What Mobility Is Not
7Capture systems have to work, and work together
I work with Richard. But I genuinly enjoy reading his take on things. Even something as “exciting” as capture. Here’s a taste:
As you probably know if you’ve been dealing with complex systems (like production capture and workflow that’s integrated with downstream business systems), it’s not enough that the technologies have to “work”. Sure, the scanner and capture software and OCR engines and imaging or document management systems have to “work” – but they also have to worktogether. The capture software has to run the scanners and other channels, and the OCR engines have to work with those things, and they all have to integrate properly with the ECM systems and downstream business systems and workflow.
But even that’s not good enough! The whole contraption has to work cost-effectively. Which is to say it has to save you money, or make you money. This is an extension about what you probably already know about when to do OCR, versus when to just hand-key the data from documents or forms: Sometimes you have too many errors, and QA and error correction makes OCR inefficient. It’s just more efficient to do it manually!
CMIS Basics
I’ll admit that I’m a little ignorant regarding the CMIS standards and what they really mean. Actually, its not because I’m stupid, I just really didn’t care. But I came across an article by Stefan Waldhauser on John Mancini’s Digital Archive blog that got to the details I cared about quickly without getting super nerdy about the code details.
First a little history:
Back in 2008 Microsoft, IBM and EMC drafted an initial proposal for an ECM interface specification. This proposed draft specification was shared with Alfresco, Open Text, Oracle and SAP, later refined by the CMIS TC (Technical Committee) and became an official OASIS standard in May 2010. Now the leading ECM vendors face a difficult situation: the point of no return is passed; now they have to support the new open standard although they know that the usage of CMIS will weaken their relationship with existing enterprise customers.
Uh, is anything happening because of it? Yes actually.
only 12 months after the initial release of the CMIS standard there are more than 50 CMIS implementations available in the marketplace. However, it is more important that every single major player not only announced but also delivered a CMIS-compliant version of its ECM repository.
But CMIS isn’t going to give you the abilities of a native API.
IBM, OpenText or EMC Documentum deliver a lot of functionality in their native API’s which is not covered by the actual CMIS 1.0 specification. But all the core features needed for comprehensive document management solutions are already included.
What is Content?
Lately one of my pet concerns about the content management industry has been with the idea that we are managing content. I can’t put my finger exactly on why the word CONTENT bothers me so much. But partly it has to do with the fact that no one sets out to create ”content”. Instead Content seems to be an abstraction forced upon the creations of workers that immediately undervalues it.
Whilst skimming the web I found an essay by Ian Bogost, Professor at The Georgia Institute of Technology. I am probably pulling these quotes out in extreme violence to the original intent. But I thought they were interesting for a community that focuses entirely on digital archives. Especially interesting is how these quotes point to the metaphors we use to describe ECM systems.
When we construct something like a digital archive, we do so thanks to an idealism underwritten by the linguistic turn. Archives house documents, and documents hold language, and language bears meaning. The rest we don’t even think to think about, but toss away like citrus rinds.
and later
Consider, for example, the future archives being built today “in the cloud” on services like Gmail and Twitter. These are not documents, but entanglements of database records, air conditioners, end-user license agreements, electricity grids, backup tape automators, venture capital, password reminder security questions, browser standards, and much more. When we call things digital, just as when we call things linguistic, we are always only partly right. Instead of file systems, we ought seek other metaphors. Perhaps future archives will be more like bestiaries or like Wal-Marts than they are like libraries.
Enterprise Search is not Web Search
Gabor Fari’s explanation of the difference between enterprise search and web search (bolded below) was really helpful for me.
There are some great search tools out there. But search tools can only find what is ‘indexable’ (and a bit more, via combining it with text mining, and semantic approaches). But this this is still not enough. I strongly believe that what is needed is to track all metadata on the object level across the enterprise, and to combine this with search results, in a faceted result set. Why is this important? Because Enterprise Search is not Web Search! We are not looking for Web pages, and ranking algorithms based on how many hyperlinks point to Site! We are looking for documents, and we often need to find every single one of them, for compliance or other reasons. The only way to do this is a faceted result set, which allows us to drill down precisely in the result set. And metadata is the ‘sorting mechanism’ that allows us to do that. Now: what kind of metadata do we need exactly? We need the following: taxonomy-driven metadata, folksonomy-driven metadata, user-defined metadata (on an individual level), and semantic (or meaning-based) metadata.
The Tough Truth about the Mobile Revolution
Dan Keldsen actually sounds like he is both sober and writing about mobility. About this time last year he laid out 6 perspectives to consider when a company assumes they can just ”go mobile”. But his closing paragraph should still be memorized and recited back to business owners by smart IT managers everywhere in 2012.
Throwing iPads at systems that aren’t made to be easy to use, and accessible in the “micro bursts” (seconds to minutes rather than hours of use at a time) that mobile use typifies, is only going to result in pain for everyone.
Prepare yourself. It is going to take work to unwind the past and pave the future. But the possibilities? Endless. But only if you take the steps to move forward.
Big Banking Gets Google
Known as Compass Bank in the US, BBVA has over 100 thousand employees. They are adopting Google apps for their enterprise. This is a big step forward for Banks moving into the cloud.
José Olalla, CIO, BBVA, says,: “We were looking for a technology that would transform our business operations - not just make our workers more efficient. Integrating the Google Apps for Business suite with our own tools will allow us to introduce a new way of working where employees have access to all the information they need with just one click, no matter where they are, and can reap the benefits of using advanced collaboration tools.”
Find Big Problems
Oliver Segovia recently wrote this for HBR. I found it very insightful.
Putting problems at the center of our decision-making changes everything. It’s not about the self anymore. It’s about what you can do and how you can be a valuable contributor. People working on the biggest problems are compensated in the biggest ways. I don’t mean this in a strict financial sense, but in a deeply human sense. For one, it shifts your attention from you to others and the wider world. You stop dwelling. You become less self-absorbed. Ironically, we become happier if we worry less about what makes us happy.
We need more Data Scientists
Luke Lonergan from Green Plum / EMC thinks we need more Data Scientists.
The amount of data being created and the technology around this are changing rapidly, but human skills and organizational structures are not keeping pace – and that’s a problem. Actually, the entire panel agreed that the analytic talent gap is the #1 issue C-level execs face when dealing with big data and its adoption. Organizations are leveraging big data to support all aspects of the business with predictive, real-time insight and this is driving the need for more and more data scientists. What is also changing is the notion of how we do experimentation, analysis, discovery and more importantly how we learn and make decisions. New techniques are being developed to address this and we need more people with new skills to do the work.
Don’t Delete Anything
Lee Dallas shared some interesting thoughts on why organizations should just keep all their content forever
There was a time when we would suggest that we dispose of data because of constraints like storage cost and manageability. The cloud however offers the potential for theoretically infinite storage at affordable cost and minimal operational impact. Most organizations of any size will find it hard to justify the destruction of electronic records based on cost of retention alone. As a matter of policy then the only non-regulated reason that a company removes data then is to prevent wrong doing from coming to light.
Policy cannot establish character but it can promote damage to it. When protection from risk takes precedence over right and moral behavior we inevitably create an organization that will be less inclined to behave rightly in the first place. The very character of an organization is eroded when the adherence to policy becomes the sole justification for any act but especially the act of destroying potential evidence…
I am coming around to agreeing with the share and keep forever idea… Not because there is a lack of risk but because all else being equal – it is probably just the right thing to do.
