The Evolution Of Collaborative Tools


In the early days of Lotus Notes we, at Lotus, often
felt like we were crying in the wilderness about how important collaborative computing
tools and groupware were to business communications and productivity. The hardest part was
getting business leaders to understand what the terms meant. We define collaborative
computing and groupware as the advent of document-centric, unstructured, knowledge-based
applications that foster simultaneous collaborative computing which, in turn, accelerate
user and corporate productivity rates manyfold.

What a difference 10 years makes. From Lotus’
perspective in the waning months of 1997, groupware has not only been firmly embraced by
major enterprises throughout the industry worldwide, but is also rapidly converging with
messaging and the Web into one inseparable piece of infrastructure. Not only are we
rapidly approaching the 20 million user mark for Lotus Notes installations, but the
biggest players in the global software market have weighed in with psuedo-competitive

A Paradigm Shift
As we consider future product directions to meet this evolution, it’s an oxymoron for
industry vendors like us to conceive of investing in separate topologies to deal with the
convergence of these three critical technologies. And if one considers the value and
complexity curve that we’ve climbed as an industry over the last three years, it’s quite
stunning. It was only about two and a half years ago that most of our email experiences
were either host-based, meaning System-370 products like PROFS, or mid-range products like
All In One-based, and/or file sharing-based, with products like Microsoft Mail, cc:Mail or
others. But today, that evolution is rapidly shifting to a second generation of client
server advanced messaging systems that facilitate collaborative computing.

It wasn’t long ago that messaging was the
carrier pigeon for a range of attachments. Somebody had to give idea to attach a world
processing file or a presentation graphics file, or some other business object to a mail
message. It was user-driven rather than a product of some centralized IS department. As a
result, the average size of a mail message in the course of the last 30 months has gone
from 4 K, on an average, to something close to 22 K, due to the ubiquity and propensity of
our email to be the carrier pigeon for this range of business attachments. There’s still a
lot about this that’s going to change very materially, as well.

With the advent of collaborative computing,
rather than using the mail message as a carrier pigeon or a transport vehicle, the
document became the central container for an entire class of business objects. It wasn’t
simply objects like text files that were sent, but rich documents that were differentiated
by many fonts, colors, sound, or video. The richness of the information sharing experience
exploded because of the diversity and robustness of the media and the data types that
could be found in a document. Today, with Internet explosion, and its revitalization with
the advent of products like Netscape Navigator, the Universal Resource Locator (URL) has
become the most ubiquitous data type of all. URLs have begun appearing in virtually all of
our documents. It was brilliant go-to-market strategy on Netscape’s part that made the
Navigator browser grow at the staggering rate that it has achieved. Practically everybody
downloaded their first browser. No one bought it. It just became freeware.

This has given millions of us the
capability to click on a URL and be immediately launched in space, to some other context,
to some other time, to some other server, in short, to the tremendous wealth of
information and contacts on the Internet. While considering how tremendous a technological
advancement this has been, it’s also important to remind ourselves that the topology has
to be consistent as we jump from one source of information to another. The users drive the
propensity of all of this change, and we can’t anticipate in advance either what the mix
of their operating systems, clients, or servers will be on either side of the firewall.
And this is even more of a given outside firewalls. Neither can we predict the rate of
growth or change that will occur within their infrastructures.

So, the important thing is to invest in an
infrastructure which deals with the convergence of these technologies, and build as much
strength and mission criticality into those infrastructures as possible. But as we reflect
upon how the industry got to this point, we’ve gone through a significant evolution since
the seventies. During that time, the bulk of our focus as an IS industry was on backoffice
automation. It was the era of big iron and big systems. Hierarchical databases were being
replaced by relational databases. We were focused on things like automating payroll and
general ledger systems. Interestingly enough, although it’s a little self-deprecating to
admit, it was this period in the mid-to late-seventies that our companies received their
greatest RoIs from IT as we were automating those manual tasks. For the most part, we
haven’t seen RoIs of that nature since then.

And as the PC moved out of hobbyists’
basements in the eighties, with the help of desktop productivity tools from companies like
Lotus, we rapidly shifted to the advent of the frontoffice.

