The Intelligence of Business
Originally posted on http://eugenea.spaces.live.com on 08/03/2007.
I use this slide (Figure 1) for presentations on SCL to explain where it fits in.
Originally posted on http://eugenea.spaces.live.com on 08/03/2007.
I use this slide (Figure 1) for presentations on SCL to explain where it fits in.
Figure 1 - The Intelligence of Business. Human/Machine intelligence continuum.
As I mentioned in my previous blog on
Business Performance Management, corporations must be seen as orgamisms and
treated as organisms. They have an intelligence like all creatures (mostly
animals) which control a body that interacts with the physical world, and it
takes in resources (revenue) to keep itself running and hopefully having excess
(profit) to support other creatures (the stockholders) as well.
The attached slide depicts four stages of the intelligence of business from the
least advanced on the left progressing to the most advanced on the right. The
third, circled in red, shows where we are today. The blue part of the bar
represents the part of the intelligence of business that is human and the green
represents the part that is machine. The green is differentiated into light and
dark green, representing pure data and rules, respectively. But, not only are
the bars showing the percentage that is human and machine, but the width of the
bars represents the size of the business.
Before computers or other recording devices such as paper, the intelligence of
the business creature was 100% human. One or more humans made all the decisions
for the business based on whatever was in their collective heads. With the
advent of paper and adding machines, humans now had tools to assist their
memories in finding patterns. This is represented by the left-most bar. However,
that level of assistance is miniscule compared to the logical power provided by
the human brain. Notice that the small green part is dark green, meaning the
part of the intelligence of business that is machine is all data. The width of
the bar is very narrow too, depicting a small business.
The early days of computers brought on a way to store and retrieve massive
amounts of data (the bar second from the left). This ability significantly
increased the percentage of the intelligence of business that is machine, even
though it is still primarily just data. But the massive amounts of data and the
ability to effectively access it greatly enhanced the effectiveness of the
logical human brain. Consequently, the scale of the business grew significantly
as the wider girth of the bar indicates. This is where business has been for the
past twenty or thirty years.
The third bar (circled in red) is where we are headed today with Business
Performance Management. We see for the first time a light green part which
represents rules stored in computers as opposed to just plain data. Such
electronic rules has been around, but represented a small part of the
intelligence of business compared to the human part. Rules existed primarily as
hard-coded logic in rigid software applications. Soft-coded rules were confined
to things like configuration files, even though such files contained just
"soft-coded parameters".
Now, soft-coded rules are more widespread, encoded using many technologies such
as Windows Workflow, BizTalk orchestration, and especially "Semantic Web"
technologies such as RDF. There are also pockets of artificial intelligence (AI)
out there such as risk management at financial institutions. The proliferation
of BPM adds rules through its fundamental concepts of strategy maps and key
performance indicators (KPI). KPIs are business rules. They are rules that tell
human (or machine) workers when they are doing well or poorly.
With BPM, the scale of business can grow significantly with encoded rules making
and executing simple and not so simple decisions more efficiently and tirelessly
(machines don't get bored) than most humans. The heavy logical lifting is still
in the realm of humans, but now humans are freed from many mundane tasks to
focus on bigger impact tasks.
The right-most bar depicts business once a widely accepted form of AI is
deployed. Such a technology would be like XML on steroids. My take on this
technology is in my SCL language, I mention above. In this bar, we see that the
intelligence of business is now about a third each of human, data, and rules.
To elaborate on the statement "XML on steroids", I'll briefly describe what XML
has done. XML truly revolutionized software architecture. It is the basis of
Service-Oriented Architecture (SOA) which enables millions of servers to easily
exchange messages. It's the backbone of e-commerce. The problem is that these
messages (SOAP) are rigid in nature. Another application of XML, RDF, is
designed to add semantics by allowing annotation of XML elements so we can
recognize that one XML document is a type of document. For example, an XML
document represents an invoice and this particular element is the customer name.
SCL and RDF overlap a great deal at this time (that wasn't so three years ago).
RDF is now the data source for query languages capable of inference. In any
case, once technologies such as RDF and SCL gain widespread acceptable across a
wide range of applications, it will kick off another revolution as XML did, but
much more profound. There is an article on my SCL site on
SCL Web
Services that introduce the topic.
SCL also runs in an environment that implements a few concepts I'm in the
process of laying down in text. I expect to have this done in a couple of weeks
and will announce it here when it's done.