With hybrid working set to become the new normal in the UK insurance industry, brokers are addressing both the challenges and potential benefits. In particular, remote working has given rise to new data management challenges, while also exacerbating pre-existing issues. In this article, well explore the top data challenges brokers face, as well as how they can be solved.
Data Challenge #1: Maintaining data security whilst retaining customer-centricity
Brokers know that data security is vital, but without the ability to view all the data you have on a given customer in one place, its challenging to provide best-in-class service. Any customer data has to be kept secure and private.
Remote working threatens data security in three main ways:
- Staff may be saving data on their personal devices, where it is vulnerable to being lost or hacked,
- With staff extracting data from multiple systems and sending it to each other in multiple static Excel files, more customer data is likely to be lost or inaccurate through human error,
- Remote access increases the vulnerability of a brokers entire network.
A cloud-based broking system that regulates access to customer data through a secure online portal means that data cannot be lost. It minimises the opportunity for human error and should provide world-class security via regular automatic updates.
Todays end-to-end broker systems come with true CRM (Customer Relationship Management) capability. This not only allows the broker to assess customer needs holistically, but securely. Are there other parts of the customers business that lack coverage? How does your customers cover compare with their peers? Could you get them better levels of coverage for similar premiums?
Data challenge #2: Data quality and accuracy
As a result of the factors mentioned in the previous paragraphs, data quality remains a pressing issue for many brokers. Manual processes mean that data must be checked and rekeyed multiple times. Each time this happens, it increases the likelihood of human error.
In many broking businesses, information is still stored in static spreadsheets and on paper in in-trays, filing cabinets, and post-it notes. While such data may be accurate, it is impossible to work with remotely. Manually transposing this data onto spreadsheets or other digital documents again increases the likelihood of human error.
Consolidating data from various sources onto a cloud-based system that allows secure, real-time access through a single portal allows for automated workflows, shared data, and reduces rekeying to an absolute minimum. Edits can be traced, and inaccuracies discovered and resolved quickly.
Data challenge #3: Data culture drives transparency and productivity
For many brokers, the biggest challenge to improving data quality starts with the business culture. Does a company have a data-led culture? In many cases the answer is no. We commonly hear:
My staff dont want to spend time keying in data when they could be spending time on new business and renewals
This can be exacerbated where brokers work with a mix of front and back office systems. Virtually no brokers have a complete 360 degree-view of all their data in one place that they can access remotely. This makes it difficult and time-consuming to create MI reports. Many brokers put up with this because it is simply business as usual.
Remote working has brought this issue to the forefront as now its clear that most senior managers and executives are unable to measure productivity. They dont have the data to know how much time is being spent servicing particular customers, or which employees are most profitable per hour.
There are several ways to manage a change in culture. From the brokers we spoke to, the main recommendations are:
- To show employees the time-saving benefits of working with data,
- To automate workflows wherever possible, so tasks are flagged automatically where staff members need to add data, and tasks are marked as incomplete until they do so,
- Offering training when adopting new systems and processes,
- Appointing a senior executive to oversee the adoption of new systems and processes,
- Finding champions within your business people who see the need for change and are willing to help promote it among their colleagues.
Once this culture is widely adopted, it will foster data visibility and transparency. Forward-thinking brokers are able to view critical business data in almost any way they choose, allowing them to monitor a range of data points, such as lack of movement on claims actions, outstanding quotes, outstanding invoices, etc.
Finally, its clear that once metrics can be applied to business as usual (BAU) processes, they can be measured and managed appropriately. This allows senior managers to track productivity in whatever way they wish by customer, by employee, or by line of business.
Data challenge #4: Data monetisation and understanding profitability
Most brokers know which customers generate the highest revenues. However, not many are able to prove how profitable that customer is. Are staff spending so much time servicing the customer that it becomes less profitable than your smaller customers? How much does that customer generate per hour, and what is the cost of servicing them?
This is largely thanks to siloed data and the manual effort of creating reports. This accounts not just for an inability to measure the problem, but also the ability to address profitability. Too many brokers miss opportunities to cross-sell or upsell cover to their customers, due to not having a holistic view of the account.
Forward-thinking brokers are deploying profitability analysis. This is another kind of actionable intelligence that analyses the profitability of a brokers customers. Their system can track time spent on the account and also integrate with diaries, payroll, and expense systems, and even mapping tools to understand how much FTE resource is being spent servicing every account.
With actionable intelligence, brokers can uncover cross-selling opportunities easily. Indeed, best-of-breed systems will flag cross-selling opportunities automatically if the brokers set the right parameters into the system.
For example, actionable intelligence can automatically compare a customer to its peers to gauge the types of cover they might buy, and highlights to the broker where that customer doesnt appear to have coverage, creating an opportunity for more business.
Data challenge #5: Remote system access and engaging with the eco-system
One of the biggest challenges cited by brokers has been inconsistent access to remote systems. They struggle with limited bandwidth or slow system performance due to the sheer number of employees who must log-on remotely at the same time. Similarly, many broking businesses simply cannot access all their data remotely because some of it is still held in on-premises servers.
In 2021 and beyond, brokers will need access to a range of online platforms and applications to do business, from Office 365 and Teams to trading platforms like Whitespace and PPL for the London market. For those brokers who work in the delegated authority space, the ability to integrate with Lloyds common data standards platform will also become essential.
At the same time, brokers need to be able to interact with customers and customers seamlessly online.
A best-of-breed, end-to-end broking system allows secure, remote access to all your key data in one place. With the right infrastructure, the system offers guaranteed levels of performance and availability, promising remote access on any device from any location via a web browser.
Many brokers see this as the next step for their business transformation to empower their brokers to do business on the move and be able to access real-time data at any time.
The future trading environment is heading towards an eco-system, knitted together by APIs (Application Programming Interface). Access to this eco-system will depend on brokers deploying open systems that allow them to integrate all their data fields with other business-critical systems and applications. Best-of-breed systems now have this capability built in for all data fields, meaning that brokers do not need to change the systems using code, or ask their system provider to make time-consuming or expensive tailored modifications.