At Dhara, we focus on three
primary areas of service to our customers. These service areas include
Strategic Support for the CIO, the implementation of new technology to improve
the business, and general sourcing for projects. In my blogs each week I
want to dedicate at least one entry to each of the above areas. On
Fridays I plan to discuss sourcing issues and opportunities.
I am a firm believer that in order
to speak about trends, or issues, it is critical to have actually operated in
the space. In my long IT career, I have managed development areas that
included out-sourced providers at the project level, the enterprise level, and
as staff extensions to fill in the missing resource needs for our core
resources. My typical span of control for technology development,
support, and operations has usually been in the fifty-to-two hundred associate
range. This will give you—the reader—an understanding of my bias when
reviewing my Blog entries.
As an outsourced service provider,
we of course believe in the wisdom of outsourcing. As a business, we
believe in win-win sustainable solutions to problems when we create
partnerships with our stakeholders.
Much has been written about the
value of offshore development facilities. One area that I have managed
that has produced extremely good value is that of prototype development for new
product concepts. Assuming that you have control of your offshore
facility’s intellectual property from an ownership and risk management
perspective, the development of new tools and technologies can be very
effectively done.
In my own experience, we developed
concepts of products in the States, with a very high degree of rigor.
This rigorous approach allowed our offshore engineers and architects to develop
component specifications that our onshore team reviewed and approved. It
allowed software construction to be done in a rapid development methodology
that allowed our onshore staff resources to review components as they were
being constructed. We were able to specify changes that needed to be made
and see the results quickly.
To manage the process we utilized
a “follow the sun” development approach. This allowed work to be
completed overnight by us in the States and during the day in our facilities in
the Pacific Rim. It required a hand-offs policy at the end of our day and
the beginning of the Asian day, and it was very effective for us.
One of the biggest benefits for us
is that it isolated our mainline staff to develop “test” concepts. One of
the things that every large development organization tries to do is to isolate
mainline business support from things that might never happen. In this
way people do not fight to protect their turf when they think that their jobs
might be threatened. So, instead of creating "skunk works", projects done
in semi-secret mode and not impacted by existing systems or thinking, here in
the States, we simply were able to isolate the effort off shore. Skunk
works were named for the secret nature of the effort—in my experience they
usually ended up creating more of a skunk like smell, rather than any tangible
results. By clearly defining the offshore work as a prototype
development, we were able to limit the distraction to our mainline staff.
By developing the prototypes with rigorous design and building components, we
were able to deliver working modules that were potentially reusable in the
future for development of the actual products.
These projects were successful
because of the design and management rigor that was employed. They would
have been unsuccessful if we had simply created a high level concept in U.S. English
in a three-page overview and had said, “Buy us one of these”. The
cultural and language differences would have been a disaster. If you have
not been to a third world or emerging economy culture, it is impossible to
understand the environment in which people are working.
Over the years I have been to the
Pacific Rim on numerous occasions, but I had never been to India until last
year. I had seen a number of pictures of Bangalore and had read about it
being the “Silicon Valley” of India. As I got off of the plane in
Bangalore, I realized that I had seen the ‘demo’ version of Bangalore, and that
the reality of that city was far closer to that of Manila than to San
Jose. It was also the most peaceful I had ever felt in the world—probably
because I felt genuinely welcomed there.
My point is simple, the cultures
and languages in Asia were different from those in the U.S. We were
successful in our development because we took these differences out of the
equation by eliminating colloquialisms from our language and expectations from
our minds.
I remember being in Paris a few
years ago, and the limo driver asked me if I was American. I hesitantly
answered, “Yes.” He said that, for an American, I spoke awfully good
English. I realized then that, to be successful in any offshore
endeavor, those traveling overseas need to have excellent English language
communication skills.
In the coming weeks I will discuss
other sourcing issues, based on my experienced point of view. I will also
explore new trends that can be applied to make sure that the promise of lower
costs and higher quality is realized in your sourcing efforts.
Fred Geiger
www.dharacg.com
At Dhara, we have been involved with “master data”
initiatives and storage mechanisms for over eight years. We think that the master data problem can be
solved once and for all with new technologies.
