Category Archives: Information Technology

The Great #Data Overload Part 2: Is #Digital Making Us Dumber?

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The pursuit of digital (and by implication, many data-related activities) is making us dumber. Whether it’s constant multi-tasking, the need for instant gratification, the compulsion to always be “on”, or the ease of access to content and connections, there’s actually a law of diminishing returns in trying to capture and engage with all this “stuff”.

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Image © 2014 Universal Pictures

Consequently, our decision-making is increasingly governed by a hair-trigger mechanism – a single-click here, a right-swipe there, a “Like”/”Share” here, there, everywhere – which makes the outcome far less important than the instantaneous and self-validating process (“I Tweet therefore I am”). The quality of our interactions and relationships risks being reduced to a single lowest common denominator of the “fear of missing out” (#FoMo).

Current business practises focus on lean, agile and flexible – meaning that we have to get used to operating in a rapidly moving environment. However, agility is not helped by either procrastination or rash calls.

Faced with these demands on our attention, how can we come to a truly informed opinion or considered conclusion? The trick is knowing whether or not you are required to respond (not everything is relevant, vital or critical that it needs your constant or immediate participation – sometimes silence is golden). If you must make a call, then know when you have enough (hopefully, the “right”) data to make a rational and reasonable decision.

How do we build a capacity for calm, considered and constructive engagement with the digital world?

Part of the challenge is changing our (recently acquired) habits and behaviours. Speaking to friends and colleagues, there is a growing realization that reaching for your smart phone just before going to sleep (or as soon as you wake up), or constantly checking for status updates, is a noxious habit. Apart from the impact it has on our brain activity, it is also reinforcing our belief that this is normal, that we are somehow subservient to these devices, and that interacting with the digital environment takes priority over everything else. I know, I’m as guilty as the next person (watching the tennis on TV while checking the cricket scores on my iPhone…), but I am also trying to be more critical of my own digital consumption:

  • Not responding immediately to every e-mail – this is about time management skills as much as anything else; the faster you respond, the more you raise expectations that you will always answer straightway
  • Unsubscribing to mailing lists – in recent weeks, I have been unsubscribing to various newsletters because I was simply no longer interested in them or because they were no longer useful; if something’s important enough, I’ll no doubt find out about it from another source
  • Being selective about social media – I’ve written about this before in the context of authenticity and personal branding; in short, I find it essential to use different social media tools for different purposes (and to use each tool differently). That way, I manage to keep some separation between various parts of my professional and personal lives – at the very least, it acts as a helpful filter between the public and private
  • Choosing on-line connections carefully – this is another topic I have covered in a previous blog; not all our interactions are equal, and other than some basic relationship filters, most social network platforms don’t allow us to distinguish between friends, colleagues, acquaintances, and someone we met at a conference.* So, I generally decline unsolicited “friend” requests if I have not actually met or interacted with the person previously, or if I cannot find relevant mutual connections, or if I do not see what value I can add by being connected to this person.
  • Limiting notifications and status updates – similar to managing in-bound e-mail, I tend to switch off/ignore real-time notifications and updates. Instead, I prefer to check-in no more than once or twice a day, rather than always being logged in.

Finally, I’m hoping to develop a status setting for my smart phone that responds to all incoming notifications with messages such as: “Neither on nor off, merely resting”, “taking a mental pause”, “out to lunch”, or “making time for reflection before I respond”.**

Next week: Differentiating in a digital world

Notes:

* I recently heard about Humin, which is sort of moving in this direction, but it’s really a personalised CRM tool for your smart phone

** Apple’s “Do Not Disturb” function only supports “on/off” with respect to phone calls, and with a limited scope to filter contacts

Analog games – interactive, real-time, educational, creative

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At various times this blog has featured articles on analog technology, and the importance of making time for play. My theme this week returns to these topics – and quite appropriately as the holiday season and gift-giving are upon us.

As part of the run-up to the holidays, last week my wife and I were at a local restaurant to meet with friends who were visiting from overseas. Among the party were four children, all aged under 10. Now, I’m sure many readers will be familiar with the situation – friends who haven’t seen each other for a while want to catch up and enjoy some good conversation over a relaxing dinner, and more often than not, the digital pacifier (smart phone, tablet, portable DVD player or games console) will be brought out to keep the children occupied.

