Data critical for food and beverage companies to improve insurance renewals
As food and beverage companies across Australia leverage data to improve insurance renewal outcomes – in particular relating to property and business interruption risks - they can use the same information to become more resilient.
The world today looks much different than it was merely a year ago. The challenges of 2020 have seen many food and beverage companies scramble to adapt, face supply chain difficulties, introduce new health and safety measures to keep their employees safe, recover from natural catastrophes, and respond to calls for increased social justice.
As food and beverage companies continue to recover from the difficulties of the past year, they are also challenged by escalating insurance pricing and tightening terms and conditions. In the Pacific region, which includes Australia and New Zealand, property insurance pricing continued its upward trend for the fourteenth consecutive quarter since Q4 2017, albeit that results for Q1 2021 showed a more moderate increase compared to the prior quarters in 2020.
Further, the renewal process is becoming more taxing as underwriters closely scrutinise submissions and ask more questions than in the past. More than ever before, underwriters expect data-focused responses that provide details about the risk profiles of insureds’ locations and the time and cost to rebuild any damaged properties.
In Australia, the level of scrutiny now imposed by insurers around the likes of contingent business interruption, accumulation risk and catastrophe risk are key drivers of renewal outcomes, and often are the difference between insurers providing affirmative cover versus no cover at all.
Fragmented data complicates analysis process
Food and beverage companies possess copious amounts of data. Yet, some risk professionals may find it difficult to leverage existing information to support their insurance renewal process.
One main difficulty revolves around accessing data. Even when such information exists in-house, it is frequently dispersed across different departments. For companies with more than one location and with information spread across each of these properties, it may be time-consuming to analyse location-specific data, such as type of roof construction or sprinkler coverage and type.
Even when risk managers are able to gather all available information, they are often faced with data that has been captured using diverse methodologies or by different individuals. Having “unclean” data in different formats and systems can make company-wide analyses geared towards identifying potential problems more difficult.
"Fragmented data, different collection methodologies complicate the analysis process."
Let’s take the example of an agricultural manufacturer with hundreds of sites across the globe. The company wants to identify potential weaknesses across its properties. Each location possesses detailed information, such as data about roof age, fire protection technology and building construction materials. But it has been collected in different ways, presented in different formats and stored in different locations, making it hard to bring all the data together and conduct a thorough analysis of risk quality.
Carriers interested in resilience strategy
Aside from the risk engineering attributes of different properties, carriers are also expressing keen interest in companies’ efforts to become more resilient. Property underwriters want to understand organisations’ efforts to improve their business continuity plans and remain operational — or reduce lost time — following different disruptions. This includes demonstrating the ability to get crucial supplies following a crisis, or the true capacity to ramp up production at an alternative location to make up for downtime at a plant that cannot operate for some time.
Underwriters have traditionally focused on locations generating the most revenue, since these tend to suffer bigger losses. However, they are now asking for risk management information about smaller locations. While losses in the latter tend to be less severe, they are also typically more frequent, leading to a higher aggregation of costs.
In today’s data-centric renewal process, food and beverage companies should focus on gathering the necessary information and making sure that data is comprehensive, verifiable, and accessible. To ease the burden of data collection, it may be helpful to think in terms of the exposures present at each location. For example, if one location is in a flood-prone zone, insurers are likely to request data on floor elevations and the value of equipment below grade.
"Information presented to underwriters needs to be comprehensive and verifiable, based on sound methodology."
Understanding the potential exposures of each location allows companies to purchase the coverage that best meets their needs, both for property damage and business interruption policies. Let’s take the example of a poultry processing plant that makes up around half of a company’s revenue. Senior leaders should understand how that particular plant could be affected by different risks, from a short power outage to a natural catastrophe that destroys part of the building and seek to answer questions, including:
- Can production be diverted to other plants?
- Can equipment that is still operational be moved to another location?
- How much will risk mitigation measures cost and what is the long term cost of not being able to fulfil orders?
- What will be the potential loss of revenue after shutting down production for a specific period of time?
As carriers scrutinise each application and are increasingly judicious about the risk they are willing to take, in-depth analysis that demonstrates the effectiveness of mitigation plans can help food and beverage companies secure needed coverage at the best available price.
Identifying location-specific challenges
The ability to answer underwriters’ questions is not the only benefit of a data-focused risk management policy. As companies continue to recover from the various challenges of 2020, they should remain focused on becoming more resilient and in order to succeed, they should identify the wide spectrum of possible risks they could face and measure their potential effects.
Food and beverage companies should not limit such exercises to their own locations but also understand the potential vulnerabilities of their critical suppliers.
When properly collected and analysed, data can help organisations identify vulnerabilities, which in turn allows them to address challenges before they become costly problems. For example, comparing the locations of its known suppliers to drought conditions worldwide can help a grain-processing firm understand where shortages might occur during next quarter’s harvest and supply, allowing the organisation to dynamically adjust its product strategy to account for such shortages.
Best-in-class companies have strong data quality and risk management information that can be converted into dynamic dashboards that allow risk managers to clearly visualise the state of play. This is the path taken by the global agricultural manufacturer in our earlier example; the company created a centralised property database that allows risk managers to analyse concentration of risk across geographies and product lines, among other categories.
This holistic view allowed the company to triage response and strategy based on the severity of challenges. Further, a single view of all data allowed risk managers to visualise vulnerabilities across different product lines, allowing them to focus on specific products that present the highest risk based on value and vulnerability.
A similar approach can be applied to supply chain analysis. A packaged food company, for example, may source a crucial ingredient from different sources. But analysis of geographic data uncovers that the majority of suppliers are in a specific, earthquake-prone region. A single catastrophe could disrupt the company’s supply chain, leaving it with a critical shortage of an important ingredient.
"Companies can use data to identify single points of failure and address challenges before they become costly problems."
When risk managers are able to analyse information about physical assets, such as buildings, inventory, and equipment, together with data from key business partners, they can better determine the effect of different perils on each location.
The events of 2020 underscore the need for businesses to be resilient and able to withstand a variety of shocks. Food and beverage companies should implement data-driven risk management plans that allow them to continuously collect, analyse, and leverage data. These insights can help companies identify risks and develop robust mitigation strategies, which, in turn, can help them negotiate more competitive insurance pricing and the terms suited to their needs.
As such, risk analysis exercises (such as business interruption reviews, catastrophe modelling and business continuity planning) should form part of an organisation’s insurance pre-renewal planning and strategy.
If you have any questions in relation to this article or would like to discuss your risk and insurance needs, please reach out to your Marsh representative or contact us here.
This article and any recommendations, analysis, or advice provided by Marsh (collectively, the ‘Marsh Analysis’) are not intended to be taken as advice regarding any individual situation and should not be relied upon as such. The information contained herein is based on sources we believe reliable, but we make no representation or warranty as to its accuracy. Except as may be set forth in an agreement between you and Marsh, Marsh shall have no obligation to update the Marsh Analysis and shall have no liability to you or any other party with regard to the Marsh Analysis or to any services provided by a third party to you or Marsh. Marsh makes no representation or warranty concerning the application of policy wordings. Marsh makes no assurances regarding the availability, cost, or terms of insurance coverage. LCPA 21/128