My personal involvement with master data began thirty years
ago, although I had never heard of the term “master data” until years
later. Back in the early eighties, I was
working in the supermarket IT services industry, and we were trying to arrive
at a unit price for the items in a shipper, which is a floor display stand
heavily used for seasonal items like cookies, make-up, suntan lotion, toys, and
spices. The problem was that the shipper’s
price was tied to the retail value of one of the items. Consequently, if all of the retail items
totaled $299.99, then one of the items sharing the same product bar code would
be assigned a price of $299.99, instead of its correct price of $1.99. This occurred because the common practice at
the time was for one of the items in the shipper to have a bar code with the
same number that was on the external carton .
Twenty years later, an industry initiative for data
synchronization was charted so that problems like that could be solved
elegantly. It sounded very simple. It
was not. We discovered that an item’s
data components could change based on the geography of the shipping point; the retailer or distributor to which items
were being shipped; and in the case of
multi-national products, the geography of the source item(s) and the shipping
route to the destination. As a result,
massive amounts of money were invested in trying to solve the problem of data
integrity.
In all of the other industries, like the high-tech ones, in
which I worked, the problems were similar.
In addition, the inclusion of more points of distribution added
complexity to the situation because third parties often did the final assembly
of the products, and different third parties
might handle multiple combinations of separate components before the
final item was sold to the ultimate consumer.
At Dhara, we are looking at applying the technology of the
semantic plane to the problem of master data provisioning. Each Wednesday, over the coming weeks, we are
going to be exploring this topic in our Blog.
But for now we wish to convey the idea that the rules for obtaining
information about a customer’s data must be dynamic and this knowledge base must be maintained by
factoring in elements such as the
quantities purchased, the available supply, and the context of use. Other factors, such as the availability of promotional
programs, time, geography, and transportation costs should also be described in a knowledge base that can be
queried.
In the 80s, being able to differentiate between a shipper
versus a consumer selling unit would have provided the information necessary to
determine the price. Unfortunately, the
technology to accomplish that did not exist at the time. Since then we have had to create kludges and a whole new system of numbering standards in order to “solve” a
simple problem.
If your organization still has a master data problem, and
you would like to discuss it with us, please see our website at dharacg.com, or contact us by email at info@dharacg.com
Fred Geiger
www.dharacg.com
Imagine a scenario where you are preparing to make travel plans, for business or pleasure. If you had a crystal ball and could predict the probability of arriving at a destination on time, you could manage your time much better than you do now. Unfortunately, that is not the case today, despite the tremendous advances made in weather predictions, traffic delays at airports and road congestions due to construction etc.,
Put in simple words, such a scenario would represent a better world where an event takes place just-in-time, just-as-predicted and just-about-right
However, humanity has now at its finger-tips the tools to predict, to a high degree of accuracy, the natural disasters and weather patterns. We have several disparate tools to predict events. However, we do not yet have a composite tool to put it all together.
Consider, for example, the question posed by this curious user about lack of mash-ups for Air Traffic delays:
http://paul.kedrosky.com/archives/2007/10/03/air_traffic_mas.html
Orbitz has made a note-worthy collaborative effort to provide such a mash-up, which relies on user updates. See below:
Absent reliable user updates, however, this tool lacks the predictability and reliability.
What is missing is a
mash-up or tool that provides semantics to all these inanimate data sets. For
example, a web-site that accepts a user’s question:
"I am traveling to
We have the current technology to answer the above question in a more or less accurate manner. However, we do not yet have the ability to analyze the question, interrogate various mash-up tools to gather answers to sub-sets of the question and stitch it all together.
Given the finite nature of relevant questions in any particular domain, air traffic and travel in this case, it is possible to parse the questions into sub-sets and get answers to those questions using existing tools (mash-up) and mash together the results of those mash-ups.
Take for example. OWL Specification from W3C:
and comments on how OWL is relevant:
http://www.xfront.com/why-use-owl.html
The example above describes how the computer can arrive at a logical conclusion that is not explicitly stated in the data presented to it. Similar conclusions can be drawn on predictability of air travel using disparate sets of data relating to weather, traffic delays and airport information.
That day is not too far off.
Sastry Dhara
www.dharacg.com
