Aug
5
The Future is Already Past
Filed Under B2B, Big Data, Blog, data analytics, eLearning, Industry Analysis, internet, mobile content, online advertising, Publishing, Uncategorized, Workflow | Leave a Comment
Is there a better instance of “speed of change” than that just when you are instancing something as a prime example of future change, you next read of it as history? We keep reminding ourselves that change is running at faster rates than we imagined, or than we experienced in childhood or at other times. My usual counter to this has been to point out how slowly things happen. Between announcement and implementation whole decades seem to yawn, so that when the signalled change does take place, we experience something like dejas vu. Yet I do share the “speed of change” experience myself, and last week, just as I was writing about the automation of aspects of building design and construction, I started to tell a friend, standing on my soapbox as a former farming person, about the developments one could forecast in agriculture. “And so”, I recall ending my peroration,” it is plain to see that the tractor is a robot waiting to happen…”
Well, he was kind enough to wait an hour or so before sending me the article about research at John Deere, and while looking at that I came across Jaybridge Robotics (www.jaybridge.com/news) and their work with Kinze to create Kinze Autonomy, the driverless tractor. This development is capable of performing a complete harvesting workflow in a geo-location-based systems environment which was launched in Iowa on July 29th. My friend kindly wrote “Your prediction was History – but remind me why I needed to know…” And there lies the problem: we need to know how our users are likely to adapt to change at the same time that they make that decision. In an information market where corporate planning times have diminished from a standard five years when I entered work, to a budget plus a forecast it is becoming peculiarly hard to negotiate the hair-pin bends of market change while keeping an eye on the horizon. I even have one colleague who does two six month budgets a year and still complains how hard it is to cope with changing circumstances.
Last Friday, Sonoma issued their interim results. How often have you read a media company boss like Harri-Pekka Kaukonen, President and CEO, say things like this:
“Learning’s solid performance continued in the second quarter whereas
structural changes accelerated in consumer media.
Advertising markets in Sanoma’s main operating countries continued to be
depressed. The likelihood of clearly improving market conditions in the second
half of the year is estimated to be low. In addition, circulation sales
continue to be under pressure, impacting our sales and profitability”
For the past five years we could have produced automated statements to this effect for every media player throughout Europe and North America. And while I am sure that the wise folk at Sanoma have new strategies to roll out in due course, I find it deeply disturbing that much of the consumer print media marketplace seems to have been sleepwalking for the last five years, and for the five years before that when structural change began. So do we really have a ten year reaction time to fundamental change? Lets move forward quickly to James Dolan, CEO of Cablevision, the fifth largest cable player in the US, as quoted this morning by the Wall Street Journal (http://onlinr.wsj.com: “The Future of Cable might not include TV”). Now here is someone who can imagine the impact of structural change when he senses it. In the wars between programme makers, internet distributors and video channels like Netflix he seems determined to be prepared, even if he is not a television player in the future. Allocating capital expenditures of $1.1 billion last year to upgrading his network, he is determined to work as a broadband distributor, offering higher speeds, greater outdoor wifi access and cloud-based storage allowing users the ability to record up to ten items at the same time. He notes that his kids (he has six boys from 6 to 26) use Netflix on Cablevision Broadband. One of his investors remarks” Jim has a multi-generational view, a longer term view”. Some people see change, and are able to think about the unthinkable.
Sometimes the best way to envision the future is to watch other people betting on it. This is why the start-up markets are so interesting, to me at least, and why watching the drift of interest in venture capital-backed plays can be so useful. I have to believe that setting up VC-style growth greenhouses makes sense (as Macmillan Education and Science, and a number of others have grasped). I noted that some now believe that the tech development impetus in Europe has moved from London to Berlin (http://newsle.com/article/0/86896557/), but where it is does not really matter. We all have to go there and see what is happening. In the UK there is a traditional gap between university science park developments and tech development zones like London’s Shoreditch, so I was pleased to see Elsevier sponsoring the Global University Venturing Summit (http://www.globaluniversityventuring.com/pages/global-university-venturing-summit-brussels-oct-16th.html) which takes place in October this year. If you want to smell the future, get into meetings like this, stop thinking about what has changed and start thinking about what will.
