An in-depth Interview with Allan Engelhardt about Analytics

In-depth with Allan Engelhardt


Part of the In-depth series of interviews

PJT Today’s interview is with Allan Engelhardt, co-founder and principal of insights and analytics consultancy Cybaea. Allan and I know each other from when we both worked at Bupa. I was interested to understand the directions that he has been pursuing in recent years.
PJT Allan, we know each other well, but could you provide a pen picture of your career to date and the types of work that you have been engaged in?
AE I started out in experimental physics working on (very) big data from CERN, the large research lab near Geneva, and worked there after getting my degree. Then, like many other physicists, I was recruited into financial services, in my case to do risk management. From there to a consultancy helping business make use of bleeding edge technology and then on to CRM and customer loyalty. This last move was important for me, allowing me to move beyond the technology to be as much about commercial business strategy and operations.

In 2002 a couple of us left the consultancy to help customers move beyond transactional infrastructure, which is really what ‘CRM’ was about at the time, to create high value solution on top, and to create the organizational and commercial ownership of the customer needed to consistently drive value from data, inventing the concept of Customer Value Management which is now universally implemented by telcos across the world and increasingly adopted by other industries.

PJT There is no ISO definition of either insight or analytics. As an expert in these fields, can I ask you to offer your take on the meaning of these terms?
AE To me analytics is about finding meaning from information and data, while insights is about understanding the business opportunities in that meaning. But different people use the terms differently.
PJT I must give you an opportunity to both explain what Cybaea does and how the name came about.
AE At Cybaea we are passionate about value creation and commercial results. We have been called ‘Management consultants with a black belt in data’ and we help organizations identify and act upon data driven opportunities in the areas of:

Cybaea offering

  1. Customer Value Management (CVM), including acquisition, churn, cross-sell, segmentation, and more, across online and offline channels and industries, both B2C and B2B.
  2. Customer Experience and Advocacy, including Net Promoter System and Net Promoter Economics, customer journey optimization, and customer experience.
  3. Innovation and Growth, including data-driven product and proposition development, data monetisation, and distribution and sales strategy.

For our customers, CVM projects typically deliver additional 5% EBITDA growth annually, which you can measure very robustly because much of it is direct marketing. Experience and Advocacy projects typically deliver in the region of 20% EBITDA improvement to our clients, but it is harder to measure accurately because you must go above the line for this level of impact. And for Innovation and Growth, the sky is the limit.

As for the name, we founded the company in 2002 and wanted a short domain name that was a real word. It turned out to be difficult to find an available, short ‘.com’ at the peak of the dot-bomb era! We settled on ‘cybaea’ which my Latin dictionary translated as ‘trading vessel’; historically, it was a type of merchant ship of Greek origin, common in the Mediterranean, which Cicero describes as “most beautiful and richly adorned”. We always say we want to change the name, but it never happens; I guess if it was good enough for Cicero, then it is good enough for us.

PJT While at Bupa you led work that was very beneficial to the organisation and which is now the subject of a public Cybaea case study, can you tell readers a bit more about this?
AE Certainly, and the case study is available at for anyone who wants to read more.

This was working with Bupa Global; a Bupa business unit that primarily provides international private medical insurance for 2 million customers living in over 195 different countries. Towards the end of 2013, Bupa Global set out on a strategic journey to deliver sustained growth. A key element of this was the design and launch of a completely new set of products and propositions, replacing the existing portfolio, with the objective of attracting and servicing new customer segments, complying with changing regulation and meeting customer expectations.

The strategic driver was therefore very much in the Innovation and Growth space we outlined above, and I joined Bupa’s global Leadership Team to create and lead the commercial insights function that would support this change with deep understanding of the target customers and the markets in which they live. Additionally, Bupa had very high ambitions for its Net Promoter programme (Experience and Advocacy) where we delivered the most advanced installation across the global business, and for Customer Value Management we demonstrated nearly 2% reduction in the Claims line (EBITDA) from one single project.

For the new propositions, we initially interviewed over 3,000 individuals on five continents to understand value- and purchase drivers, researched 195 markets to size demand across all customer segments, and further deep-dived into key markets to understand the competitors with products, features, and prices, as well as the regulatory environment, and distribution options. This was supported by a very practical Customer Lifetime Value model, which we developed.

Suffice to say that in two years we had designed and implemented a completely new set of propositions and taken them live in more than twenty priority markets where they replaced the old products.

The strategic and commercial results were clearly delivered. But when I asked our CEO what he thought was the main contribution of the team and the new insights function, he focused on trust: “Every major strategic decision we made was backed by robust data and deep insights in which the executive team had full confidence.”

In a period of change, trust is perhaps the key currency. Trust that you are doing the right things for the right reasons, and the ability to explain why that is. This is key to get everybody behind the changes that need to happen. This is what the scientific method applied to data, analytics, and insights can bring to a commercial organization, and it inspires me to continue what we are doing.

PJT We have both been engaged in what is now generally called the Data arena for many years, some aspects of the technology employed have changed a lot during this time. What do you think modern technology enables today that was harder to achieve in the past and are there any areas where things are much the same as they were a decade or more ago?
AE Ever since the launch of the Amazon EC2 cloud computing service in late 2006 [1], data storage and processing infrastructure has been easily and cheaply available to everybody for most practical workloads. So, for ten years you have not had any excuse for not getting your data in order and doing serious analysis.

The main trend that excites me now is the breakthroughs happening in Deep Learning and Natural Language Processing, expanding the impact of data into completely new areas. This is great for consumers and for those companies that are at the leading edge of analytics and insights. For other organizations, however, who are struggling to deliver value from data, it means that the gap between where they are versus best practice is widening exponentially, which is a big worry.

PJT Taking technology to one side, what do you think are the main factors in successfully generating insight and developing analytical capabilities that are tightly coupled with value generation?
AE Two things are always at the forefront of my mind. The first is kind of obvious, namely to start with the business value you are trying to create and work backwards from that. Too often we see people start with the data (‘I got to clean all the data in my warehouse first!’), the technology (‘We need some Big Data infrastructure!’), or the analytics (‘We need a predictive churn model!’). That is cart before the horse. Not that these things are not important; rather, that there are almost certainly a lot of opportunities you could execute right now to generate real and measurable business value and drive a faster return on your investments.

The second is to not under-estimate the business change that is needed to exploit the insights. Analytical leaders have appetite for change and they plan and resource accordingly. Data and models are only part of the project to deliver the value and they are really clear on this.

PJT Looking at the other side of the coin, what at the pitfalls to look out for and do you have any recommendations for avoiding them?
AE The flip-side of the two points previously mentioned are obvious pitfalls: not starting from the business change and value you are trying to create. And it is not easy: great data scientists are not always great commercially-minded business people and so you need the right kind of skills to bridge that gap. McKinsey talks of ‘business translators who combine data savvy with industry and functional expertise’, which is a helpful summary [2]. Less helpfully they also note that these people are nearly impossible to find, so you may need to find or grow them internally.

