Let’s see if you’re ready to embrace adaptive case management…
How long would take you to go through all the possible solutions of this equation: 1 ? 2 ? 3 = ?
How about this one: 1 + 2 + 3 = ?
A piece of cake!
What’s the difference? Well, in the first case you would have to consider all the possible options before giving an answer. It is not impossible, but it’s neither efficient, nor feasible…
Imagine the first example as being a scenario for Adaptive Case Management (ACM). You know the rules of play, you know the players, but it’s impossible to easily know the end result without having additional data.
Now let’s go back in history, when automated processes started to be part of our lives. Industrialization brought us the first production lines. The sequence of steps was very clear, the end result was always the same, the path was predefined, the machines repeated the same action every time and changing a step would mean to stop production and modify the way a mechanism works.
After some time, organizations started to adopt the same concept by automating business processes using BPM. A workflow defined a clear and standardized way of handling data, systems and people. Things started to become more flexible with the help of services and software.
Nowadays, nature makes its way back into our lives and automation, linearity, standards and predictability start to become show stoppers in the way in which we try to evolve. A simple linear process just won’t be able to handle the way we implement solutions. We would need to be able to handle much more complexity.
Complexity means multiple interactions between different independent elements. Adaptive Case Management tries to give a solution to handling complex systems in a very natural, human way. This is done by defining a set of independent activities and actors, all being governed by a set of rules. The rules are applied on the information we have inside the system. Every time data changes, the actors are able to trigger activities according to the rules. This means that data drives the process – , not the other way around – and that the system adapts itself.
Let’s take an example – The game of chess.
The actors are the chess pieces and the activities are the set of permitted movements for each type of piece. The data is represented by all the information a player has about the game. Everything is governed by a simple set of rules – the rules of the chess play. Each time a player will have a different array of possible moves, but based on the current status of the game, he would chose only one action, of course, by obeying the rules of play.
Here are some characteristics of ACM:
1. Data drives the process – The status of the chess play is decisive for the next move.
2. The process path is not known from beginning – You only know the history of the moves once the play is finished, not beforehand.
3. Non-linearity & unpredictability– Each step allows for multiple actions which can change the direction of the case decisively.
All elements of a case can sum up to this diagram.
- Data – all information a player has
- Activities – play moves
- Milestones – phases of play
- Stakeholders – chess pieces
- Rules – rules of play
- Events – when time for a move runs off or when it’s check
- Outcomes – win or loss
Everything that we do is governed by our human nature which is unpredictable, nonlinear and forever changing in response to the interaction with what surrounds us. Embracing this behavior and letting our technology become more human we will be able to address challenges which until now were impossible tasks.
People are the ones who possess creativity. Machines simply execute.
ACM is about teaching systems and software to work more as our brain does.