Jun
14
Seven Starters in Data Analytics
Filed Under B2B, Big Data, Blog, data analytics, Education, Financial services, healthcare, Industry Analysis, internet, mobile content, news media, online advertising, Publishing, Search, semantic web, social media, STM, Uncategorized, Workflow | 1 Comment
Phil Cotter’s comment on last week’s post here really got me going. Now that I know that suicide bombers max their credit cards before setting off to do the deed I somehow feel a gathering sympathy for the security services. So the starting point is 5 million up-to-the-limit cards? We need to funnel cash into predictive analytics urgently if anything we do is to show better results than airport security (to begin from a very low measure indeed). So I began to look for guidelines in the use and development of predictive analytics, thinking that while we wait for terrorist solutions we might at least get a better handle on marketing. I am surprized and impressed by how much good thinking there is available, so in the spirit of a series of blogs last year (Big Data: Six of the Best) here are some starting points on innovative analytics players who all have resonance for those of us who work in publishing, information and media markets. And a warning: the specialized media in these fields all seem to have lists of favoured start-ups enttitled “50 Best players in Data Analytics”, so I am guilty of scratching lightly at the start-up surface here.
In the same spirit of self-denial that drives me to abstain from a love of eating croissants for breakfast, I have also decided to stop using the expression “B** D***”. I am so depressed by publishers asking what it means, and then finding that, because of “definition creep” or “meaning drift”, I have defined it differently from everyone else, including my own last attempted definition, that I am going to cease the usage until the term dies a natural, or gets limited to one sphere of activity. So Data Analytics is my new string bag, and Predictive Analytics is the first field of relevant activity to be placed inside it. Or do I mean Predictive behaviour analytics?
I was very impressed by analysts studying our use of electricity (http://www.datasciencecentral.com/profiles/blogs/want-to-predict-human-behavior-use-these-6-lessons-based-on-data-). Since the work throws up some lessons which we should bear in mind as we push predictive analytics into advertising and marketing. The thought that it was easier to influence human populations through peer pressure and an appeal to altruism, as against offers of “two for one”, cash bonuses and discounts is clearly true, yet our behaviour in marketing and advertising demonstrates that we behave as if the opposite was the case. The emphasis on knowing the industry context – all analytics are contextualised – and the thought that, even today, we tend to try to make the analysis work on insufficient data, are both notions that ring true for me. We need as well to develop some scientific rigour around this type of work, using good scientific method to develop and disprove working hypotheses. Discerning the signal from the noise, like “never stop improving”, are vital, as well as being hard to do. I ended this investigation thinking that even as the science was young, the attitudes of users as customers were even more immature. If we are to get good results we have to school ourselves to ask the right questions – and know which of our expectations are least likely to be met.
Which brings me to the people we should be asking. Amongst the sites and companies that I looked at, many were devoted from differing angles to marketing and advertising. But many took such differing approaches that you could imagine using several in different but aligned contexts. Take a look for example at DataSift (www.datasift.com). It now claims some 70% accuracy (this is a high number) in sentiment tracking, creating an effective toolset for interpreting social data. Here is the answer to those many publishers in the last year who have asked me “what is social media data for, once you have harvested it?” Yet this is completely different from something like SumAll (https://sumall.com), which is a marketeers toolset for data visualization, enabling users to detct and dsiplay the patterns that analysis creates in the data. Then again, marketing people will find MapR (www.mapr.com) fascinating, as a set of tools to support pricing decisions and develop customer experience analytics. Over at Rocket Fuel Inc (www.rocketfuel.com) you can see artificial intelligence being applied to digital advertising. As a great believer in sponsorship, I found their Sponsorship Booster modelling impressive. This player in predictive modelling has venture capital support from a range of players, from Summit to Nokia.
When the data is flowing in real time, different analytical tools are called for, and MemSQL (www.memsql.com) has customers as diverse as Zynga, and Credit Suisse and Morgan Stanley to prove it. Zoomdata (www.zoomdata.com) is a wonderful contextualization environment allowing users to connect data, stream it, visualize it and give end-user access to it – on the fly. This is technology which really could have a transformative effect on the way that you interface your content to end users, and you can demo it on the Data Palette on the site. And finally, do you have enough of the right data? Or does some government office somewhere have data that could immensely improve your results? Check it on Enigma (press.enigma.io), the self-styled “Google of Public Data”, a discovery tool which could change radically product offerings throughout the industry. Perhaps it is significent that the New York Times is an investor here.
So, for the publisher who has built the platform and integrated search, and perhaps begun to develop some custom tools, there is a very heartening message in all of this. A prolific tool set industry is growing up around you at enormous pace, and if these seven culled from the data industry long lists are anything to judge by, the move from commoditized data increasingly free on the network to higher levels of value add which preserve customer retention and enhance brand are well within our grasp.
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