Which gets to a second pitfall. When thinking about generating value from data, many want to do it all themselves. And I understand why: after all, data may well be a strategic asset for your organization.

But when you recruit, you should be clear in your mind if you are recruiting to deliver the change of creating the first models and changed business processes, or if you are recruiting to sustain the change by keeping the models current and incrementally improving the insights and processes. These two outcomes require people with quite different skills and vastly different temperaments.

We call them Explorers versus Farmers.

For the first, you want commercially-focused business people who can drive change in the organization; who can make things work quickly, whether that is data, analytics, or business processes, to demonstrate value; and who are supremely comfortable with uncertainties and unknowns.

For the second, you want people who are technically skilled to deliver and maintain the optimal stable platform and who love doing incremental improvements to technology, data, and business processes.

Explorers versus Farmers. Call them what you will, but note that they are different.

PJT Many companies are struggling with how to build analytical teams. Do they grow their own talent, do they hire numerate graduates or post graduates, do they seek to employ highly skilled and experienced individuals, do they form partnerships with external parties, or is a mixture of all of these approaches sensible? What approaches do you see at Cybaea clients adopting?
AE We are mostly seeing one of two approaches: one is to do nothing and soldier on as always relying on traditional business intelligence while the other is to hire usually highly technical people to build an internal team. Neither is optimal in getting to the value.

The do-nothing approach can make sense. Not, however, when it is adopted because management fears change (change will happen, regardless) or because they feel they don’t understand data (everybody understands data if it is communicated well). Those companies are just leaving money on the table: every organization have quick wins that can deliver value in weeks.

But it may be that you have no capacity for change and have made the informed decision that data and analytics must wait, reflecting the commercial reality. The key here is ‘informed’ and the follow-on question is if there are other ways that the company can realise some of the value from data right now.

The second approach at least recognises the value potential of data and aims to move the organization towards realising that value. But it is back to those ‘business translator’ roles we discussed before and making sure you have them, as well as making sure the business is aligned around the change that will be needed. Making money from data is a business function, not a technical one, and the function that drives the change must sit within the commercial business, not in IT or some other department that is still an arms-length support function.

We see the best organizations, the analytical leaders, employing flexible approaches. They focus on the outcomes and they have a sense of urgency driven from the top. They make it work.

PJT I know that a concept you are very interested in is Analytics as a Service (AaaS). Can you tell readers some more about what this means and also the work that Cybaea is doing in this area?
AE There is a war on analytical talent and a ‘winner takes it all’ dynamic is emerging with medium-sized enterprises especially losing out. Good people want to work with good people which generates a strong network effect giving advantage to large organizations with larger analytical teams and more variety of applications. Leading firms have depth of analytical talent and can recruit, trial, and filter more candidates, leaving them with the best talent.

Our analytics-as-a-service offering is for organizations of any size who want to realise value from data and insights right now, but who are not yet ready to build their own internal teams. We partner with the commercial teams to be their (commercial) insights function and deliver not just reports but real business change. Customers can pay monthly, pay for results, or we can do a build-operate-transfer model.

One of our first projects was with a small telco. They were too small to maintain a strong analytical team in-house, purely because of scale. We set up a monthly workshop with the commercial Marketing team. We analysed their data offline and used the time for a structured conversation about the new campaigns and the new changes to the web site they should implement this month. We would point them to our reports and dashboards which had models, graphs, t-tests, and p-values in abundance, but would focus the conversation on moving the business forward.

The following month we would repeat and identify new campaigns and new changes. After six months, they had more than 20 highly effective and precisely targeted campaigns running, and we handed over the maintenance (‘farming’) of the models to their IT teams. It is a model that works well across industries.

PJT Do you have a view on how the insights and analytics field is likely to change in coming years? Are there any emerging areas which you think readers should keep an eye on?
AE Many people are focused on the data explosion that is often called the ‘Internet of Things’ but more broadly means that more data gets generated and we consume more data for our analytics. I do think this opens tremendous opportunities for many businesses and technically I am excited to get back to processing live event streams as they happen.

But practically, we are seeing more success from deep learning. We have found that once an organization successfully implements one solution, whether artificial intelligence or complex natural language processing, then they want more. It is that powerful and that transformational, and breakthroughs in these fields are further expanding the impact into completely new area. My advice is that most organizations should at least trial what these approaches can do for them, and we have set up a sister-organization to develop and deliver solutions here.

PJT What are your plans for Cybaea in coming months?
AE I have two main priorities. First, I have our long-standing partner from India in London for a couple of months to figure out how we scale in the UK. This is for the analytics as a service but also for fast projects to deliver insights or analytical tools and applications.

Second, I am looking to identify the right partners and associates for Cybaea here in the UK to allow us to grow the business. We have great assets in our methodologies, clients, and people, and a tremendous opportunity for delivering commercial value from data, so I am very excited for the future.

PJT Allan, I would like to thank you for sharing with us the benefit of your experience and expertise in data matters, both of which have been very illuminating.

Allan Engelhardt can be reached at Allan.Engelhardt@cybaea.net. Cybaea’s website is www.cybaea.net and they have social media presence on LinkedIn and Google+.


Disclosure: Neither peterjamesthomas.com Ltd. nor any of its directors have any direct financial interest in either Cybaea or any of the other organisations mentioned in this article.


If you are a Chief Data Officer, a Chief Analytics Officer, a Director of Data, or hold some other “Top Data Job” and would like to share your thoughts with the readers of this site in an interview like this one, please get in contact.

 
Notes

 
[1]
 
https://aws.amazon.com/about-aws/whats-new/2006/08/24/announcing-amazon-elastic-compute-cloud-amazon-ec2—beta/
 
[2]
 
McKinsey report The Age of Analytics, dated December 2016, http://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/the-age-of-analytics-competing-in-a-data-driven-world

From: peterjamesthomas.com, home of The Data and Analytics Dictionary, The Anatomy of a Data Function and A Brief History of Databases

 

Solve if u r a genius

Solve if u r a genius - Less than 1% can do it!!!

I have some form when it comes to getting irritated by quasi-mathematical social media memes (see Facebook squares “puzzle” for example). Facebook, which I find myself using less and less frequently these days, has always been plagued by clickbait articles. Some of these can be rather unsavoury. One that does not have this particular issue, but which more than makes up for this in terms of general annoyance, is the many variants of:

Only a math[s] genius can solve [insert some dumb problem here] – can u?

