Brokers may not be getting the most out of MI, says Jeff McCracken
Using computer-based systems to broker insurance delivers enormous benefits, not the least of which is the automatic capture of data. It is widely accepted that unlocking this management information (MI) can help steer a business to success. However, in reality, few organisations make the best possible use of this information to influence their business operations for the better.
Insurance broking software providers represent invaluable partners in helping brokers make good use of their MI. Brokers, however, must be willing to use the system correctly, invest in training and extend MI solutions beyond senior management if they are to maximise the benefits that MI can deliver.
Optimising the quality of the captured data is the basis of all good MI and the following tips should ensure that data is consistent and reportable.
- Implement a good system training program: this will maximise the efficiencies a system has to offer and contribute to improving the quality of data.
- Enforce system usage through available configuration options: making field population mandatory, where appropriate, will prevent inconsistent use of fields and therefore systematic gaps in data, allowing business activity to be reliably categorised for analytical purposes.
- Promote best practice within the organisation: publish process guides and encourage completion of risk capture. Bypassing the system or updating it retroactively in a batch manner will result in missing or skewed data. This makes it difficult or impossible to perform any meaningful analysis on areas such as lead and quote response time analysis, industry segment client analysis and client retarget success rates.
- Create appropriate task workflows and ensure that they are followed. These should reflect real-life processes so that users are comfortable using them. The progress rate and completion times of workflows can then be monitored to identify issues with performance, service levels or compliance. With measures in place to maximise data quality, the focus can turn to driving well-informed decision-making to the heart of the business model through the effective use of MI.
- Improve accessibility to MI solutions that are intuitive and not overly complicated to use. A poorly-designed user interface, or one that requires database or coding knowledge, will not yield benefits and will likely result in inefficient attempts to extract results.
- Raise awareness of the MI analysis tools available. Ignorance among management of the MI solutions available and how to access them is a common cause of frustration within an organisation.
- Expand availability of appropriate MI analysis tools beyond senior management. This enhances individuals’ views of their personal or team’s performance and encourages a culture of self-management and motivation. The same MI tools should be used to ensure a standardised set of performance indicators is in use across the organisation resulting in a common view of data for those at all levels within the firm.
- Provide MI solutions training to all those with access in the organisation. This often overlooked aspect improves users’ ability to interpret results and take appropriate actions. It also dispels any confusion that would discourage users from trying to make use of a powerful but complex MI solution or, worse, misunderstandings that could result in incorrect conclusions.
- Give users freedom to navigate and drill into/across the data available to them. Encourage the use of MI tools for data discovery and ensure users regularly present the results of their MI analysis, discuss conclusions and resultant actions. This will help improve understanding of the business and drive a greater desire for identifying improvements from users and management at every level of responsibility.
- Ensure users can share their saved views on data for use by others within their organisation. This should be possible on any good solution, and helps to improve understanding of the MI solution and the business as a whole, as well as encouraging further discovery
Establishing the foundations to enable meaningful conclusions to be drawn from the data generated is essential. It is equally important to identify which individuals could benefit from a greater exposure to the data relevant to them and training them to ensure they can maximise its use.
Encouraging discussion of analysis methods and conclusions, as well as sharing of discoveries, will help motivate those with responsibility at all levels to identify improvements in their area and tackle these proactively.
If brokers want to build a more dynamic, responsive and efficient business then investing the effort to get more people within a company using MI constructively may be one of the most significant changes they can make.