Today’s Adoption Series entry follows our last article which looked at the concept of a “learning curve” and argued that until users find the new process to be more efficient than the old process (when the efficiency “hump” is crossed), end-user adoption remains at risk.
Say what you want about the “old ways” (i.e. the legacy/offline/manual processes that leverage no or little technology), for many end-users, they are pretty easy (even if the results leave much to be desired). Discussions onsite at client this month raised the some issue when user adoption came up.
Me: So you deployed a suite of solutions five years ago, why wasn’t there greater adoption?
Client Answer: People found using the tools more difficult than what they were already doing; so ,most people tried whatever they could to not use them.
Me: Ugh!
The end users’ response is problematic but unfortunately, it is not unusual. Let’s get specific using a Spend Analysis example for a Buyer who needs to understand total spend in one category.
Spend Analysis – The Old Way
From: End User [mailto:end.user@company.com]
Sent: Before New Spend Analysis Initiative
To: IT
Subject: Category Spend
Dear IT –
Please run a Spend Report on the following category for the following time period.
Regards,
End-User
Spend Analysis (Advanced) – The Old Way
From: End User [mailto:end.user@company.com]
Sent: Before New Spend Analysis Initiative
To: Suppliers
Subject: Our Spend
Dear Suppliers –
Please send me the detail on our spend with you over the last contract period.
Regards,
End-User
Unfortunately (again), this is still a common practice. And, when you look at the amount of time the End User spends get an answer to how much total spend is in one category using the above process, we’re looking at 10 minutes tops –
- 2-3 minutes to write and send the emails
- 2 minutes to download reports
- 5 minutes to calculate the sum of one column
If the supplier is on its game, it will deliver a nice response and cut that 10 minutes down to 5 minutes.
“Done! Here’s your answer….”
The first time this same buyer logs into a new Spend Analysis tool, it will take more than 5 or 10 minutes to get comfortable with the system and run a category spend report (even a pre-canned one). It may take more than 5 or 10 minutes to login.
The second time this same buyer logs into a new Spend Analysis tool, it will take more than 5 or 10 minutes to get comfortable with the system and run a report on category spend
This same buyer may never be able to get the total spend on a category from a Spend Analysis system in less than 5 or 10 minutes.
“What’s so efficient about that?”
Obviously, the “Old Ways” shown above are not ideal, in fact they are problematic – do we think a supplier has never “tweaked” what is purported to be a “direct AR feed?” Can we wait 4 months for IT’s response? Does the Buyer really know all of the suppliers in one category? etc. etc. etc…… And that is the point, that is why companies automate Spend Analysis.
But, how many solutions are internally sold as driving huge “efficiency” gains? Companies need to look at the phase one of a supply management technology deployment and determine where the efficiency benefits are realized and who’s really saving time? When it comes to the end-users, time savings may not be their major benefit, at least to start – accuracy and timeliness of data may be the first level of end-user benefit.
End-user efficiency (defined as end user time spent doing an activity) does not have to be a wave one goal of a new technology deployment
Postscript: Happy Diwali!
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