Life is too short to complain about Facebook content, but this particular virus now seems to have infected LinkedIn (aka MicrosoftedIn) as well. Indeed as LinkedIn’s current “strategy” seems to be to ape what Facebook was doing a few years ago, perhaps this is not too surprising. Nevertheless, back in the day, LinkedIn used to be a reasonably serious site dedicated to networking and exchanging points of view with fellow professionals.

Those days appear to be fading fast, something I find sad. It seems that a number of people agree with me as – at the time of writing – over 9,000 people have viewed a LinkedIn article I briefly penned bemoaning this development. While some of the focus inevitably turned to general scorn being heaped on the new LinekdIn user experience (UX), it seemed that most people are of the same opinion as I am.

However, I suspect that there is little to be done and the folks at LinkedIn probably have their hands full trying to figure out how to address their UX catastrophe. Given this, I thought that if you can’t beat them, join them. So above appears my very own Mathematical meme, maybe it will catch on.

It should be noted that in this case “Less than 1% can do it!!!” is true, in the strictest sense. Unlike the original meme, so is the first piece of text!
 


Erratum: After 100s of views on my blog, 1,000s of views on LinkedIn and 10,000s of views on Twitter, it took Neil Raden (@NeilRaden) to point out that in the original image I had the sum running from n=0 as opposed to n=1. The former makes no sense whatsoever. I guess his company is called Hired Brains for a reason! This was meant to be a humorous post, but at least part of the joke is now on me.

– PJT

 

 

The Big Data Universe

The Royal Society - Big Data Universe (Click to view a larger version in a new window)

The above image is part of a much bigger infographic produced by The Royal Society about machine learning. You can view the whole image here.

I felt that this component was interesting in a stand-alone capacity.

The legend explains that a petabyte (Pb) is equal to a million gigabytes (Gb) [1], or 1 Pb = 106 Gb. A gigabyte itself is a billion bytes, or 1 Gb = 109 bytes. Recalling how we multiply indeces we can see that 1 Pb = 106 × 109 bytes = 106 + 9 bytes = 1015 bytes. 1015 also has a name, it’s called a quadrillion. Written out long hand:

1 quadrillion = 1,000,000,000,000,000

The estimate of the amount of data held by Google is fifteen thousand petabytes, let’s write that out long hand as well:

15,000 Pb = 15,000,000,000,000,000,000 bytes

That’s a lot of zeros. As is traditional with big numbers, let’s try to put this in context.

  1. The average size of a photo on an iPhone 7 is about 3.5 megabytes (1 Mb = 1,000,000 bytes), so Google could store about 4.3 trillion of such photos.

    iPhone 7 photo

  2. Stepping it up a bit, the average size of a high quality photo stored in CR2 format from a Canon EOS 5D Mark IV is ten times bigger at 35 Mb, so Google could store a mere 430 billion of these.

    Canon EOS 5D

  3. A high definition (1080p) movie is on average around 6 Gb, so Google could store the equivalent of 2.5 billion movies.

    The Complete Indiana Jones (helpful for Data Management professionals)

  4. If Google employees felt that this resolution wasn’t doing it for them, they could upgrade to 150 million 4K movies at around 100 Gb each.

    4K TV

  5. If instead they felt like reading, they could hold the equivalent of The Library of Congress print collections a mere 75 thousand times over [2].

    Library of Congress

  6. Rather than talking about bytes, 15,000 petametres is equivalent to about 1,600 light years and at this distance from us we find Messier Object 47 (M47), a star cluster which was first described an impressively long time ago in 1654.

    Messier 47

  7. If instead we consider 15,000 peta-miles, then this is around 2.5 million light years, which gets us all the way to our nearest neighbour, the Andromeda Galaxy [3].

    Andromeda

    The fastest that humankind has got anything bigger than a handful of sub-atomic particles to travel is the 17 kilometres per second (11 miles per second) at which Voyager 1 is currently speeding away from the Sun. At this speed, it would take the probe about 43 billion years to cover the 15,000 peta-miles to Andromeda. This is over three times longer than our best estimate of the current age of the Universe.

  8. Finally a more concrete example. If we consider a small cube, made of well concrete, and with dimensions of 1 cm in each direction, how big would a stack of 15,000 quadrillion of them be? Well, if arranged into a cube, each of the sides would be just under 25 km (15 and a bit miles) long. That’s a pretty big cube.

    Big cube (plan)

    If the base was placed in the vicinity of New York City, it would comfortably cover Manhattan, plus quite a bit of Brooklyn and The Bronx, plus most of Jersey City. It would extend up to Hackensack in the North West and almost reach JFK in the South East. The top of the cube would plough through the Troposphere and get half way through the Stratosphere before topping out. It would vie with Mars’s Olympus Mons for the title of highest planetary structure in the Solar System [4].

It is probably safe to say that 15,000 Pb is an astronomical figure.

Google played a central role in the initial creation of the collection of technologies that we now use the term Big Data to describe The image at the beginning of this article perhaps explains why this was the case (and indeed why they continue to be at the forefront of developing newer and better ways of dealing with large data sets).

As a point of order, when people start talking about “big data”, it is worth recalling just how big “big data” really is.
 


 Notes

 
[1]
 
In line with The Royal Society, I’m going to ignore the fact that these definitions were originally all in powers of 2 not 10.
 
[2]
 
The size of The Library of Congress print collections seems to have become irretrievably connected with the figure 10 terabytes (10 × 1012 bytes) for some reason. No one knows precisely, but 200 Tb seems to be a more reasonable approximation.
 
[3]
 
Applying the unimpeachable logic of eminent pseudoscientist and numerologist Erich von Däniken, what might be passed over as a mere coincidence by lesser minds, instead presents incontrovertible proof that Google’s PageRank algorithm was produced with the assistance of extraterrestrial life; which, if you think about it, explains quite a lot.
 
[4]
 
Though I suspect not for long, unless we chose some material other than concrete. Then I’m not a materials scientist, so what do I know?

 

 

The Great Divide – Worrying parallels between Windows 8 and the Xbox One

Yosemite Valley

Back in July 2012 in A William Tell Moment? I got a little carried away about the potential convergence between tablets and personal computers. Nearly a year later – and with the Surface Pro only becoming available in my native UK last month – I probably know better. The following is therefore a more balanced piece.

It’s been a while since I put finger-tip to keyboard on this web-site. The occurrence which motivated me to do so was the arrival of my first new home computer since 2008 (yes unfortunately dear reader, the author is that much of a Luddite). The time since 2008 has seen a lot of changes in the technology sphere, notably the rise of the tablet (at probably the third time of asking) and the near ubiquity of end user computing. Certainly in response to the former (and maybe with some influence from the latter) my new laptop (if you can so describe a 17.3” desktop replacement) came with Windows 8 pre-installed.