The ‘Virtual’ Environment
We’re now in a period in the nineties that has focused on what I would describe as the
‘virtual office’. All our quaint definitions of office or enterprise, which encompass in
many cases the organizations in which we work, are crumbling into virtual teams, virtual
organizations-even virtual companies in some respects-as we merge our computing paradigm
outside our firewalls and directly connect our suppliers, our customers, and in some
cases, our competitors. With the advent of the virtual office and the graphical user
interface layer in the Web, our entire computing paradigm has evolved far beyond what had
been predicted, and irrevocably changed for the better. The system architecture that is
allowing ‘virtual offices’ to exist in this manner is one based on network computing.

Network computing is driving 24 percent of
the CAGRs in business today, and what we traditionally refer to as backoffice and
frontoffice computing paradigms are driving about 7 percent of the industry’s growth,
which will top $ 1.3 trillion this year. It’s also important to note that 15 percent of
that growth is coming from embedded microelectronics devices, which brings about a whole
additional thrust in the advent of things like universal messaging, as things like our
messaging and our mail systems merge and the client devices that we potentially
interoperate with become more ubiquitous. We used to think about dumb terminals or PCs,
and now of course the birth of the NC. But, it’s the advent of things like smart
telephones and PDAs for the first time that are becoming a significant and a serious part
of this business.

The Knowledge Management
An important subset of network computing that speaks to the practical application of the
vast wealth of collective data being captured and managed by collaborative computing
technologies is Knowledge Management. Knowledge Management is simply the conversion of
tacit knowledge, our corporate or institutional learning in memory, to explicit knowledge.
The important issue here is the use of technology to capture the inherent learning that
goes on in our corporate cultures ubiquitously as we progress. If we don’t find a way to
capture and harness that collective knowledge, it will never be captured, stored, or
served to people in any useful manner. And, especially in our industry, it’s that
intellectual capital-our human assets-that walk out of the door every night that we care
most about. They represent the biggest chunk of our investments. But, what is the process
for making this Knowledge Management workable and returnable in our companies? It’s about
creation, it’s about the ability to employ tools, to build a sort of infrastructure that
captures information as we move forward, and the corporate discipline to codify all this.
It’s about the application of this knowledge for specific corporate purposes. And is about
the technology that allows for its universal distribution: technologies like search
engines, datamining capabilities, an ability to move and manipulate this information

It’s also about the ‘occasionally
connected’ computing metaphor and technologies that we are becoming dependent upon in
collaborative computing, like replication. An easy example is how rapidly the travelling
business knowledge workers are adopting personal data assistants that can easily capture
and update data (mail in particular) over standard phone lines or wireless means. The
payoffs are obvious: accelerated cycle-time for decisions, real-time training and enhanced
skills, reduced R&D costs, increased worker independence and empowerment, enhanced
customer relations, and improved products and services.

For example, Nokia recently sought to
operationalize what it calls the notion of ‘democratizing strategy’. This is a very
diversified company with large, global operations producing about $ 33 billion in annual
revenues. The CIO there had the notion of what would later be called ‘future watch team
rooms’-knowledge bases that were spread around 18 different sites where they got
information from the market about changes in the nature of the competitive frame of
reference in that particular part of the world, aggregated back to a centralized database
every night, and shared with the part of the corporate staff that dealt with all of the
annual planning cycles. Part of its beauty was that it was never more than a few days out
of date. Ultimately, it led to the building of a future watch database for the board of
directors. It became a way to establish listening posts throughout the marketplace, where
soundings could be taken on a regular basis, gathering latest information on the
competitive dynamics of their particular business. That’s a real form of knowledge
management at work today.

Similar circumstances at Chrysler Corp.,
which is made up of a lot of independent brands and lines, whether trucks of passenger
cars, led to the creation of what it called Engineering Book of Knowledge (EBoK). This was
about common manufacturing processes that were relevant not just to trucks, but to cars
and other things, because the construction of subcomponent processes for doors or
dashboards, in some cases, were irrespective of models. And in automotive manufacturing,
70 percent of the parts that go into the cars we buy are outsourced. So, this became an
important part of their Knowledge Management process. Important because it netted them, in
the model year 1996, $ 1.2 billion in savings and reduced manufacturing and subcomponent
costs, while accelerating time-to-market in certain lines and models. $ 1.2 billion!
That’s Knowledge Management.

These are the results of collaborative
computing maturing into the age of network computing. It’s an incredible journey from
where I sit, and one where we’ve only begun to see the real payoff for the global

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