Well, I have to say I was very pleasantly surprised that our four younger diners were fully engaged in each other’s company for nearly four hours – and not a screen in sight. Instead, they happily played together with the following toys and games:

  • A board game of Ludo
  • Some LEGO mini-figures
  • A box of alphabet flash cards

They even managed to invent their own game using the flash cards.

I’m not saying that younger children shouldn’t be playing with apps or video games – but screen time has to be used constructively, not as a default setting. I’m also aware that many apps and games can be educational and interactive. But I don’t think we place enough value on enabling and encouraging children to play games in real-time, with real friends, using toys that they can easily understand and control.

On a related note, another friend recently bought his wife a record player, so they could rediscover their vinyl music collection. Their young daughter, on seeing and hearing the gramophone in action asked, “How does the sound come out of those round things?”

How often do children display the same curiosity about how mp3’s or YouTube work?

On that note, I would like to take this opportunity to wish you a safe and peaceful festive season. In particular, I would like to thank all my regular readers who have each given me feedback on what they like about this blog, especially those who have been generous enough to either comment on or critique specific content.

#Startup Victoria finds the human connection

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The team behind Startup Victoria held the inaugural Above All Human conference in Melbourne last week, co-directed by Susan Wu and Bronwen Clune, and MC’d by futurist Mark Pesce. If there was a single, overarching theme to the day, I would sum it up as: don’t overlook the human component in what you do.

Whether you are a startup founder or investor, defining your purpose is not enough; it also takes considerable self-awareness to build an innovative, successful, and sustainable business. It also requires curiosity, risk-taking, resourcefulness, empathy, creativity, resilience, perception, drive, reflection, vision, perseverance, passion, luck and critical thinking….

Featuring an interesting mix of established, experienced and emerging startup entrepreneurs and experts, we were treated to a broad range of themes including:

  • bringing financial services to the “unbanked” world;
  • the importance of design;
  • building startup platforms and ecosystems;
  • the power of storytelling;
  • challenging gender bias in the tech sector;
  • the potential of mass customisation;
  • understanding the value of an accelerator program;
  • the ethics of driverless cars;
  • changing minds with technology; and
  • the wisdom of knowing when to give up the dream and move on to the next opportunity.

Aside from the plenary, Q&A and panel sessions, there were product demos and startup pitches, and the whole event offered a valuable learning opportunity for anyone interested in engaging with the local startup community, or those curious about making connections between technology and the human condition.

Finally, it should be said that without Melbourne’s growing status as a global startup venue, the organisers would have been unable to attract such an impressive cohort of international speakers. This also reinforces Melbourne’s reputation as one of the world’s most livable cities (#1 or #11 depending on which list you are reading…).

 

The New Alchemy – Turning #BigData into Valuable Insights

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Here’s the paradox facing the consumption and analysis of #BigData: the cost of data collection, storage and distribution may be decreasing, but the effort to turn data into unique, valuable and actionable insights is actually increasing – despite the expanding availability of data mining and visualisation applications.

One colleague has described the deluge of data that businesses are having to deal with as “the firehose of information”. We are almost drowning in data and most of us are navigating up river without a steering implement. At the risk of stretching the aquatic metaphor, it’s rather like the Sorcerer’s Apprentice: we wanted “easy” data, so the internet, mobile devices and social media granted our wish in abundance. But we got lazy/greedy, forgot how to turn the tap off and now we can’t find enough vessels to hold the stuff, let alone figure out what we are going to do with it. Switching analogies, it’s a case of “can’t see the wood for the trees”.

Perhaps it would be helpful to provide some terms of reference: what exactly is “big data”?

First, size definitely matters, especially when you are thinking of investing in new technologies to process more data more often. For any database less than say, 0.5TB, the economies of scale may dissuade you from doing anything other than deploy more processing power and/or capacity, as opposed to paying for a dedicated, super-fast analytics engine. (Of course, the situation also depends on how fast the data is growing, how many transactions or records need to be processed, and how often those records change.)