My new 'laptop'

I am obviously several months too late for my review of Microsoft’s latest OS to have much resonance and my brief comments here have no doubt been offered up by other pundits already. What I want to do instead is perhaps try to tie Windows 8 together with some broader trends and explore just how weird and polarised the technology market has become recently. However, some brief initial commentary on Windows 8 is perhaps pertinent.

The main thrust of Windows 8 is for Microsoft to remain relevant, perhaps not so much in its traditional arena of PC computing, but in the newer world of tablet and mobile computing. I’m sure some tablet fans may take issue with my observation, but my opinion is that Windows 8 is trying to do two, potentially incompatible, things: to be relevant to content creators and to content consumers. I am sure there are all sorts of examples of people creating amazing content on their iPads or Android tablets, however perhaps the surprise here is that it is done at all, rather than done well[1].

Regardless of some content creation doubtless occurring on tablets, I stand by my assertion that they are essentially platforms for the consumption of content; be that web-pages (sometimes masquerading as apps), games, videos, music, or increasingly feedback from the ever increasing range of sensors providing information about everything from the device’s location to its owner’s current heart rate. The content that is consumed on tablets is – in most cases – created on other types of devices; often the quotidian ones which have physical keyboards and pointing devices which allow for precision work.

Fitzgerald demonstrating that you can play two roles

In the past, the dichotomy between content creators and content consumers has been somewhat masked by them employing similar tools. Of course every content creator is also a content consumer, but it has always (“always” of course being an interesting word when what I probably mean is “since the Internet became mainstream”), been the case that there were significantly more of the latter than the former[2]. What was different historically was that both creators and consumers used the same kit; PCs of some flavour[3] (though maybe the former had better processors and more memory on their machines). The split in roles was evident (if it was evident at all) in computers that were only ever used to surf, do e-mail and write the occasional letter; there were probably an awful lot of these. We had a general purpose computing platform (the PC) which was being under-utilised by the majority of people who owned one.

The eventual adoption of tablets has changed this dynamic. Although of course many tablets have processors that previous generations of PCs could only have dreamed of, their focus is firmly on delivering only those elements of a PCs capabilities which most people use and eschewing those which the majority ignore. As always, specialisation and focus leads to superior execution. The author (no fan of Apple products in general) can confirm that an iPad is much more fit for purpose than a laptop when the purpose is watching a film or TV show on a train or plane. Laptops can of course do this, but they are over-engineered for the task and also pretty bulky if all you want is to watch something. Having played Angry Birds on each of Android, iOS and web-versions on a laptop, the experience is best on the smaller, lighter, touch-based devices.

PC and iPad

The reason that the sales of PCs have plummeted while those of tablets soar is not that tablets are better than PCs, nor is it even that they demystify computing in a way that their elder brethren fail to do (more on this later), but simply that tablets are more aligned with what the majority of people want from their computers; as above to be media platforms that allow basic surfing and e-mail. To borrow the phrase from the last paragraph, tablets are more fit for purpose if the purpose is consumption of content.

The flip side of this is what I am currently doing: namely writing this article, sourcing / editing / creating images to illustrate it and cutting some entry-level HTML in the process. I could of course do this on an iPad or Android tablet. However this is much like saying that you can (in extremis) use a foot-pump to re-inflate a car tyre, but why would you if you can make it to a garage / service station and get access to a machine that is dedicated to inflating tyres with greater efficiency. If there was no machine with a keypad to hand, then I might decide to write on an iPad, but it would be a frustrating and sub-optimal experience. PCs are more fit for purpose where the purpose is content creation.

Which market would you rather sell into?

However, we now reach a problem in economics. If we apply the Wikipedia percentages to content creators versus content consumers, then the split is (depending on which side of the fence you place editors) either 1 : 10 or 1 : 100. In either case, someone pitching hardware and software to a content creator is addressing a much smaller part of the marketplace than someone pitching hardware and software to content consumers; aka the mass market. This observation inexorably leads to the types of features and capabilities which will dominate any platforms aimed at general computer users; basically content consumers are king and content creators paupers.

Which returns me to Windows 8. The metro interface is avowedly designed for mobile devices with a touch-based interface. My new machine doesn’t have a touch screen. Why would I need one on a device that supports the much more efficient and precise input provided by a physical keyboard and mouse? Indeed, one of the nice things about my new laptop is its 1920×1080 screen, why would I want to cover this with as many annoying finger smudges as my iPad has when there are much better ways of interacting with the OS which also leave the monitor clean? In fact, on reflection, I guess that the majority of people and not just content creators would prefer a non-smeared screen most of the time.

There seem to be obvious usability snafus in Windows 8 as well. To highlight just one, if you move your mouse (aka finger) to the top right-hand side, one of the “charms” menus appears (I’d really like to know why Microsoft thought “charms” was a great name for this). But what is also at the top right-hand side of any maximised window? The close button of course. I have lost count of how many times I have wanted to close a programme and instead had the charming blue panel appear instead. I spent the first eight years of my career in commercial software development and fully appreciate that there is no such thing as bug-free code, however this type of glitch seems so avoidable that one has to question both Microsoft’s design and testing process.

An early adopter of Excel 2013

Anyway, enough on the faults of Windows 8. In time I’ll get used to it just as I did with Windows 95, 97, XP and 7. Just as I have got used to each version of Excel being harder to use than the last for anyone that has a track record with the application. Of course I’ll get used to Excel 2013, what choice do I have? But this leads us into another economic dichotomy. Microsoft don’t need to win me over to Excel, I’m going to put up with whatever silly thing they do to it in the latest version because that’s a lower hurdle than learning another spreadsheet; even assuming that something like Google Docs offers the same functionality. The renewal rates for products like Excel must be 95% plus, this means that a vendor like Microsoft focusses instead on getting new business from people who don’t use their applications. If this means making the application “easier” for new users, then who cares if existing users are inconvenienced, it’s not like they are going to stop using the application.

As I alluded to above, a general claim made for tablets (and for the iPad in particular) is that they demystify computing, making it accessible to “regular people” (as an aside here we have the entire cool dude versus nerd advertising encapsulated in “I’m a Mac, he’s a PC”, something which I think Microsoft are to be lauded for lampooning in their later campaign). Instead I would argue that tablets offer a limited slice of what computers can do (the genius being that it is the slice that 90% or 99% of content consumers seem to want). They don’t make computing easier or more accessible, they make it more limited and sell this as a benefit using words like “elegant”, “stripped-down” or “minimalist”.

Tablets clearly fill a large market need, I use them myself. However, my Window-centred gripe is when I have to buy a product (a PC) whose basic operation is dictated by a function (content consumption) for which the machine is over-engineered, whereas the function for which a PC is perfect (content creation) is symmetrically and even systematically compromised.

