Tag Archives: Robinson

How to Prepare Your Firm for Winter

Disasters can happen in an instant, or they can come with some warning. There is usually some notice when there is an impending winter storm, but, all too often, people are still caught by surprise. When looking at the winters of 2015 and 2016, winter storms hit in some areas of the country that were not accustomed to such harsh conditions. This only proves winter storms can happen anywhere, no one is immune and, if you have a business, you need to be prepared.

When people hear “winter storm,” they usually think about snow or blizzards — and that is certainly part of it. But winter storms can also bring high winds, ice and freezing rain. There could also be a combination of any of these conditions. This can result in power outages, downed trees, unsafe roads and other situations that make it dangerous to be outside.

Statistics show nearly 25% of disaster-affected businesses never re-open. It doesn’t matter if that disaster is a winter storm, flood, hurricane or some other tragedy. Any business is vulnerable, but small businesses are especially at risk. They tend to have fewer employees who are able to get the business up and running again and assist in recovering losses. They also have less capital available to start over or even recoup losses.

Creating a Business Emergency Plan

A good business emergency plan could be the key to allowing your business to recover and resume operations after a disaster. This sample business emergency plan from Ready.gov is a good place to begin.

First, identify the address where your business will operate, then identify a secondary location should the first become inaccessible. Next, appoint someone as the primary crisis manager for your business and designate a backup if that person is unavailable. Assemble a crisis management team and find other businesses that you can network or coordinate within a disaster.

See also: Getting Beyond Risk in Insurance M&A

After this, determine and prioritize your critical operations as well as who is in charge and what he/she needs to do when the emergency plan goes into effect. Also, list your suppliers, vendors and contractors — their contact information, what they supply and how to reach them. Then, identify an alternative for each, perhaps outside of the affected area or businesses that can get to you if the roads are closed.

Include these elements in your emergency plan:

  • Evacuation plan
  • Shelter-in-place plan
  • Crisis communications plan
  • Cyber security plan
  • Records backup
  • Employee contact list

Your plan should be updated annually and after any emergency event. After a crisis, it is important to review your plan, assess its effectiveness and document any lessons learned — then make adjustments accordingly.

Prepare Employees

Most cities have text or SMS alerts for severe weather. Encourage your employees to sign up for alerts and download weather apps so they can keep an eye on the weather. Provide information on putting together an emergency supply kit, securing important documents in a safe place and creating a family communication plan so they can be prepared at home. Your employees are more than just workers in your business, and part of continuing operations means ensuring their personal safety.

Make information about winter storms accessible to your employees, especially if you are in an area where winter storms are somewhat uncommon or if you have employees who are from such areas. Have a meeting to discuss these things with your employees and help them prepare. Review various scenarios, problems and potential resolutions for both work and home.

Prepare your Business

Use this 12-point checklist to get your business winter-ready:

  1. Review your insurance policy and coverage. Some policies offer financial protection for business interruption because of severe weather. Also, make sure your policy adequately covers your business and the property it is on.
  2. Replace old doors and windows, ensuring there are no gaps or cracks where cold air can seep in.
  3. Clear your gutters of all debris.
  4. Make sure your pipes are properly insulated, even if you live in an area that does not typically get severe winter weather.
  5. Don’t leave any building unheated for any time, even if it is empty. The pipes can freeze, which has the potential to cause serious problems.
  6. Check outside for dead trees or branches that are low-hanging or weak. Wind can cause a tree or branches to fall. Ice can accumulate on branches, creating what is called a “widow maker,” which is a deadly branch that can fall suddenly when it breaks under the burden of the ice.
  7. Inspect your roof for any loose shingles for issues that could present problems during a storm.
  8. Hire a pro to inspect your heating systems.
  9. Invest in a good generator. Even if the power goes out, a generator can keep your business operational.
  10. Create a plan for ice and snow removal. Ice and snow are significant liability risks as a safety hazard. They also have the potential to cause severe structural damage and can prevent your customers from being able to get to your business if you are able to remain open.
  11. Teach your employees how to manually process credit cards and ring up customers. If you are a retail establishment, this is particularly crucial, but it can allow you to still make sales transactions even if you don’t have internet access. You will need to have a detailed inventory and make precise notes on what is sold so that the information can be entered once your business is back online.
  12. Back up your data. Many businesses purchase cloud technology to back up their data, but if you have sensitive information you should get professional assistance. You can also back up offline as well using an external drive.

