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 government back 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. (Note: for those who are interested in learning more about why prices for certain products increase throughout the day, here is the link to Part 7 of my Dangerous Supply Chain Myths Series which explains this phenomena.)
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?
Tomorrow’s post: Technology
30
Procurement Insights
In the Year 2020 . . . Process
Posted on July 13, 2011
0
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.
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 government back 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. (Note: for those who are interested in learning more about why prices for certain products increase throughout the day, here is the link to Part 7 of my Dangerous Supply Chain Myths Series which explains this phenomena.)
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?
Tomorrow’s post: Technology
30
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