As things stand, maybe Microsoft should not be so concerned about losing the mobile and tablet market (perhaps for them it is already too late). Instead it could be argued that they should be more worried about, though a lack of attention to the needs of their core users, forfeiting the PC market which they have dominated for so long and in which their products (pre-Windows 8 at least) were the ones best suited to the job at hand.

Brothers in arms?

The recent launch of the Xbox One (whatever happened to sequential numbering by the way?) was roundly condemned by gamers as focussing too much on the new console being a media hub (again attracting new users) rather than a gaming platform (again ignoring the needs of existing users). At least one cannot accuse Microsoft of being inconsistent, but alienating existing customers is seldom a great long-term strategy for a business.


Notes

[1] Let’s glide seamlessly over Samuel Johnson’s original application of this image to comment on women preachers; the 18th Century is certainly a foreign country and I’m rather glad that we now [mostly] do things differently here.
[2] By way of illustration, Wikipedia tends to assume the 90-9-1 rule. 1% of users create content, 9% edit or otherwise modify content, the rest consume.[citation needed]
[3] Although maybe the term PC has become synonymous with Wintel based machines, I include here personal computers running flavours of UNIX such as Mac OS and Linux.

 

 

A William Tell moment?

Microsoft Surface
Image © Microsoft


Disclosure #1: As is inevitable for any IT professional, the author has used Microsoft’s enterprise products at many points during his career. As is inevitable for any sentient inhabitant of planet Earth, he has used their more broadly targeted software on a daily basis for longer than he can remember (many of the images on this site were created via the combination of Visio supplemented by the non-MS – and horribly old school – PaintShop Pro). He has no direct holdings in Microsoft, but undoubtedly must have some interest in the company indirectly via pension or investment funds; something that would probably also hold for all of Microsoft’s main competitors.

Disclosure #2: Beyond this, the author has been featured in a Microsoft Business Intelligence video; but this did not relate to the endorsement of any Microsoft product.

Disclosure #3: The author can proudly state that he has never owned any Apple product, but does periodically use a corporate iPad and has occasional access to an iPhone owned by someone else (doesn’t everyone?). Rumours that he has three stars at all levels of Angry Birds Space have not been independently verified.

Disclosure #4: The author has neither seen directly, nor further still touched a Surface – though if Microsoft wanted to remedy this situation, he would at the very least guarantee them a thorough (and professionally neutral) review.


It’s somewhat odd to report that I am rather excited by an announcement Redmond’s finest (with apologies to Nintendo America). Like many people I have had a love / hate relationship with the Washington behemoth for more years than I care to remember; having lived through the hype and subsequent let down of every MS O/S since 95. Come to think of it, as my girlfriend suggests, that would be a great slogan: “Microsoft – disappointing expectant millions since 1995!”

Maybe my general take on the firm’s recent output was best summed up by another noted industry commentator:

Perceptive tech industry commentary
“My new computer came with Windows 7. Windows 7 is much more user-friendly than Windows Vista. I don’t like that.”

However, having had to put up with umpteen technology industry commentators sycophantically parroting Cupertino’s “the PC is dead, long live the tablet” mantra over the last few years, it is gratifying to think that there may (and I stress may) soon be a tablet available that is also a proper computer; i.e. one that you can actually do useful things on, rather than fashion accessory cum entertainment centre with a bad browser and support for only for the type of games that you can play equally well on your Facebook page. Please don’t get me wrong, as I mention above, I’m as much a fan of Angry Birds as the next guy, but as a lapsed gamer myself I can hopefully tell the difference between a gaming platform and an amusing diversion.

The ubiquitous iPad has been touted as bringing computing to the non-technically literate masses. Instead it has brought a grossly watered down ability to conspicuously consume at the expense of any support for creative activities. In my opinion, the oft repeated phrase that “there’s an app for that” tends only to work when “that” is a pretty narrow range of activities. I’m on my iPad; I want to update my Facebook status – tick; I want to upload an un-edited photo I just took – tick (on some models at least); I want to tweet something (maybe even including a URL I have copied from elsewhere) – tick (fiddly as this might be); I want to write a lightly formatted blog post without too many typos and which includes a couple of images I have either lightly-edited, or created from scratch – um…

Smarter than the average iPad user?

That’s where most types of tablet seem to hit their limit, Android as well as iOS (and undoubtedly Amazon’s offering as well); casual surfing (be it browser or other app based), checking mail, watching a movie, working out what street I am on, simple social medial interactions. These things are all OK and all are light on content creation. Anything else (even a lengthy e-mail – something I specialise in) quickly becomes a chore. Pointedly, all of the things that I have mentioned working well on tablets, also work at least to close to as well on a decent sized smart ‘phone, which also has the benefit of actually being portable and also (at least in most cases) of being a ‘phone.

So, given my zeitgeist-busting lack of whelmedness with tablets, where does that leave Ballmer’s latest offering. Well, let’s discount the ARM-based, “me too” version (with apologies to my fellow inhabitants of Cambridge; East Anglia, not Massachusetts) and focus on the Ivy Bridge-powered Surface Pro. This is (as far as can be discerned from the [limited] information that Redmond have thusfar divulged) where the real attention will inevitably focus. As the BBC’s (oft lampooned) technology correspondent states:

“At one small business this week – my excellent local optician – I learned that the owner plans to replace all his PCs with Surface tablets when they come out. Why not go straight to iPads, I wondered – only to learn that just about every ophthalmic application was Windows-based.”

http://www.bbc.co.uk/news/technology-18626087

I.e. there are an awful lot of proper, grown-up applications out there which only work on the dreadfully uncool WinTel platform. Indeed, outside of the creative industries (like other parts of industry can’t be creative?) and parts of science that rely upon tuned-up versions of graphical software that emanates essentially from the former (or which were provided “free” back in the day by those awfully nice Apple chaps), most business-focussed software (that is not already web-based) is WinTel based.

A long long time ago / I can still remember how / That gadget used to make me smile / And I knew if I did my tricks / That I could save those people's clicks /  And maybe they'd be happy for a while...

The idea of a proper computer that can (as far as we can tell at present) support all of the above, plus coming in a conveniently portable tablet-like package; but – crucially – with adult input devices like (shock-horror) a keyboard and track-pad and (even more shock and even more horror) a DisplayPort port for those tasks (like many of mine) where at 10” monitor is way too small and (Nightmare on Elm Street levels of horror) a USB 3.0 port; sounds awfully like the tablet concept coming of age (or, for those with an historical bent, fulfilling the vision that Bill Gates originally outlined for the device, long before the late Steve Jobs imbued it with his irreplaceable and inimitable coolness).

Many much wiser commentators than me have stated that the Surface will live or die based on the quality and extent of the app ecosystem it develops around it. For me the Pro has all the apps you could ever need, the Windows ones that people use to actually do things.