See also: Riding Out the Storm: the New Models

Winter storms should be taken very seriously. Prepare your business and ensure continued operations or decrease your downtime. You don’t have to become a statistic. No business has to fail after a disaster if it is properly prepared.

‘Jobsolescence’: How Big a Threat?

“I think the guiding principle for government should be to protect and enable/retrain the worker, not protect the job. Policy makers and educators should focus on making sure that workers are as equipped as possible to transition to new opportunities…” —Peter Robinson

A recent OECD report finds that low- and middle-income earners have seen their wages stagnate and that the income share of middle-skilled jobs has fallen. Rising inequality has led to concerns that top earners are getting a disproportionate share of the gains from global “openness and interconnection.” This summer, the OECD Employment Outlook 2017 revealed that job polarization has been “driven by pervasive and skill-biased technological changes.”

Founded in 1945, the U.S. Council for International Business (USCIB) builds awareness among business executives, educators and policy makers around issues related to employment, workforce training and skills enhancement. CMRubinWorld spoke with USCIB president and CEO Peter M. Robinson, who serves as a co-chair of the B20 Employment and Education Task Force, through which he helped develop recommendations to the G20 leaders on training for the jobs of the future. Robinson also serves on the board of the International Organization of Employers, which represents the views of the business community in the International Labor Organization.

Peter, welcome. How severe do you believe jobsolescence will be over the next 20 years? How big will the challenge be to offset it and maintain a growing workforce?

I really don’t think the overall effect will be as dramatic as some people fear — at least for the medium term, as far as we can tell. There is an over-hype factor at play, but the consequences still deserve serious attention. For one thing, so many of the jobs in the U.S. and other advanced economies are in the service sector and involve interacting with other people. Despite all the advances in AI, we are still a long way off from robotic nurses or home health aides. Overall, history tells us that at least as many new jobs are created as are displaced by technological innovation, even though transitions can be difficult in some sectors and localities, and as long as upskilling takes place.

“The biggest threat is that our educational institutions won’t be able to keep pace with new skills demands.” —Peter Robinson

What do you think are the biggest obstacles facing college grads today trying to enter the workforce?

I actually think the greatest obstacles are faced by those who don’t make it to college or some form of higher education beyond high school (a four-year degree is not the right path for everyone). A 2014 Pew survey found that among workers age 25 to 32, median annual earnings of those with a college degree were $17,500 greater than for those with high school diplomas only. Obviously, everyone at whatever educational level needs to keep their skills sharp, and governments should join with employers and educators to instill better life-long learning. But there are far fewer established paths toward long-term employment at a middle-class level of income for those who don’t graduate from college. A greater emphasis on vocational education and apprenticeships would help. We strongly support the work being done by Secretary of Labor Acosta to promote apprenticeships.

See also: The Sad State of Continuing Education  

Given that machines are in the process of stripping white collar workers from their jobs, what kind of skills are key manufacturing and service industries going to need from new employees?

I think the premise of your question is overstated. We’re all being told that our jobs are doomed by robots and automation. But the OECD estimates that only 9% of jobs across the 35 OECD nations are at high risk of being automated — although, of course, even 9% can be generative of social difficulties. But there is an established track record across history of new technologies creating at least as many new jobs as they displace. Usually these new jobs demand higher skills and provide higher pay. The biggest threat is that our educational institutions won’t be able to keep pace with new skills demands.

“It is becoming clear that versatility matters in a constantly changing world, so Jim Spohrer’s IBM model of a “T-shaped” person holds true: broad and deep individuals capable of adapting and going where the demand lies.” —Peter Robinson

In an economy with a significant on-demand labor force, what competencies will these workers need to compete?

There are two types of competencies that will be needed: “technical”  or, in other words, related to deep knowledge of a specific domain, whether welding or optogenetics; and “transversal,” which applies to all occupations. Those are described by the Center for Curriculum Redesign as skills (creativity, critical thinking, communication, collaboration), character (mindfulness, curiosity, courage, resilience, ethics, leadership) and meta-learning (growth mindset, metacognition).

How will managerial skill requirements change as a result of major structural changes that are likely, including human replacement by machines and growth of the on-demand economy?

