Scenario Planning in Anaplan, Part II: From Insight to Action
In my recent blog post titled Scenario Planning in Anaplan, Part I: The Power of 'What If', I introduced the key steps needed for effective scenario planning in Anaplan and focused on the mechanisms to develop a forecast ('what') and evaluate the impact of forecast events ('so what'). In this second part, we look to move beyond vision and insight to evaluate actions ('do what').
Like many modeling use cases in Anaplan, there are multiple approaches to take. Below I describe what I have found to be the best way to leverage effective model building techniques and best business practices.
Key Elements: Drivers, Actions, and Playbooks
- The base model should be driver-based and include multiple scenarios, as described more fully in Part I. This allows us to use actions to adjust driver values and reevaluate results dynamically.
- Each action can be used independently to incrementally adjust driver values (Figures 1,2,3).
Figure 1: Adjusting Capital Expenditures
Figure 2: Adjusting Productivity
Figure 3: Adjusting Driver ValuesThese impacts can be of various types, including but not limited to:
- Productivity changes: adjusting the volume of activity that can be handled by a single resource.
- Business or activity volume changes: adjusting the number of business units and/or activity (effort) units. For example, a business unit might be the number of units sold while an activity unit might be the number of cases shipped or calls taken.
- Pricing changes.
- Capital expenditure changes and the impact on cash and depreciation.
- Changes in non-volume-sensitive operating costs or headcount.
- Ideally, actions are combined in playbooks. Our model uses a separate list of actions, and then assigns actions to playbooks. In the new UX, we use forms to allow the users to create and assign actions on the fly (Figure 4).Figure 4: Enable playbooks and actions; evaluate impact on P&L
- Playbooks and actions can be enabled or disabled through a simple boolean.
- The model should have the ability to evaluate the resulting model elements, both including and excluding the impact of playbooks and actions.
- I have generally chosen NOT to dimension the entire model and calculations by playbook or action. In a large model, this would create significant size implications, particularly since these apply against multiple scenarios and other dimensions (products, customers, etc). Instead, I adjust the driver values on the combined impact of the selected changes.
- The impact of this is that driver values changes are additive. In a more complex model, the modeler might choose to find a way to allow for automated interaction between drivers. For example, one action could impact on another in a non-linear way. Using multiple actions, this can be adjusted manually by the analyst by customizing actions and enabling as needed.
- In very complex Anaplan models, interaction between variables and over time would tend to create circular calculations. We have overcome this through repurposing of the time dimension, or one could leverage external capabilities to find optimal solutions.
- The modeler should be able to evaluate the sensitivity of output to changes in inputs. For example, what is the impact on profitability of a 5 percent increase in sales, compared to a 5 percent impact in productivity? This allows the modeler to identify the most likely set of actions that would be leverage-able.
- This building of these models, and the testing of scenarios, is valuable in and of itself, because well thought out models help us understand both the likely range and volatility of potential outcomes, and the actions that the organization can take to prepare, anticipate and react.
- Ensure that all model elements can be adjusted in a driver-based way, and that all actions are linked to all of the drivers that they impact. For example, changing sales volumes (or product/customer mix) would have impact not only on sales, but on any post-sales volume-driven activity, such as shipping, invoicing, customer contact, etc. It is important that proper stewardship of the model be employed. Since the model is likely to be used for quick decision-making, it is critical to ensure that corporate subject matter experts are engaged, both in advance and on a regular basis, on the model and action assumptions.
- In a football playbook, for example, a given play includes actions for each member of the team. In our Anaplan model, multiple actions are connected to a single playbook, so that there is a coordinated set of activity around a desired outcome.
- Playbooks are evaluated across each scenario. Consider whether or not driver values would be different for each scenario and over time.
- Leverage other analytics in developing actions. For example, in our model we leverage activity-based costing information to identify low-profitability products and customers and target those for action under adverse scenarios (Figure 5).
Figure 5: Profitability analysis can inform potential actions
- Consider if given actions would create positive outcomes under any scenario. In this case, the business may choose to implement this action immediately. Similarly, evaluate whether a given action now would insulate from any down-turn scenario. Like buying insurance, the cost of extra capacity could be carried if it produces sufficient optionality for the business.
Anaplan is an incredible tool for scenario-based planning. Use the approaches outlined here to help boost your ability to forecast the future and evaluate alternative action plans that will enable your business to survive and thrive during changing times.
Please share your comments or reach out if you would like to discuss any specific issues in your business.