If you look at decision modelling as an organisational task, it is no different to development, sales planning, marketing, project planning or the other hundred thousand tasks that we perform in our daily corporate lives. Tools such as Slack, AnaPlan and Atlassian have enabled collaboration for many of these tasks and led to tremendous efficiency gains. No wonder they are market leaders, member of unicorn club and used by millions of users worldwide.
But does collaboration even make sense in decision modelling? Let us look at five reasons why this may not be even required in your organisation.
Everyone on their own
At many companies, different departments, divisions or even subsidiary companies operate as a separate organisation in their own right. There is a reason why management has designed the organisation that way, to encourage competition. Could be that different divisions could be potentially spun off as a different entity or listed in the stock markets? In such organisations, collaborative decision modelling may not make any logical sense to implement. The key here is to encourage healthy competition and not share knowledge, best practices or even a common platform for decision making.
IT and business – completely aligned
Many organisations have taken analytics to the core of their business model and have built a corporate culture around data driven decisions. At these companies, IT and business users are aligned 100% in their vision and capabilities. Obviously, this also means significant investment in tools and a large team of data analysts and scientists to make full use of all the modern software. Here, if business users want a new decision model to be built, it doesn’t have to go through lengthy cycles of planning. Or even better, IT is two steps ahead and are constantly building new models for the business in anticipation. Again here, a business user driven decision modelling platform wouldn’t make a huge difference.
Unique model every time
Imagine an organisation working on unique business problems each time. So bespoke that one you have built the model, made the decision, it is done and dusted. The problem is not going to happen again, so the model is redundant once the decision has been taken. Probably not much use in centrally persisting the model, sharing it with peers and re-use it in the future.
Once your organisation has captured data, converted to information and extracted insights, spreadsheets are an option to build decision models. You may have a team of spreadsheet experts who can build complex calculations in spreadsheets, meticulously build the models without human errors, build PowerPoint presentations to explain the results in an engaging and effective manner. And if the decision makers have the expertise to analyse these spreadsheets to understand the models distributed through email chains, of course it will work. In the end, it is not about technology, it is about human behaviour and how well the existing tools can be effectively used.
Off the shelf models for each business problem
Almost in most cases, the data for building the decision model originates at a source system. Could be an in-house operational system or third party data or combination of the two. If the source systems have been built with enough intelligence to provide detailed analytics and decision models or if your organisation has implemented specific off the shelf software packages for all the potential decisions that needs to be made in the future, it doesn’t warrant to implement a generic decision modelling framework to implement what is already available for the business users. Also, they are more used to the existing solutions than learn and use a new platform which would cost time and money.
Could there be any other reasons
Probably your organisation prefers gut based decisions or have outsourced all strategic decision modelling to a big 5 consultancy, there could be many such reasons why decision modelling may not be a task that is prevalent in your organisation. But these are a rarity and not a norm.
But if those five reasons listed above are applicable, probably spending time and money to implement a new collaborative decision modelling tool is not going to give the necessary efficiency gain that other collaboration tools have resulted in your organisation.
But if you still think collaboration may help, Decision Modelling 2.0 is the solution. What would that look like though? Business language based modelling without any need for coding or technical knowledge, creating and sharing the models along with visualising the outcomes in the same platform and not to mention the fact that centrally persisting the models on the cloud.
Images by Jordan via Flickr