OECD’s BIAC surveys of 50 employer organizations worldwide has shown that employers value not just skills as described above but also character qualities, as well. Further, it is becoming clear that versatility matters in a constantly changing world, so Jim Spohrer’s IBM model of a “T-shaped” person holds true: broad and deep individuals capable of adapting and going where the demand lies.

“We often hear about the need for more STEM education. But I think there is an equal need for a greater emphasis on the humanities and the arts, for their intrinsic value, as well as for developing skills and character qualities.” —Peter Robinson

What central changes in school curricula do you envision, both at the secondary school and college levels?

We often hear about the need for more STEM education. But I think there is an equal need for a greater emphasis on the humanities and the arts for their intrinsic value, as well as for developing skills and character qualities as described above. As David Barnes of IBM wrote recently, these skills are more durable and are also a very good indicator of long-term success in employment.

See also: Innovation Maturing Into Major Impacts  

How can the evolving changes in competencies required for employment be effectively translated into school curricula? Where are the main opportunities to enable this? Assessment systems? Business/education collaboration? Curriculum change?

I’d go back to something else David Barnes said: We need much stronger connections between education and the job market, in the form of more partnerships among employers, governments and education institutions. Everyone needs to step up and create true partnerships. No one sector of society can address this alone. OECD’s BIAC has also documented employers’ wishes for deep curricular reforms to modernize content and embed competencies to meet today’s market needs.

What role should government play in ensuring citizens receive a quality and relevant education given the challenges that lie ahead?

I think the guiding principle for government should be to protect and enable/retrain the worker, not protect the job. Policy makers and educators should focus on making sure that workers are as equipped as possible to transition to new opportunities as these develop, and on ensuring that businesses have the freedom to pivot and adopt new technologies and business processes.

The article was originally published on CMRubinWorld under the headline, “The Global Search for Education: Jobsolescence – A Conversation with USCIB President and CEO Peter Robinson.” 

Top 10 Changes Driven by Insurtech

With 2017 Insuretech Connect happening this week, below is one industry insider’s top 10 of the notable insurtech changes since the inaugural event this time last year:

See also: Insurtechs: 10 Super Agents, Power Brokers  

  1. Early-stage ventures are moving beyond the online/UI experience and are focused on the core industry economics — i.e. driving down the 56 cents of every premium dollar that is indemnity (loss costs), the further 12 cents needed to assess, value and pay those losses, and the circa 26 to 30 cents required to develop, distribute, select and price product.
  2. There is an increased presence of early-stage-focused VCs that have insurance chops, meaning that high-quality startups focused on more complex industry issues have smart capital for funding (there wasn’t much of that last year at this time).
  3. An extraordinary boom in insurtech investment capital means that too many businesses with little chance for success are getting funding. (How many new millennial-focused renters insurance ventures does the market actually need?)
  4. Despite the overwhelming level of capital focused on the space, valuations are generally rational. Yet, there are far too many high-profile investments that seem to make little sense, both in terms of funding levels and valuations. (I can personally attest to being recruited for two roles running pre-revenue startups that received term sheets from investors with pre-money valuations between $30 million and $40 million…exciting for the founder, but irrational in the cold light of day.)
  5. Insurance (viewed by some/many as old school and boring) is showing signs that it can lead in the commercializations of new technologies (IoT, blockchain, telematics, etc.). This can only be positive for attracting “A” talent to our industry.
  6. Lemonade has demonstrated that all of us in the industry can learn something from them. The most recent example is the zero-deductible product (and a no-rate-change protection for as many as two claims), which received unprecedented attention. While this is not new and is already offered by some, the lesson in this case is that being a marketing machine may be worth something (or Dan Ariely, the behavioral economist working with Lemonade, should be hired by us all).
  7. The intractable trend in new risk-taking capital (pensions fund, hedge funds, SWFs, etc.) is leading to “infrastructure light” risk takers — we now have some smart insurance entrepreneurs jumping in with solutions that enable this structural change.
  8. Well-established insurance vertical solution tech companies are now providing attractive exits for insurtech early-stage companies.
  9. Emergence of insurance-specific hot technologies in areas such as chatbots, machine learning and advanced analytics, etc. seems to be leading (in terms of trial by the insurance industry incumbents) the more established, industry-agnostic solutions — watch this space!
  10. The industry is all in on insurtech! Witness the presence of public company CEOs’ commentary on the topic, the abundance of CVCs, the number of corporate intra-ventures, etc. Also compare and contrast year-over-year presence at this conference.

