Let’s take queuing for example. There are several constraints to optimizing a queue, for example;
- The number of channels or service personnel available
- The speed in which each personnel is able to service the customer
- The time in which these personnel are ‘operational’ (i.e. 7 days a week, 8 hours a day etc)
So companies place service personnel into training, create reams of documentation and process charts that ‘robotizes’ their capabilities on top of automation tools to supposedly hyper speed all those back end processing.
Appointments help somewhat but they’re not too efficient for mass services type of operation and customers themselves tend to be undisciplined in keeping to the appointment leading to backlogs.
So the problem statements are:-
- Customers wait for too long and they balk or renege
- They choose an off peak hour to go to a branch only to discover that the services that they require are prioritized to only 1 booth and that booth also has an annoying queue.
But what are we abstracting?
Let’s think about the constraints a bit, the extensive queuing occurs because people tend to converge on commonly known and accessible landmarks. They wait because there’s only X amount of people available to service the potentially hundreds of people waiting to be served. This also happens because:-
- Customers have to be physically at the branch or retail service centres to take a number
- Customers can’t know for certain how long it will take before their number is called.
- Customers still need to be physically present to be called.
Level 1 Abstraction
What if we can eliminate the need for physical presence, what if queue numbers can be taken online anywhere, over the mobile phone for example; this would allow the customer to pre-plan his trip and roughly estimate when he should start the journey to your office, making the experience less taxing.
Level 2 Abstraction – It’s really about time, not the queue
Now what if the service provider is able to tell the customer exactly how long it will take before we reach his queue number; so now the customer can pre-plan his journey, queue while he’s not physically there and time his entrance precisely (well almost).
You’ve just eliminated the concept of queuing from the customer and replaced it with ‘time’. Remember the earlier principle ->
“Do not make your problem the customer’s”.
Beyond guaranteeing time, you are now able to guarantee service to the customer; when the moment he walks into the branch, he shall wait for no more than 5-10 minutes. And that margin can be further reduced with the old school optimization methods that we mentioned earlier.
Level 3 Abstraction – The head shake moment (mashing things up)
So now imagine this, all the queuing system from all your branches are made available on line to the customers and aggregated into a database and updated real time. Customers just need to recommend the time that he wishes to conduct a business at the branch; the solution recommends a branch closest to him through the GPS system, with the shortest queuing time for the time slot that he wants. There’s no such thing as waiting number, and the customer is notified should there be an earlier slot or whether he’ll be running late because the GPS works both ways.
What we’ve just done is abstracting a queuing problem to a focus on time, availability and location. More importantly; bringing customer centricity to the fore.
NOW GO DO IT!