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In the Year 2020 . . . Process
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| Guest post by: Jon Hansen |
Article Overview: As posted this past past Friday, each day this week I will be providing my take on the top 5 predictions for the year 2020 from Bob Lohfeld’s July 7th Washington Technology article aptly named 5 predictions for the 2020 market. Today we tackle prediction number 3, process.
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In the Year 2020 . . . Process
As posted this past past Friday, each day this week I will be providing my take on the top 5 predictions for the year 2020 from Bob Lohfeld’s July 7th Washington Technology article aptly named 5 predictions for the 2020 market.
Today we tackle prediction number 3, process.
Lohfeld’s prognostication: There will be a
strong connection between technology and workflow to enforce process
rigor and increase efficiency. BD, capture management, and proposal
development processes will become more agile and refined to fit shorter
procurement life cycles. We will place renewed emphasis on process
maturity. Process optimization will be based on actual measurements
taken across multiple capture and proposal efforts and will use
statistical analysis as the basis for process change. Companies will
implement BD, capture management and proposal development into an
integrated workflow management system that serves as the corporate
repository to manage all new business pursuits.
Maybe it is
just me, but even though one of my core areas of expertise was heading
up an R&D team that was funded by the governmentback in 1998 to
develop applications utilizing an agent-based Metaprise model (re how
traditional software applications would eventually evolve within the
virtual realms of the Internet), I quite frankly did not understand what
Lohfeld's actual process prediction entailed.
Perhaps playing one
too many football games without a helmet, I readily got lost in the
mire of buzz terminology for what in reality should be a very straight
forward commentary.
Process and process mapping, as I have always
quite simply maintained, must reflect the manner in which the real-world
operates. In essence, and eschewing the traditional assumptive-based
equation models under which most workflow mapping is analyzed and
developed, establishing a process that adapts to the way in which people
actually work versus creating an illusionary ideal to which they must
adapt is the linchpin for ultimate success.
Take for example the
high rate of eProcurement automation initiative failure which is upwards
of 85% (and even higher). In these instances, the traditional approach
was to develop a theorized optimized workflow process which then
usually required an aggressive change management strategy that for the
majority of organizations was impossible to implement. In short,
organizations in both the public and private sectors spent hundreds of
millions of dollars trying to adapt their operations to an ideal
workflow that in reality created more work re cycles on the front lines
than it did the expected efficiencies. Now you know why 85% of all
initiatives fail.
This premise of equation-based versus agent-based modelling extends to all areas of an enterprise as well.
For
example, in developing the process strategy for the New York City
Transit Authority to support their IT infrastructure, I discovered that
the biggest obstacle to their service department's ability to meet the
3-hour response or Service Level Agreement and corresponding service
call resolution requirement was linked to the fact that the majority of
technicians would wait until the end of the day when they returned to
the office to order replacement parts. This created what I called the
proverbial fork in the process road scenario.
Specifically,
technicians were rated on the number of service calls to which they
could respond on a daily basis within the appointed 3-hour time frame.
If you have ever driven anywhere in New York you will understand the
true weight of this situation. This meant that ordering the required
parts at the conclusion of each service call delayed their ability to
get to the next site. As a result, the technicians sandbagged as it is
called all parts orders until the end of the business day, thus
maximizing their ability to respond to on-site call requests.
Unfortunately,
by waiting until the end of the day to order the required parts meant
that the cost per item rose significantly, as did the challenges with
receiving it on a timely basis re the later in the day an order was
placed, the longer it would take for the part to arrive and thus
extending the call resolution period to between 48 and 72 hours. Also
adding insult to injury was the fact that the later in the day a part
was ordered, the greater it's cost.
So what is the solution? Adhere to a workflow process that conflicts
with the real-world in which the technicians operate forcing them to
comply with the post call ordering mandate or, adapt to the end of day
reality thereby achieving the optimal combined result of service call
response and resolution?
To me, the latter made more sense, and as
a result I leveraged emerging SaaS-based technology to support the
end-of-day ordering process that in conjunction with improved warehouse
management significantly reduced the cost of goods ordered at the end of
the day, while compressing the service call closure time period from 72
hours to 24 hours (or less). Ironically, and I must admit
unexpectedly, there was no decline in the number of calls to which a
service technician was able to respond. Go figure.
In my humble
estimation, this is the epitome of linking supporting technology to
real-world process to deliver a desired outcome.
Now some might
suggest that scalability of workflow processes is a factor that I may be
ignoring in that within the same industry sectors there are general
rules of operation that should and do apply. You would of course be
correct in assuming the transportability (if this is the right word) of
workflow process within similar industries. However, and here is the
problem as I see it, are the inherent risks linked to assumptive
expedience and implementation convenience. Especially in the emerging
non-consultancy world.
What I am talking about is the shift as one
senior Cap Gemini executive put it, from implementing a particular
strategy over a period of years to months or even weeks. This
pressurized timeline means that results have to be produced much, much
sooner and therefore increases the potential for a one size fits all
approach. Nothing could be further from the truth as each and every
business while sharing similar operational traits also has unique and
competitive differences.
So what is the future of process for 2020?
Creating
and utilizing an adaptive model that maximizes an organization's
ability to customize workflow processes leveraging the modularity of
SaaS-based technologies within the framework of a Metaprise or private
hub.
I know, I could have said this right out of the gate and
saved time and/or electronic print, but wasn't the journey to get here
fun?
Next installment in the 5-part series: Technology
Article Tags: 2020 market predictions, process analysis
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About the Author: Jon Hansen RSS for Jon's articles - Visit Jon's website Personal Profile: http://www.linkedin.com/in/jwhansen Click here to visit Jon's website The IACCM Global Collaborative Platform Delivering The Power For Change IACCM Profile What are the 3 biggest challenges faced by supply chainpurchasing professionals today Survey Result 19 What kinds of information and technology is used in Supply Chain communication The Power of the Blog Is There a Difference Between a Material Requisition and a Purchase Requisition A PI QA |
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