big Data should almost never start with “pick a tool, and use it”. It should invariably start with: pick a belief, and then challenge it. The choice of appropriate analytical tool (and data) should be driven by: what could change my mind?…”

Of course conflict isn’t only possible between intuition and data. It can also be created between different data patterns. Carraway has an earlier related post, “Big Data, Small Bets“, that looks at creating multiple small experiments for big data sets designed to minimize identifying patterns that are either random or not significant.

Thanks to Professor Carraway for elevating the discussion. Read his full post.

How long does it take to develop a mobile app?

We have covered and written about the issues enterprises need to consider when planning to develop a mobile app, especially on choosing between native apps, mobile web apps (HTML5, etc.), or a hybrid approach that includes elements of each. And have discussed some of the choices / factors that would have an effect on the time required to bring an app to market, but made no attempt to advise or speculate on how long it should take to “develop a mobile app”. This is not a question with a straightforward answer as any software development manager will tell you.

There are many reasons estimating app development time is difficult, but there are also items outside of actual coding that need to be accounted for. For example, a key factor often not considered in measuring app development is the time involved to train or hire for skills. Since most organizations already have experience with standards such as HTML and CSS developing mobile web apps should be, ceteris paribus, less costly and quicker than developing a native app. This is especially true when the app needs to run on multiple devices with different APIs using different programing languages on multiple mobile (and possibly forked) operating systems. But there are often appealing device features that require native code expertise, and even using a mobile development framework which deals with most of this complexity requires learning something new.

App development schedules can also be at the mercy of app store approvals and not-always-predictable operating system updates.

As unlikely as it is to come up with a meaningful answer to the catchy (and borrowed) title of this post, executives need good estimates of the time and effort in developing specific mobile apps. But experience in developing mobile apps is still slim in many organizations and more non-technical managers are now involved in approving and paying for app development. So even limited information on length of effort can provide useful data points.

I found the survey that informed the Visual.ly infographic below via ReadWrite at How Long Does It Take To Build A Native Mobile App? [InfoGraphic]). It involved 100 iOS, Android and HTML5 app developers and was done by market research service AYTM for Kinvey, provider of a cloud backend platform for app developers.

Their finding? Developing an iOS or Android app takes 18 weeks. I didn’t see the survey questions so don’t know whether whether 18 weeks was an average of actual developments, opinions on what it should take, or something else.

Of course there are simple apps that can be created in a few days and some that will take much longer, but in either case the level of effort is almost always underestimated. Even with all the unanswered questions about resources etc., the infographic raises, the 18 week finding may helpfully temper somebody’s overly optimistic expectations.

 

Customer experiences, communications, and analytics

three epicenters of innovation in modern marketing
I recently discovered Scott Brinker’s Chief Marketing Technologist blog and recommend it as a useful resource for marketers. The Venn diagram above is from a recent post, 3 epicenters of innovation in modern marketing. It was the Venn diagram that first grabbed my attention because I love Venn diagrams as a communication tool, it reminded me of another Venn diagram well-received at the recent Gilbane Conference, and most of the conference discussions map to someplace in the illustration.

As good as the graphic is on its own, you should read Scott’s post and see what he has to say about the customer experience “revolution”.

Lest you think Scott is a little too blithe in his acceptance of the role of big data, see his The big data bubble in marketing — but a bigger future, where the first half of the (fairly long) post talks about all the hype around big data. But you should read the full post because he is right on target in describing the role of big data in marketing innovation, and in his conclusion that data-driven organizations will need to make use of big data though these data-driven and data-savvy organizations will take some time to build.

So don’t let current real or perceived hype about the role of big data in marketing lead you to discount its importance – it’s a matter of when, not if. “When” is not easy to predict, but will certainly be different depending on an organizations’ resources and ability to deal with complexity, and organizational and infrastructure changes.

HTML5 Definition Complete, W3C Moves to Interoperability Testing and Performance

HTML5_Logo_128The W3C announced today that the HTML5 definition is complete, and on schedule to be finalized in 2014. This is excellent news for the future of the open Web, that is, all of us. If you were involved in discussions about mobile development strategies at our recent conference you’ll want to check out all the details at http://dev.w3.org/html5/decision-policy/html5-2014-plan.

Moving right along, the HTML Working Group also published the first draft of HTML 5.1 so you can see a little further down the road for planning purposes. See http://www.w3.org/TR/2012/WD-html51-20121217/.

From the W3C newsletter…

W3C published today the complete definition of the “HTML5” and “Canvas 2D” specifications. Though not yet W3C standards, these specifications are now feature complete, meaning businesses and developers have a stable target for implementation and planning. “As of today, businesses know what they can rely on for HTML5 in the coming years, and what their customers will demand,” said Jeff Jaffe, W3C CEO. HTML5 is the cornerstone of the Open Web Platform, a full programming environment for cross-platform applications with access to device capabilities; video and animations; graphics; style, typography, and other tools for digital publishing; extensive network capabilities; and more.

To reduce browser fragmentation and extend implementations to the full range of tools that consume and produce HTML, W3C now embarks on the stage of W3C standardization devoted to interoperability and testing. W3C is on schedule to finalize the HTML5 standard in 2014. In parallel, the W3C community will continue its work on next generation HTML features, including extensions to complement built-in HTML5 accessibility, responsive images, and adaptive streaming.