Setting the Record Straight on Big Data

Recently, an article was written on ITL (and published in the Six Things newsletter) that cautioned against the use of big data to change the customer experience when applying for insurance. The article demonized eliminating or even minimizing the plethora of questions required by carriers and, instead, using data from the public domain. In making his point, the author referred to a “startup called Aviva.” Aviva, in fact, is not a startup, but a FTSE 100 company that has revenue in excess of GBP50 billion, has 30,000 employees and has been around for more than 150 years given its Norwich Union and Commercial Union lineage.

The article stunned me. The author’s thinking seems to be of a different era.

In no way am I suggesting that efforts by the insurance community to use data from the public domain to improve customers’ experience is perfect, but the premise of the article showed little understanding for the depth and complexity of information sought by insurers to evaluate and price risk, and the burdens for customers and their agents to provide that information. The article also tried to simplify a complex subject into good versus bad because of specific instances of incorrect information sourced from the public domain.

The evolution in this space is far more robust and advanced than the author seemed to understand.

See also: When Big Data Can Define Pricing  

As society has evolved, so have the sources and accessibility of information, and so has our decision making. We don’t rely on the first return by Google on a search engine or simply get a single return on a product search when seeking a product on Amazon. The same rules apply when humans make decisions – they seek input from multiple people. Insurtechs seeking to navigate the big data domain are addressing the challenge by applying this real world behavior — reducing the demands for customer information by understanding the context and bringing data together from a variety of sources, often with a high degree of veracity.

Terrene Labs, a SaaS provider to the carrier, MGA and broker community is among the most compelling examples. Terrene has managed to reduce the 150 to 200 questions required to place a property and liability, work comp and auto cover for small business customers (the $100 billion market of companies with as  many as 100 employees and $10 million in revenue) by requiring only four pieces of data. Terrene assembles data fragments from more than 900 sources (insurance-specific, non-insurance, private data sources, etc.) to generate all the information for a completed application (as well as additional relevant risk information not sought by carriers). Terrene does not have static rules of sourcing data (despite what the author suggested) but uses machine learning and artificial intelligence to dynamically source data based on algorithms that value veracity. The results are far more impressive and the process to achieve this far more complex, than the author of the referenced article seems to understand.

A powerful example that illustrates the point is determination of NAICS or SIC code, which is the basis for all carriers’ risk appetite selection and the basis for pricing. Terrene’s proprietary techniques are far more accurate than the process an agent CSR typically uses to determine class of business. A customer that identifies her business as a “cabinet store, maker and installer” could be properly categorized as a NAICS classification of 337 (furniture and related product manufacturing) or a NAICS code 444190 (kitchen cabinet store). The Terrene engine can properly determine which category is appropriate with an extremely high degree of accuracy. This accuracy ensures that appropriate carriers for this risk can be identified without the risk of rejection further into the submission/quoting process, frequently a pain point and a significant source of inefficiency and yield loss.

Big data, if done well, can improve the quality as compared with a customer’s self-reporting, which typically has an element of bias. For example, in a surety context, over a large sample set from one carrier, none of the customers reported prior bankruptcies. The Terrene solution, in fact, determined that 16% had a prior bankruptcy. Similarly, powerful insights into risk profile that are typically not sought by carriers can now be generated. For example, Terrene profiles characteristics in the risk that are not consistent with self-reporting of profession or trade – one recent example was a home remodeler that carried an asbestos remediation license.

See also: What Industry Gets Wrong on Big Data  

The evolution of big data is a work in process, so companies are taking different approaches in their journey. One such example is a company that uses the Terrene capability to pre-populate an application that then can be reviewed and affirmed by a customer before a submission is made – a process that customers report is far more effective than self-completing a 200-question set (which typically takes two-plus hours), not to mention the substantial improvement in information veracity. Unfortunately, like the article referenced at the outset, not enough positive attention is being taken to understand these powerful advancements that leaders such as Terrene can deliver now.

