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ENTERPRISE CONTENT MANAGEMENT
When we
talk about
repositories
we don’t just
mean content
repositories
but other
business
systems like
CRM and ERP
as well
and advances in technology
have created the need for a
more dynamic, flexible content
management platform that offers:
1
Access to content wherever it
might reside:
A system will have
its own repository but must also
be repository-neutral and able to
connect to external repositories via
connectors.
2
On premises, cloud and hybrid
deployment:
In the past, a system
tended to be either on premise or
cloud-based. As the popularity of
the cloud increases, users should
be able to switch between the two.
“When you’re archiving content,
you could move from a cloud-based
implementation to an on premise
one where storage might be less
expensive. Or, a highly regulated
business that’s very concerned
about its compliance might want to
retain data on premise but share
and collaborate with partners
and vendors via a cloud-based
repository,” explained Milliken.
3
Intelligent metadata layer and
federated access across multiple
sources:
“This,” explained Milliken,
“is the idea of getting access to
content based on context rather than
just what repository it resides in.
When we talk about repositories we
don’t just mean content repositories
but other business systems like
CRM and ERP as well. If I’m in the
CRM and I’m working on a given
customer, it’s obviously important
to find documents and other
information related to that customer.
That’s where you begin to see the
opportunity to span outside of one
system. It won’t be where content is
stored that’s important but how it’s
contextually relevant to you.”
4
Automatic tagging and content
analysis:
Advances in analytics,
machine learning and natural
language processing mean that
tagging and content classification
can be done automatically rather
than manually or semi-automatically
through barcodes and OCR.
Milliken points out that with natural
language processing, things can be
inferred about a document that may
not be directly stated in its content.
For example, certain characteristics
might associate it with a particular
project, even if the relationship is
never stated. Machine learning
might also lead to improved
results. It might decide ‘Everybody
else on the sales team is using
this document, maybe you’d be
interested in it too’ or ‘If you’re
searching for these kinds of things
with the term agreement, maybe we
should tag this with agreement too,
rather than just contract’.
A visionary
Gartner predicts that by 2020, 20%
of ECM vendors will be morphing
their systems to provide these
capabilities. M-Files, the only
visionary in Gartner’s
2016 Magic
Quadrant for ECM
(Enterprise
Content Management), is already
well down this road.
“Where we think we’ve got a
big head start is that we have
done this metadata thing from
the outset and have been honing
it through thousands of customer
deployments. For us, it’s always
been a question not of where
but what. In the past, we were
thinking more about data within
M-Files, but now we are extending
that to connectors so that we can
be repository-neutral. It’s a very
natural extension. Now it’s not just
unstructured content – documents,
contracts, proposals, presentations,
invoices, whatever it might be –
it’s the structured data too, the
customers in the CRM and the
vendors and projects in the ERP.
“Unifying these two
environments will lead to better
user adoption because people can
find what they need right when
they’re in the CRM. We call it a
360-degree view. It really doesn’t
matter where you start, you will find
what you need. If you’re looking at
a document and you see it’s related
to a certain customer and then you
look at that customer and you see
that that customer’s now related to
a bunch of other documents, that
leads you to information that you
might not have found with a search.
You’re creating a unified, really
intelligent environment in which
information finds you almost as
much as you find it.”
M-files’ new solution, when it is
launched later this year, will take
this to another level.
“All we had to do was generalise
our metadata-driven approach to
be repository-neutral, open up the
architecture to plug in the analytics
and boom,” said Milliken.
“Imagine you have a fileshare with
a ton of files. You now automatically
start scanning this fileshare with
intelligent analytics, something
like IBM Watson, and suddenly you
infer the customer relationships for
those documents and you tag all
those documents with a customer.
You’re not just putting a text string
in, you’re literally linking it to the
object in the CRM. At that point,
just by adding that context you’ve
dramatically changed the relevance
of that information and that is
absolutely within reach,” he said.
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