Tablets in the Enterprise and BYOD strategies

A couple of observations about tablets in the enterprise:

  • Tablets of all dimensions have a role in enterprise use, as do all types of personal computing devices.
  • BYOD is certainly a challenge for some organizations, but is a reminder of how we should have been managing data all along.

Tablets and other personal computing devices in the enterprise
One reaction to Apple’s iPad mini last week was that it would change the dynamic of Apple’s market for tablets since a 7″ inch tablet is more appropriate for consumers so enterprises would stick to the 10″ versions. The only thing correct about this view is that the tablet market will change. But we don’t know how – use-cases are evolving and there are way too many variables beyond physical size. It seems just as likely that the iPad mini form-factor could grow faster in enterprises than the full size iPad. In any case there are certainly enterprise use cases for a smaller, cheaper iPad, especially since those seem to be the only significant differences, and there is no apparent app development cost or learning curve further easing enterprise adoption.

But the bigger point is that enterprises need to be able to support not only multiple tablet and smartphone form factors but a large subset of an unpredictably large set of personal device types.

This is not a new challenge, it is simply one that is accelerating because of the decreasing costs and increasing ease of device development. “Personal” devices in enterprises are not new – employees have often used their own personal computers especially as they shrunk in cost and to BYOD notebook size. Tablets and phones are the next step, but enterprises will soon be dealing with watches, wearable computing, and implants which is why…

BYOD strategies need to focus on the data not the devices
The BYOD continuum is also largely additive – employees aren’t just replacing devices but often using multiple devices to access and process much of the same data – keeping up with the variety and volume and versions of personal devices is hopeless. A BYOD management strategy that focuses on device management will at best have a negative impact on productivity, will certainly increase costs, and most likely fail. There are environments and applications where data security is critical enough to warrant the overhead of a device management strategy that approaches being fail-proof, but even in these cases the focus should be on the data itself with device control as a backup where it makes sense.

It may not be much easier to manage the data independently but that’s the ball to keep your eye on.

Frank Gilbane interview on Big Data

Big data is something we cover at our conference and this puzzles some given our audience of content managers, digital marketers, and IT, so I posted Why Big Data is important to Gilbane Conference attendees on gilbane.com to explain why. In the post I also included a list of the presentations at Gilbane Boston that address big data. We don’t have a dedicated track for big data at the conference but there are six presentations including a keynote.

I was also interviewed on the CMS-Connected internet news program about big data the same week, which gave me an opportunity to answer some additional questions about big data and its relevance to the same kind of  audience. There is still a lot more to say about this, but the post and the interview combined cover the basics.

The CMS-Connected show was an hour long and also included Scott and Tyler interviewing Rob Rose on big data and other topics. You can see the entire show here, or just the 12 twelve minute interview with me below.

W3C Web Platform Docs – a new resource for web developers

Web Platform.orgW3C announced Web Platform Docs, which promises to be a valuable new resource for web developers of all levels. Imagine a single site that you can depend on for up-to-date, accurate, and browser and device neutral answers and advice for both simple and complex questions. It is brand new and “alpha” but already useful. Below is info from their announcement and a short video. For those of us that prefer textual info see this blog post from Doug Schepers: http://blog.webplatform.org/2012/10/one-small-step/

W3C, in collaboration with Adobe, Facebook, Google, HP, Microsoft, Mozilla, Nokia, Opera, and others, announced today the alpha release of Web Platform Docs (docs.webplatform.org). This is a new community-driven site that aims to become a comprehensive and authoritative source for web developer documentation. With Web Platform Docs, web professionals will save time and resources by consulting with confidence a single site for current, cross-browser and cross-device coding best practices.

Tablet market evolution and mobile development strategies

It was only about a year ago that the tablet market was only really about general-purpose tablets. There was the dominant iPad, and the fragmented Android market. Ebook readers were a separate animal altogether, although the anticipated release of the first Kindle Fire raised the question of whether it would bridge the general-purpose and ebook market.

In some ways it did, adding enough apps and internet access that it was hard not to sneak in some work email or web research even when your laptop or iPad was purposely left at home for the weekend away with the family. But of course Amazon’s business model was/is different – a subsidized device to increase the sale of content. And Amazon’s use of Android was significantly more customized than other Android tablets.

The folks over at Tech.pinions continue to be a must-read for anyone following/investing in the tablet market. John Kirk in Battle of The Tablet Business Models: Lessons Learned and a Look Ahead, argues that the future of the tablet model will be determined by the business models behind them, and points out some consistencies and lack thereof between the major players, Apple, Amazon, Google, Samsung and Microsoft. He is surely right that too often commentators and analysts have focused on hardware characteristics and software and not paid enough attention to business models. However, product capabilities can either create new business model possibilities or prevent their success so also help determine the landscape. For example, a non-glare, color display with low power requirements that combines the best of an iPad and a Kindle will certainly have a material effect on the market. In any case John’s post contains a number of nuggets.

Another aspect to consider in tablet market evolution is the difference between enterprise and consumer tablet markets. We’ll look at that in another post.

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