Aug
3
Learning a lesson from Jana and Teachers?
Filed Under B2B, Blog, Cengage, Education, eLearning, Financial services, Industry Analysis, internet, Publishing, Thomson, Uncategorized, Workflow | Leave a Comment
Activist investors from hedge fund Jana and the Ontario Teachers Pension Fund (“Teachers”) have bought 5.2% of McGraw-Hill Corporation with the avowed intent of forcing the division of the company into a financial services company and an educational/B2B company.
When the activists arrive, they always show an immediate profit: this announcement triggered a sharp rise in McGraw’s share price (http://dealbook.nytimes.com/2011/08/02/mcgraw-hill-shares-rise-after-activist-stake/), and a great deal more interest in what many media market investors have long regarded as an unspectacular mid-market performer. Disincentives in large media players have always included unified Chairman/CEO roles, and divided equity classes with limitations on voting shares. Incentives have always included the thought of break-up in conditions where the sum of the parts may be found to be greater than the value of the whole. McGraw now faces this scenario, and has known for at least a year that it was likely. Hence the strategic portfolio review launched last Fall, and the creation of a McGraw-Hill Financial Services division. But now that the real question has been asked by Teachers and Jana, how can management react without appearing to be running the company on the agenda of a powerful but still small shareholder?
Over the last decade the great principle in developing B2B assets has always been Portfolio. Sir Crispin Davies practised this at Reed, building a four legged table in the sure and certain knowledge that not all markets would go bad at once. Problems only arose when the education leg fell off, and the last recession provided his successors with the assurance that all markets can go wrong at once. Thomson Reuters’ reaction was different; move away from Portfolio into Wide Vertical – a huge construction from law and regulation to financial services and transactions where a broad base of clients can be inter-related and cross sold, and where service and content assets can be optimized. Will it work? Well, its work in progress and good progress is being made. And the not wanted on board assets like Healthcare are on the block.
These are options. But what about the McGraw-Hill asset base? What are its strengths and where does it dominate? The first thing to say is that, in comparative terms, great changes have taken place in the past few years which have surprised observers of this often fiercely conservative company. The sale of BusinessWeek and the acquisition of J D Power are cases in point. But in terms of the wholesale creation of the group asset base in digital first terms? Progress is there, but is seen by outsiders as slow and patchy, part of niche and product strategies rather than the platform and standards driven thinking of some of the market leaders. There is no doubting the pre-eminence of Standard and Poor’s, however, and the activists, by attacking at this point, may be more likely to set up a bidding war for this (Hearst are already in Fitch, Bloomberg and Thomson Reuters lead these markets) than create a successful IPO.
What about the other assets? B2B has huge positions of strength, but they are all under pressure. McGraw have long dominated construction, but now finds that while it did all the right things to get Sweets and FW Dodds into workflow networks, recession (and an ill-judged law suit with Reed Construction) has lost it concentration and time to market. Alongside it, Platts rested on its laurels for too long as the leader in oil price indexation (losing market position with Aramco to the tiny British player Argus Media) and is now rushing to catch up in other asset classes (its latest buy was the Steel Index) and broadening a portfolio which should be doing very well at this time. One hopes that Platts is seen as much as anything as a part of financial services (who bought New Energy Finance and Point Carbon? Bloomberg and Reuters), but probably it is seen as the counterbalance to construction and the aerospace/aviation holdings (who lost out to Reed in bidding for Ascend Worldwide), both of whom continue to require careful nursing to bring their brand strengths into full recognition in the digitally networked marketplaces in which they exist.
But you cannot invest in everything at once. McGraw-Hill Education is a case in point. This side of the company created digital firsts 15 years ago (think of Primis) but then was allowed to graze as a cash cow when other priorities in the portfolio became more important. With Pearson now emerging as the unassailably dominant player in North American education, but the whole market suffering a hangover now that school spending cuts from 2009 are hitting spending with full force, McGraw-Hill has nowhere to go. Its overseas holdings are tiny, and mostly in Higher Education: Pearson is now getting considerable and sustaining returns from non-US markets which have taken a decade to create. Meanwhile McGraw seem at last, after constant strategic re-appraisal and constant changes of CEO (to the point where they are now run by the former veteran group CFO) to be heading in a digital first direction, launching really interesting environments like Campus and ensuring that all of their content is digital and licenced from the very beginning. Is this too late? We can only tell when markets recover, but outsiders might well think that US education was over-published. How things will consolidate (the assets are Harcourt Houghton Mifflin, McGraw and Kaplan) may be one of the outcomes of the Jana move.
McGraw’s latest announcements indicate 11% growth in income in the second quarter but a 5% drop in education revenues. Neither of these is in the least surprising, and may indicate some signs of recovery. But now the question has been asked, every piece of emerging evidence will be used to support a break-up theory. And now two points of caution for those prone to jump to conclusions: Teachers is not the same as the Ontario Municipal workers pension fund which co-owns Cengage with Apax, and the David McGraw who is CFO of Teachers is …no relation. Now that the News of the World is closed and hacking has ceased you will just have to take my word for it!