Of course the devil is in those (perhaps worryingly as yet undisclosed) details. What will the precise specs of the Surface Pro processor and RAM be? What is the screen resolution? How long will the battery last? How good a keyboard substitute will the Type Cover be in practice? Why on Earth does the RT come with Office and the machine set up to run it properly apparently doesn’t? Will Metro be pleasurable to use in those (infrequent) moments when all you actually want is an entertainment platform? These will all become clear in time no doubt, and there is obviously more than enough scope for Microsoft to disappoint me again. However, at present I am holding on to the glimmer of hope that this time they have got it right. If they have, the Surface could be very good indeed. As Don Maclean never sang:

  So bye bye to my Pad with an ‘i’
Get a Surface in to yer place
Won’t you give it a try
Those Angry Birds may may just have to fly
Singing this could be the tablet I’d buy
 

 

You have to love Google

…well if you used to be a Number Theorist that is.

Google / Fermat

It’s almost enough to make me forgive them for Gmail’s consider including “feature”. Almost!
 

 

LinkedIn does what it says on the can

Referring domains
An analysis of peterjamesthomas.com traffic based on linking site

I suppose, given that this is a essentially professional blog, I should not be surprised that LinkedIn dominates traffic for me, dwarfing even the mighty Google and Twitter (incidentally Facebook was in 13th place, below Microsoft – a verdict of “could do better”, but then Facebook is only semi-pro for me).

It is also worth noting that traffic from all WordPress blogs (not included in the 4% WordPress figure above) amounted to 3% of traffic. Adding in all other non-corporate blogs got this to 5% and notional 4th place).

It is also notable that StumbleUpon outdid all other social bookmarking sites, with Reddit next in a lowly 23rd place.
 
 
Some selected top threes…

Please note that the only criteria here is quantum of traffic.
 
 
The Social Media “Big Three”

  1. LinkedIn
  2. Twitter
  3. Facebook

 
Vendors

  1. Microsoft
  2. SAS
  3. IBM

 
Blogs

  1. Oracle Business Intelligence 101
  2. Judith Hurwitz
  3. Merv Adrian

 
Social Bookmarking

  1. StumbleUpon
  2. Reddit
  3. Delicious

 
Blog Readers

  1. Bloglines (now sadly defunct)
  2. Netvibes
  3. Google Reader

 
Technology News / Communities

  1. Smart Data Collective
  2. IT Business Edge
  3. Joint: IT Finance Connection & Social Media Today

 
Media

  1. CIO Magazine
  2. The Economist
  3. Computing

 

I should point out that the figures presented above are all-time, rather than say the last six months. It would be interesting to do some trending, but this is a bit more clunky to achieve than one might expect.
 

Four [Social Media] Failures and a Success

Four Social Media Failures and a Success - with apologies to Mike Newell

Introduction

The internet is full of articles claiming to transform the reader into the Social Media equivalent of Charles Atlas. I have written some of them myself (though hopefully while highlighting that that things are seldom as simple as ticking a set of boxes). Bearing in mind the old adage that you learn more from your mistakes than your successes, here are some thoughts on Social Media failures; the first three are mine and the fourth a failure that seems very widespread. Lest this article becomes too depressing, I will close with a more positive piece of Social Media news.
 
 
Failure 1 – Thinking that you can dip in and out of Social Media

Articles per month

I recently came across Ken Mueller’s blog via a LinkedIn Group (see the segment of New Adventures in WiFi that relates to LinkedIn for some thoughts on groups). In one of his articles he lays out what he sees as the factors that have led to him tripling his blog traffic. Foremost amongst these is consistency:

I’ve been doing this every day for about 2 years now. Some of the growth that I’m seeing is due to just plugging away and forcing myself to blog every day, hopefully creating good, relevant content that people want to read. If I take a day off, I notice a drop in traffic. In fact, I always see a drop in my November traffic because I go away for Thanksgiving to an area with no Internet access.

A quick look at the above chart, which shows the number of articles I have published each month since founding this blog back in November 2008, will reveal that consistency hasn’t been my middle name.

For a variety of reasons, I have had periods where I have sustained a high output of articles (without, it is to be hoped, quantity compromising quality) and periods where my writing has slowed to a barely perceptible trickle. To take an ultra-prosaic example, I started writing this piece while commuting by train and my recent output is highly correlated with my method of transportation.

Now what shall I blog about today? ... Sadly I don't travel too much on the London Tube nowadays - odd the things that you miss

Coming out of some of the troughs in writing, I have sometimes felt that I could simply pick up where I left off. This is probably the case with some niche readers who may visit this site; this is precisely because at least some of my content is directly pertinent to them from time to time. However, after a while, even they may have looked elsewhere for their regular fix of the topics I cover here. Beyond this, there is equally likely to be a second cohort of casual readers who will quickly move on to pastures new if the grass here does not re-grow apace [note to self, I am meant to be restraining myself from overly liberal use of analogies, must try harder!].

Even if an author has written several articles that have proved popular with a number of people; after anything more than a few weeks’ lay-off, it can almost be like starting again from scratch. To employ a too widely-used phrase, you are only as good as your last month’s (or maybe week’s, or maybe day’s) output.

7th November 2002 - Brisbane Cricket Ground, Queensland, Australia. England's Simon Jones ruptures a cruciate ligament. It took him until 11th March 2004 to play for England again.

Disregarding for the moment my own parenthetic advice from the end of the paragraph before last, this feels rather familiar. It seems to be very like what it feels like trying to get fit again after an injury or time away from a sport. It doesn’t really matter if you had attained a certain level of fitness a year ago; what is relevant today is your current level of fitness and the gap between the two. Sometimes recalling just how long it took them to achieve a previous standard can be quite de-motivating to an athlete returning from a break. Once fit, it is a lot easier to stay fit than is is to regain lost fitness. The same applies to audiences and this is why – as Kevin suggests in his article – at least periodic blogging (assuming that it is of a standard) is essential.

My learning here is both to make time to write and also to re-engage with my readers.

[Perhaps ironically this article itself has been in gestation for a few weeks]
 
 
Failure 2 – Assuming that what has worked before will work again

Michael Schumacher's comeback - or how to dim a glistening reputation

I have a specific example in mind here and it relates to a blog post that precedes this one. In turn this goes back to a survey of senior IT people that I carried out predominantly via LinkedIn back in January 2009. This related to their view on the top priorities that they faced in their jobs. Recently I thought that it would be interesting to update this and – no doubt naturally – I also though that I would adopt the same modus operandi; i.e. LinkedIn. I even targeted the same Group – that of CIO Magazine.

linkedin CIO Magazine CIO Magazine forum

Sad to say, while I had dozens of responses last time round, there was been little or no response at all when I attempted to refresh the findings. I have been thinking about why this might be. Of course my musings are pure speculation, but a few ideas come to mind:

  1. The output of the last survey was not of much interest / didn’t tell people anything that they didn’t already know and so it was not worth the effort of replying again.
  2. The people frequenting the CIO Magazine LinkedIn Group back in 2009 were a very different set of people to now. Back then we were in the aftermath of the global banking crisis and perhaps a number of good people had more time on their hands than would normally be the case. Today, while the good times are not exactly rolling, I hope that a large tranche of these people are once more gainfully employed.
  3. It could be (as I have mentioned before) that the wild proliferation of LinkedIn groups means that people’s time and energy is spread over a wider set of these, with less time to devote to specific questions. I have no access to LinkedIn statistics, but would like to bet that while overall Group-based activity has no doubt increased, activity per group may well have decreased.
  4. Variants of the same question may have been asked so often that people have grown tired of answering it.
  5. This could be one of the early signs of general Social Media fatigue.

