- Splits should be at the highest possible level (break down into the biggest possible chunks)
- Each split branch should be variable, specific and measurable
- The branches should fully define the split above
Identifying the problem
Measure, Prioritise, Action (MPA)
The Measure, Prioritise, Action tool is a simple and powerful tool which enables us to diagnose a problem through the prioritisation of its drivers, the tool brings clarity to complex challenges by doing so it empowers us to clearly articulate and congregate around the case for change. This approach to problem solving is data driven, and enables us to differentiate between fact and anecdote to inform impactful action and through monitoring of a key measure we are able to focus on a key measure which requires improvement, to remain improved.
The approach has 3 sections to its application and supports us to plan out meaningful change initiatives.
- The ‘measure’ is the identification and measuring of a key metric, against an ideal world scenario. This allows us to understand the scale of a complex dilemma by comparing it to an ideal situation and by doing so allows us to form an accurate understanding of the best-case state and taking a data led approach to improvement. For example, 56% of adults in ASC receive their ideal outcome.
2. Finally, by this stage we have a clear view of where action is required, and we can prioritise the actions and resources to resolve the most valuable drivers and problems to maximise our impact. For example, dedicated time and space to focus on solution finding.
3. Action - We then prioritise using a ‘pareto’ – this is an ordered bar graph that displays the causes of inefficiencies in descending order. This breakdown of the drivers of the dilemma provide a clear and enhanced understanding of the impact of resolving each area, this approach helps us to prioritise where we can have the biggest impact against the ‘measure’. For example, breaking down the 44% of adults who did not receive their ideal outcome from ASC, in order to analyse key drivers influencing non-ideal outcomes. This could be ASC decision making or lack of an MDT approach. These drivers inform our improvement themes.
Split solving complex dilemmas requires a structured and disciplined approach, the approach is very effective and enables us to drill down to the root cause of a problem. The split solving approach enables us to apply a structure to identify problems, prioritise them and then highlight long term solutions that will have the biggest impact. We do this by breaking down a key variable in order to understand the different variables that drive it. For example, we could break down Value of Reablement (£/week) into 2 further variables of the number of adults who completer their Reablement package over a weekly period, and the reduction in ongoing care hours for completers (hours / week / Service users). These variables Demonstrates the relationships between the key variables of a problem and Helps to understand the impact of a specific variable on a KPI.
The approach has 3 stages to its application and supports us provide clarity to complex dilemmas:
- Firstly, we need to clearly identify the problem and describe the problem in maximum detail, this is our problem statement.
- The second step is to identify the root cause.
- Finally, we can implement the action to address the root cause to the problem.
- Close a split if it’s performing correctly, or if the cause is understood
- Split down further if the split is performing incorrectly
- Repeat until we know the root cause (or combination of root causes)