Jul
29
Intelligent Life in Big Data
Filed Under B2B, Blog, data protection, Financial services, healthcare, Industry Analysis, internet, privacy, Search, semantic web, Uncategorized, Workflow | 1 Comment
When a movement in this sector gets a name, then it gets momentum. The classic is Web 2.0; until Tim O’Reilly invented it, no one knew what the the trends they had been following for years was called. Similarly Big Data: now we can see it in the room we know what it is for and can approach it purposefully. And we know it is an elephant in this room, for no better reason than the fact that Doug Cutting called his management and sorting system for large, various, distributed, structured and unstructured data Hadoop – after his small boy’s stuffed elephant. And this open source environment, now commercialized by Yahoo, who developed it over the previous five years on top of Google’s open source MapReduce environment, is officially named HortonWorks, in tribute to the elephant from Dr Seuss who Hadoop really was. With me so far? Ten years of development since the early years of Google, resulting in lots of ways to agglomerate, cross search and analyse very large collections of data of various types. Two elephants in the room (only really one), and it is Big Search that is leading the charge on Big Data.
So what is Big Data? Apparently, data at such a scale that its very size is the first problem encountered in handling it. And why has it become an issue? Mostly because we want to distill real intelligence from searching vast tracks of stuff, despite its configuration, but we do not necessarily want to go to the massive expense of putting it all together in one place with common structures and metadata – or ownership prevents us from doing this even if we could afford it. We have spent a decade in refining and acquiring intelligent data mining tools (the purchase of ClearForest by Reuters, as it was then, first alerted me to the implications of this trend 5 years ago). Now we have to mine and extract, using our tools and inference rules and advanced taxonomic structures to find meaning where it could not be seen before. So in one sense Big Data is like reprocessing spoil heaps from primary mining operations: we had an original purpose in assembling discreet collections of data and using them for specific purposes. Now we are going to reprocess everything together to discover fresh relationships between data elements.
What is very new about that? Nothing really. Even in this blog we discussed (https://www.davidworlock.com/2010/11/here-be-giants/) the Lexis insurance solution for risk management. We did it in workflow terms, but clearly what this is about is cross-searching and analysing data connections, where the US government files, insurer’s own client records, Experian’s data sets, and whatever Lexis has in Choicepoint and its own huge media archive, are elements in conjecturing new intelligence from well-used data content. And it should be no surprise to see Lexis launching its own open source competitor to all those elephants, blandly named Lexis HPCC.
And they are right so to do. For the pace is quickening and all around us people who can count to five are beginning to realize what the dramatic effects of adding three data sources together might be. July began with WPP launching a new company called Xaxis (http://www.xaxis.com/uk/). This operation will pool social networking content, mobile phone and interactive TV data with purchasing and financial services content with geolocational and demographic content. Most of this is readily available without breaking even European data regulations (though it will force a number of players to re-inforce their opt-in provisos). Coverage will be widespread in Europe, North America and Australasia. The initial target is 500 million individuals, including the entire population of the UK. The objective is better ad targetting; “Xaxis streamlines and improves advertisers ability to directly target specific audiences, at scale and at lower cost than any other audience -buying solution” says its CEO. By the end of this month 13 British MPs had signed a motion opposing the venture on privacy grounds (maybe they thought of it as the poor man’s phone hacking!).
And by the end of the month Google had announced a new collaboration with SAP (http://www.sap.com/about-sap/newsroom/press-releases/press.epx?pressid=17358) to accomplish “the intuitive overlay of Enterprize data onto maps to Fuel Better Business Decisions”. SAP is enhancing its analytics packages to deal with content needed to populate locational display: the imagined scenarios here are hardly revolutionary but the impact is immense. SAP envisage telco players analysing dropped calls to locate a faulty tower, or doing risk management for mortgagers, or overlaying census data. DMGT’s revolutionary environmental risk search engine Landmark was doing this to historical land use data 15 years ago. What has changed is speed to solution, scale of operation, and availability of data filing engines, data discovery schema, and advanced analytics leading to quicker and cheaper solutions.
In one sense these moves link to this blogs perennial concern for workflow and the way content is used within it and within corporate and commercial life. In another it pushes forward the debate on Linked Data and the world of semantic analysis that we are now approaching. But my conclusion in the meanwhile is that while Big Data is a typically faddish information market concern, it should be very clearly within the ambit of each of us who looks to understand the way in which information services and their user relevance is beginning to unfold. As we go along, we shall rediscover that data has many forms, and mostly we are only dealing at present with “people and places” information. Evidential data, as in science research, poses other challenges. Workflow concentrations, as Thomson Reuters are currently building into their GRC environments, raise still more issues about relationships. At the moment we should say welcome to Big Data as a concept that needed to surface, while not losing sight of its antecedents and the lessons they teach.
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