Second, processing velocity, volume and data variety are also factors – for example, unless you are a major investment bank with a need for high-frequency, low-latency algorithmic market trading solutions, then you can probably make do with off-the-shelf order routing and processing platforms. Even “near real-time” data processing speeds may be overkill for what you are trying to analyze. Here’s a case in point:

Slick advertorial content, and I agree that the insights (and opportunities) are in the delta – what’s changed, what’s different? But do I really need to know what my customers are doing every 15 seconds? For a start, it might have been helpful to explain what APM is (I had to Google it, and CA did not come up in the Top 10 results). Then explain what it is about the resulting analytics that NAB is now using to drive business results. For instance, what does it really mean if peak mobile banking usage is 8-9am (and did I really need an APM solution to find this out?) Are NAB going to lease more mobile bandwidth to support client access on commuter trains? Has NAB considered push technology to give clients account balances at scheduled times? Is NAB adopting technology to shape transactional and service pricing according to peak demand? (Note: when discussing this example with some colleagues, we found it ironic that a simple inter-bank transfer can still take several days before the money reaches your account…)

Third, there are trade-offs when dealing with structured versus non-structured data. Buying dedicated analytics engines may make sense when you want to do deep mining of structured data (“tell me what I already know about my customers”), but that might only work if the data resides in a single location, or in multiple sites that can easily communicate with each other. Often, highly structured data is also highly siloed, meaning the efficiency gains may be marginal unless the analytics engine can do the data trawling and transformation more effectively than traditional data interrogation (e.g., query and matching tools). On the other hand, the real value may be in unstructured data (“tell me something about my customers I don’t know”), typically captured in a single location but usually monitored only for visitor volume or stickiness (e.g., a customer feedback portal or user bulletin board).

So, to data visualisation.

Put simplistically, if a picture can paint a thousand words, data visualisation should be able to unearth the nuggets of gold sitting in your data warehouse. Our “visual language” is capable of identifying patterns as well as discerning abstract forms, of describing subtle nuances of shade as well as defining stark tonal contrasts. But I think we are still working towards a visual taxonomy that can turn data into meaningful and actionable insights. A good example of this might be so-called sentiment analysis (e.g., derived from social media commentary), where content can be weighted and scored (positive/negative, frequency, number of followers, level of sharing, influence ranking) to show what your customers might be saying about your brand on Twitter or Facebook. The resulting heat map may reveal what topics are hot, but unless you can establish some benchmarks, or distinguish between genuine customers and “followers for hire”, or can identify other connections with this data (e.g., links with your CRM system), it’s an interesting abstract image but can you really understand what it is saying?

Another area where data visualisation is being used is in targeted marketing based on customer profiles and sales history (e.g., location-based promotion using NFC solutions powered by data analytics). For example, with more self-serve check-outs, supermarkets have to re-think where they place the impulse-buy confectionary displays (and those magazine racks that were great for killing time while queuing up to pay…). What if they could scan your shopping items as you place them in your basket, and combined with what they already know about your shopping habits, they could map your journey around the store to predict what’s on your shopping list, thereby prompting you via your smart phone (or the basket itself?) towards your regular items, even saving you time in the process. And then they reward you with a special “in-store only” offer on your favourite chocolate. Sounds a bit spooky, but we know retailers already do something similar with their existing loyalty cards and reward programs.

Finally, what are some of the tools that businesses are using? Here are just a few that I have heard mentioned recently (please note I have not used any of these myself, although I have seen sales demos of some applications – these are definitely not personal recommendations, and you should obviously do your own research and due diligence):

For managing and distributing big data, Apache Hadoop was name-checked at a financial data conference I attended last month, along with kdb+ to process large time-series data, and GetGo to power faster download speeds. Python was cited for developing machine learning and even predictive tools, while DataWatch is taking its data transformation platform into real-time social media sentiment analysis (including heat and field map visualisation). YellowFin is an established dashboard reporting tool for BI analytics and monitoring, and of course Tableau is a popular visualisation solution for multiple data types. Lastly, ThoughtWeb combines deep data mining (e.g., finding hitherto unknown connections between people, businesses and projects via media coverage, social networks and company filings) with innovative visualisation and data display.

Next week: a few profundities (and many expletives) from Dave McClure of 500 Startups