By way of contrast – and perhaps tapping into my thoughts about variants of the same question having been asked many times before – the same Group has a thread asking members to state in one word what their key challenge is. Although many of the replies are somewhat trite and there is a limit to how much information a single word can convey, it is instructive to think that an innovative approach (and one that requires little time typing a response) has been successful where my attempt to repeat a previous exercise has failed.

My learning here is to think of new ways to approach old material, rather than simply believing that your can repeat past successes.

[UPDATE: I posted on the original CIO Magazine Group threads to change its status to publicly available and started to receive new thoughts on this. Another thought – perhaps people are just more comfortable contributing to discussions that others have already engaged in, rather than being the first to comment?]
 
 
Failure 3 – Ascribing [as yet] unwarranted maturity to Social Media

Starting them young...

I religiously refrain from blogging about current work projects, however the following was 100% in the public domain of its very nature.

I have recently been doing some recruitment and – given both the increasing use of LinkedIn by recruitment firms in their work and that I have a pretty extensive network – thought that it would be worth trying to leverage Social Media to reach out to potential candidates. I did this via a status update, rather than taking the perhaps more obvious path of using the various job sections. My logic here was that I would potentially reach a wider audience in one go than via several postings within pertinent groups. I was also pursuing my recruitment through more traditional channels, so this idea could simply be viewed as a Social Media experiment.

As with any honest scientist, it is important that I state my negative results as well as positive. In this case, though I was contacted by many recruitment agencies, I didn’t get any feedback from actual candidates themselves at all. It could be argued that the failure was in the way I approached the experiment, or the narrowness of the channel that I selected. While both of these are true observations, the whole point of Social Media in business (if there is one) is to make either organisation-to-person, or person-to-person contact ridiculously easy and immediate. Regardless of my level of ineptitude, it wasn’t easy to achieve what I wanted to achieve and I abandoned my experiment after a week or so.

My learning here is to not to refrain from business / Social Media experimentation, but not to expect too much from what is after all an emerging area.
 
 
Failure 4 – Vendor employees not “getting” Social Media

Clueless about Social Media

I have often used this column to talk about my opinion that your choice of Business Intelligence tool is one of the least important factors in a BI/DW project. In the article I link to in the previous sentence, I quote from an interview I gave in which I compare the market for BI tools with that for cars. There is no definitive answer to the question “what is the best car?” and in the same way there is no “best BI tool”. Going further than this, there are many other areas of a BI/DW project which, if done well, will come close to guaranteeing your success regardless of which BI tool you select; but, if done badly, will come close to guaranteeing your failure with any BI tool.

I have also previously contrasted my opinion with the surprisingly large number of discussion threads on LinkedIn that have as a title some variant of “Please, please, please, please, please tell me which is the best BI tool”. I worry about people making quite significant purchasing decisions based on replies posted in an internet forum, but that is perhaps a topic for another day. The particular failure I wanted to highlight is of people posting on these types of thread who work for Big BI Corporation Inc. Of course everyone is entitled to their opinion, but I am not sure that many readers would be swayed by:

I highly recommend Object Explorer Studio+ for all your BI needs

– Joe Blogs

Particularly where one click reveals that Joe Blogs is either employed by the owners of OES+ or a consultant whose company seems to exclusively do OES+ implementations. I hate to single out one vendor, but a particularly egregious reply to one of these “Which BI Tool?” threads that I saw recently consisted of one word:

Microsoft

– Jimmy Blogs

As I say, on the very same thread there were examples of employees of many other big and small BI vendors doing just the same, but most of them at least provided more than one word. In the cause of balance, the same thread also contained some thoughts along the lines of:

I can heartily recommend Oracle BI, OBIEE+ is great because [sales pitch deleted]. If you would like to know more drop me a line at jeff.blogs@oracle.com

– Jeff Blogs

I still wonder whether Jeff got any e-mails. At least he flagged his connection with Oracle, I don’t recall many other vendor employees being honest enough to do the same.

Lest I be accused of bias there were also not too dissimilar postings from people strongly associated with SAP, IBM, QlikTech, Pentaho and a sprinkling of BI start-ups. I should perhaps also note that SAS was not a culprit (at least to date), but then maybe this was because the question was about BI, something they abjure. Microstrategy was also honourably notable for its lack of replies containing naive self-promotion, but perhaps this was simply an oversight.

The above rather bizarre behaviour leads to two questions:

  1. Why do the people making these types of posting think that they will be taken seriously?
  2. Why do the vendors themselves not offer better guidance to their employees about avoiding crass and counter-productive social media advertising of a sort that is more likely to tarnish reputations than enhance sales?

Maybe here again we have an issue of social media maturity. Many people are perhaps struggling as much to get their message across effectively as they did with say the advent of television advertising.

My learning here is that I should curb my rather obsessive compulsion to “out” vendors promoting their own products under the guise of neutral advice-giving.

[not sure that I am going to take much notice of this one however]
 
 
Success – The Accidental Search Engine Optimiser

After covering three of my own failures and one of the BI vendor community (though I am sure the phenomenon is not restricted to BI or even technology vendors), I will close with one of my successes, albeit an unintentional one. I noticed a strange result the other day when looking at the following (I was actually looking for something else believe it or not):

Business Intelligence Expert

I believe that my elevated ranking is probably correlated to recent changes in Google’s algorithms that take greater account of social media. Certainly I don’t recall placing on the first page for any Google search before, let alone rank #1. I suppose that I might have a degree of technical satisfaction if this was as the result of months of assiduous search engine optimisation. However the truth is that the result appears to be the unintended by-product of doing lots of things that I wanted to do anyway, like writing about topics I am interested in and trying to engage with a wide group of people in a number of different ways. In a sense the fact that this achievement was accidental (or at least collateral) makes it more pleasing. Maybe the secret to Social Media success is simply to not worry about it and just get on with expressing yourself.

My learning here is that providing content that is of interest to your target audience and being clear about who you are and what you do is going to be an approach that trumps any more mechanistic approach to SEO.
 
