Oct

1

PlanS: Does Publishing have a Plan B?

Filed Under Artificial intelligence, Big Data, Blog, data analytics, Industry Analysis, internet, machine learning, Publishing, Reed Elsevier, semantic web, STM, Workflow | Leave a Comment

 

Plan S was greeted with widespread and intense… silence in the publishing industry. Part of the reaction was governed by the need for rapid analysis to see what it might actually mean. Part of it was sheer disbelief – are taxpayer funded research institutions going to be allowed to create policy which they think is in the interests of science, not business? Listening to a lobbyist tackling an industry minister on this topic this week, I had a distinct impression that if the perception of funders is that PlanS is good for science, it will be very hard for commercial interests to change the the climate of opinion. Nor, I think, will the argument that I have seen from Joe Esposito and others that making it a condition of funding that researchers publish in non-hybrid journals is a major attack on freedom of expression and scholarly independence carry much weight in Europe, even if it has more resonance in the USA. A funding body that says it is using taxpayers money responsibly when it ensures that the outcomes of research are known to the greatest number of taxpayers who funded it and at the least additional cost surely trumps (sorry about that) the commercial sector’s hand. While there must be scope for arguing funders into a slower pace – the plan to have this fully effected by January 2020 may be in place as much as anything to concentrate people’s minds – I have little doubt that the attack on hybrid journals is real and will succeed unless direct political action stops it. This is not however an issue that creates electoral movement, and the political agendas of Europe are pretty full of other things. 

So what does it mean if PlanS succeeds? Matthew Walker, the very knowledgeable analyst at Credit Suisse, points out that the potential effects on two quoted companies that he follows closely are limited. At RELX and at Informa, 4% and 2.5% of gross revenues derive from UK/Europe journal subscription revenues. He calculates that at the group operating profit level, the impact could be 5% and 2.5% respectively. The fact that share prices in both companies have fallen 10% since the summer (H1), and that these falls discount this effect somewhat is the shorter. The longer term thought of the EU with $14 bn in research funds following PlanS, as well as Wellcome and Gates, sharpens the impact. Even if we concede that it will take longer and the big players will find a degree of mitigation, the most immediate effects will be felt not where PlanS intended, but amongst scholarly societies and institutions. For many of these this could be a disaster. The enlightened few , like the Royal Society of Chemistry, are out there promulgating new business models like Read and Publish. They scored a notable success outside of the UK by engaging MIT in this last month. But this is still hybridity by another name. If you are a scholarly society and the whole organisational structure is based around funding derived from journal subscription revenues, PlanS is a threat of potential extinction. 

And some of the other PlanS conditions have equally serious implications. The Hybrido journals are not just a target because of widespread fears that they are (often unintentionally) “double dipping” – charging APCs and taking subscriptions which accidentally cover the same content during embargo periods. By removing embargo periods and demanding immediate release of content under CC BY licence, PlanS removes the “need to subscribe “requirement, while by threatening to cap APCs by reducing what it will pay as part of research grants, funders could end up in control of publishing margins for a wide sector of the industry. Capping APCs will be tough, both in terms of co-ordination and in terms of content – the increasing need to include data, graphics and video in research content widens the range of charges and makes uniformity across disciplines difficult. Some authors will lose prestige, but few will reject funding because of it. 

There will be winners too. Born-OA players like Hindawi and Frontier, and, since all of this is said to extend to books in time, new players in monograph publishing like Knowledge Unlatched. Apart from buying Gold OA journals quickly (availability strictly limited), what are STM publishers going to do? It is one thing saying that it will be slower to take effect than people think , or other parts of the world are different – it is all true – and it is another to say that there will be more mega journals, or that the industry will condense as societies cash in their journal annuity revenues – or there is only space for two big players (a long held belief of my own roundly rejected by most!), but it is harder to turn this into concrete action unless you place it in the context of the current trajectory of change. 

