I got an interesting comment the other day from Craig Cameron about the potential for self regulation - the fact that some businesses want not only to comply with government enforced regulations but also to "comply" with the wishes of socially conscious consumers, for instance. This got me thinking about how this might be the same or different from other kinds of compliance-oriented decision automation. Some thoughts then:
- Like most compliance problems automation is primarily a rules problem.
Showing that every transaction had followed the same rules, being able to show which rules fired in which transactions, managing exceptions effectively and so on would all be key, even if the rules were things not to do with regulation but with "social" compliance.
- There is a growing role for analytics
Just as we see in regulation a trend towards expecting companies to manage the statistically likely outcomes of their rules, I would expect to see the same in social compliance. If the effect of my rules is to have a socially unacceptable impact overall, it will not matter that the rules themselves seem OK.
- Rules may need to be more visible in this case
Unlike a typical compliance problem where the rules will likely only be shown to regulators or auditors, rules for social compliance might have to be published to show the public they were being followed. This would make the normal readability benefit of a business rules approach even more critical. Being able to display the actual rules and have an auditor, say, confirm that they are what is running in the system might be critical. Having a readable syntax would be key.
- Customization of rules by consumers or trading partners
If a company starts offering customers (whether consumers or trading partners) options for social compliance, they will likely need to allow a degree of customization. A company or consumer might, for instance, want to specific a maximum additional cost for a renewable component let's say. This will mean using the power of a business rules management system to mange layers of rules - central ones, local ones and customer-centric ones.
Thanks to Craig for an interesting line of thought.