 
Closing thoughts

I believe that I have leant something from my three failures above (and that vendors should learn something from the fourth), but the single success encourages me to persevere. My aim in sharing these experiences is to hopefully also similarly encourage other Social Media ingénues like myself. I hope that I have at least partially achieved this.
 

Consider including…

Gmail logo

Let me get something out of the way straight up. I am a fan of Google. Are their services and products flawless? Probably not. Did they live up to their stated objective of “do no evil”? Well I guess the Chinese difficulties didn’t exactly paint them in the best light, nevertheless I can think of less savoury technology companies. On the plus side, I have used Google’s services and, in particular, their cloud-based e-mail – Gmail – for years and been very happy with them. If I explain that my smart phone is a Nexus One, you will probably get the general idea.

Gmail fail?
Image edited and truncated to fit page - click for full version

However, Google have introduced a “feature” into Gmail which leads me to question what on earth they were thinking. This is the “Consider including” function. When you type an e-mail, Gmail comes up with a list of people that you may like to also copy it to. Let’s pause and just think about this. You are writing an e-mail, generally the first thing that you do is to type in the address of the person (or people) you are writing to. Gmail has a useful feature that scans your previous mails, so typing “Pe” will bring up “Peter Thomas” as an option. So far so good. But then, based solely on this first e-mail entered (not even on the subject), the bar highlighted in pale yellow appears above with a list of people that you may consider including on the mail.

Google’s algorithms may be great at figuring out which context-based ads to display alongside the advertising-supported Gmail (though I must admit to never having clicked on any of these and to generally mentally filtering them out), but how does an algorithm know better than me who I want to send an e-mail to? I suppose we could give the geniuses at Google the benefit of the doubt, maybe they do know.

Sadly empirical evidence is that the software doesn’t have a clue. In the example above, the contacts “J”, “L” and “R” (the names have been anonymised to protect those irrelevant to the context) have nothing whatsoever to do with the e-mail recipient (again anonymised) that I started writing. Aside from perhaps once being cc’ed in an e-mail sent to the person whose address I typed in, they have no relation to either the intended recipient, or indeed to each other. As to content, at this point there isn’t any, so it is anyone’s guess how Google generates the list; an even more worrying question is why do they?

Not only does the feature fail to work, it is also totally asinine. It might make some sense for say Facebook to suggest people with whom you might want to share a link. However, there are people who you might e-mail twice a year for very specific purposes, that still get suggested in a “Consider including”. Google plainly doesn’t know better than me to whom I actually want to send an e-mail. A worry is that a stray click and a lack of attention could send an e-mail to someone who is not intended to see it. Given the fact that many small businesses and sole-trader consultants rely on Gmail, then – in extremis – this could lead to commercially sensitive (or indeed personally private) information being sent to the wrong person. The feature is clearly ill-advised and – worst of all – you cannot (at present) turn it off.

In searching (via Google) for tips on how to get rid of this truly abysmal piece of functionality I came across two things: screeds of people just like me asking what Google was thinking and the an article entitled: Gmail’s Most Ridiculous, Idiotic, Intrusive, Useless Feature Ever by Zoli Erdos, which covers the problems and potential implications of “Consider including” in more depth. Here is a pithy quote:

I’ve never thought the day would come I would write the words utterly ridiculous, iditiotic, intrusive, with absolute certainly about a Google feature

This “feature” is bad enough to have merited me writing to Google asking them to remove it, or at least make it optional. Their support forums are full of people saying the same. It will be interesting to see whether or not they listen.

[Disclosure: I have more than one Gmail account and also use Google apps from time to time, as stated above, I also use Feedburner and have a Google smart phone. Other than this I have no commercial relationship with Google and have never bought or recommended their services in a business context]
 

Illuminating the darkness

Recrudescence

My partner was kind enough to buy me an Amazon Kindle for Christmas and I have enjoyed using it. Yes there were the problems with them registering me to Amazon.com, rather than Amazon.co.uk (thereby incurring foreign transaction charges). And yes they didn’t cancel a trial Economist subscription I took out on the former when I was transferred to the latter. However, these issues were sorted out and money refunded.

I suppose I had the same initial reaction as many people; that they had left a sticker covering the screen, which was intended to demonstrate what the display looked like. After failing to peal it off (thankfully not too energetically) I realised that the screen was actually that clear and that different from a “normal” computer display (I was thinking smart ‘phone or laptop). I am writing this post on one of my many laptops, the screen is OK, but the Kindle is much easier on the eye and pretty close to a high-quality printed page. Suffice it to say that I downloaded new copies of several of my favourite books to it with the prospect of re-engaging with them at my leisure.

But enough of me singing the general praises of the device, I have discovered a particular benefit. While this may well be realised by other people, it is of particular pertinence to devotees of the works of Joseph Conrad.

Joseph Conrad

As one of the undisputed giants of English prose, it is rather ironic that English itself was either Conrad’s fifth, or sixth, language (chronologically: Polish; Russian – though he later, perhaps understandably given the turbulence of the times, repudiated this as a language; French; Latin; German; and – finally, when he was in his twenties, English). I have greatly appreciated his work, since first reading Heart of Darkness. I won’t attempt to offer a literary appreciation of his genius and leave this to others with greater talents in that area. However, despite coming late to the English tongue, Conrad was a master of it and had an amazing vocabulary.

An indispensable companion to Conrad's works

I generally view myself as being reasonably erudite (less charitably I have been accused of having swallowed a thesaurus), but used to have to keep a dictionary at hand when reading Conrad; either that or try to impute meaning from context (probably getting it wrong more times that I care to admit). In some ways, my own limitations slightly diluted my enjoyment of reading. It is a bit distracting to put down one book, pick up a dictionary, look up a word and then revert to the original tome (it was even more complicated as a child reading Jules Verne’s 20,000 Leagues under the Sea with both a dictionary and gazetteer to hand!).

Incidentally my fondness of Conrad led to my one contribution to the field of science. I established my result after extensive fieldwork involving Nostromo and a daily commute. Thomas’ Theorem is as follows:

While this feat is more than achievable with the works of other authors, it is impossible to read Conrad on the Tube.

However, the Kindle is a joy in this respect as you can look up words using the built in dictionary, quickly, easily and without disturbing the thread of the narrative too much. This has got me out of my rather lazy habit of assuming that I sort of know what a word means and thereby given me a few surprises. Based on the the initial illustration above, for example, I had to modify my understanding of recrudescence!

Of course this means that I may have to re-evaluate whether Thomas’ Theorem holds in all conditions. Perhaps a sub-clause excluding the use of a Kindle is required. I will report back…
 


 
This is not the first time that Conrad has appeared in the pages of this blog, I had the temerity to also reference him in Aphorism of the Week some time ago.