The STM publishing business has known for a decade that the journal door is slowly closing. Those publishers at Frankfurt Book Fair  next week who are not gripping the bar of the Hessicher Hof with whitening knuckles and asking for less water in their Scotch will be hurrying around to the UNSILO stand (Hall 4.2 L 86) to see if modelling manuscript evaluation in AI really works. Ever since publishers realised that their defensive moat of peer review was breached in a network society by the ability of evaluation to be a continuing process from funding to whenever, important publishers have been investing in scholarly workflow, led by Elsevier and Clarivate and Digital Sciences, in oversight of continuous review, in research support services, in improving discovery, in creating discipline mapping and bibliographical tools (Wizdom.ai), or in creating the dissemination and impact planning (Grow Kudos) that funders want to bake in to research approval and planning. The industry is shifting, and PlanS, by speeding change, may be doing everyone a favour. 

Sep

27

RPA: Generating Workflow and Automating Profits?

Filed Under Artificial intelligence, B2B, Big Data, Blog, data analytics, Financial services, Industry Analysis, internet, machine learning, RPA, semantic web, Uncategorized, Workflow | Leave a Comment

RPA  Robotic Process Automation. The new target of the Golden Swarm of software VC investors. Sometimes misleadingly known in more refined versions as IPA (Intelligent Process Automation, not warm English beer). 

In my view the central strategic question for anyone who owns or collects and manages news and information, educational and professional content, prices or market data relating to business verticals, and commodities is now simply this: when I license data to process automation, what is my expectation of the life of that annuity revenue stream, and how fast do my users connections and market requirement sensitivity decay? Over the past five years we have seen an industry predicated on the automation of mundane clerical work take huge strides into high value workflows. Any doubt around this thought can be clarified by looking at the speed of advance of automated contract construction in the legal services market. The ability to create systems that assemble precedents, check due diligence, create drafts and amend them is as impressive as it is widespread. The fact that many law firms charge as much for signing off on the results as they did for the original work says more for their margins than it does for the process. But that message is the clearest of all: automating process software is expensive, but eventually does wonders for your margins in a world where revenue growth is hard to come by for many. 

And, at least initially, RPA systems are greedy eaters of content. Some early players, like Aravo Solutions, became important middlemen for information companies like Thomson Reuters and Wolters Kluwer in creating custom automation for governance, risk and compliance systems. Their successors, productising the workflow market, have been equally enthusiastic about licensing premium content, but unlike their custom predecessors, while they have enjoyed the branded value of the starter content, they have also found that this is less important over time. If the solution works effectively and reduces headcount, that seems to be enough. And over time, systems can become self-sufficient in terms of content, often updating information online or finding open data solutions to diminish licensing costs. 

The ten companies in this sector (which included Century Tech as an example of learning as a workflow) that I started to follow three years ago have matured rapidly. Three have become clear market leaders in the past 6 months. Automation Anywhere and UiPath in the US, together with Blue Prism in Europe have begun, from an admittedly low start points, to clock up 100-500%+ annualised revenue growth rates, But a note of caution is needed, and was importantly provided by Dan McCrum writing in the FT on 13 September (https://ftalphaville.ft.com/2018/09/13/1536811200000/The-improbably-profitable–loss-making-Blue-Prism/). He demonstrated that by writing all of its sales costs ( mostly through third parties) to fixed administration costs it was able to claim close to 100%  ebitda and score a 1.7 billion pound valuation on the London AIM market while revenues were 38 m pounds and losses are still building. UiPath (Revenues $100m, revenue growth 500%, valuation $1 bn) and Automation Anywhere (valuation $1.8 bn) follow a similar trajectory. 

All content markets are looking at a future where machines use more content than people, This makes it more important than ever that information is sourced in ways that can be verified, audited, validated and scored. This is not just an “alternative facts” or “fake news” issue – it is about trust in the probity of infrastructures we will have to rely upon. Content owners need to be able to sell trust with content to stay in place in the machine age, at least until we know where the trusted machines are kept. In the meanwhile it will be interesting to see which information, data and analytics companies acquire one of these new software players, or which of these new high value players uses the leverage of that valuation to move on a branded and trusted information source.

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