Insurtech Is Ignoring 2/3 of Opportunity

Fifty-six cents of every premium dollar is indemnity (loss costs). A further 12 cents is needed to assess, value and pay those losses. Given that two-thirds of the insurance industry economics are tied up in losses, it would be logical that much of the innovation we are now witnessing should focus on driving down loss costs and loss adjustment expense — as opposed to the apparent insurtech focus on distribution (and, to a lesser extent, underwriting).

This is beginning to happen.

What do you have to believe for loss costs and adjustment expenses to be a prime area of innovation and disruption? You have to believe that the process (and, thus, the costs) to assess, value and pay losses is inefficient. You have to believe that you can eliminate the portion of loss costs associated with fraud (by some estimates, as much as 20%). You have to believe that there is a correct amount for a loss or injury that is lower than the outcomes achieved today, particularly once a legal process is started. You have to believe that economic improvements can happen even as customer experience improves. And you have to believe that loss costs and adjustment expenses can decline in a world in which sensor technology starts to dramatically reduce frequency of losses and manufacturers embed insurance and maintenance into their “smart” products.

See also: ‘Digital’ Needs a Personal Touch  

Having spent years as an operating executive in the industry, I happen to believe all of the above, and I am excited by the claims innovation that is just now becoming visible and pulling all of the potential levers.

We are seeing an impact on nearly all aspect of the claims resolution value chain. Take a low-complexity property loss. Technology such as webchat, video calls, online claims reporting and customer picture upload are all changing the customer experience. While the technologies aren’t having a huge impact on loss adjustment or loss costs, they are having profound impact on how claims are subsequently processed and handled.

One such example, as many have heard, is how Lemonade uses its claims bot for intake, triage and then claims handling for renters insurance. Lemonade’s average claim is a self-reported roughly $1,200 (low value), and only 27% are handled in the moment via a bot as opposed to being passed to a human for subsequent assessment. Still, Lemonade certainly provides a window to the future. Lemonade is clearly attacking the loss-adjustment expense for those claims where it believes an actual loss has occurred and for which it can quickly determine the replacement value.

More broadly, Lemonade is a window into how many are starting to use AI, machine learning and advanced analytics in claims in the First Notice of Loss (FNOL)/triage process — determining complexity, assessing fraud, determining potential for subrogation and guiding the customer to the most efficient and effective treatment.

While Lemonade is the example many talk about, AI companies such as infinilytics and Carpe Data are delivering solutions focused specifically on identifying valid claims that can be expedited and on identifying those claims that are more questionable and require a different type of treatment. These types of solutions are beginning to deliver improvement in both property and casualty. New data service providers — such as Understory, which provides single-location precision weather reports — can be used to identify a potential claim before even being notified, which can reduce loss costs through early intervention or provide reference data for potentially fraudulent claims.

Equally interesting is the amount of innovation and development appearing in the core loss-adjusting process. Historically, a property claim — regardless of complexity — would be assessed via a field adjuster who evaluates and estimates the loss. Deploying technical people in the field can be very effective, but it is obviously costly, and there is some variability in quality.

In a very short time, there are very interesting new models emerging that reimagine the way insurers handle claims.

Snapsheet is providing an outsourced solution that enables a claimant of its insurance company customers to use a service that is white-labeled for clients. The service enables the claimant to take pictures of physical damage, which is then “desk adjusted” to make a final determination of the value of the claim, followed by a rapid and efficient payment.

WeGoLook, majority-owned by claims services company Crawford & Co, is using a sophisticated crowd-sourced and mobile technology solution to rapidly respond to loss events with a “Looker” (agent) who can perform a guided process of field investigation and enable downstream desk adjusting process, as well.

Tractable provides artificial intelligence that takes images of damaged autos and estimates value (effectively a step toward automatic adjudicating). Tractable — like, Snapsheet and WeGoLook — has made great strides. Aegis, a European motor insurer, is rolling out Tractable following a successful pilot. In each of these instances, the process is much improved for customers — whether it be self-serving because they choose to do so (Snapsheet), rapidly responding to the event (WeGoLook) or dramatically reducing the cycle time (Tractable). All provide material improvements in customer experience.

See also: Waves of Change in Digital Expectations  

Obviously, each of these models is attacking the loss adjustment expense — whether through a more consistently controlled process of adjusting at a desk, using AI to better assess parts replacement vs. repair or improving subrogation, among other potential levers.

Today, all of these solutions are rather independent of each other and generally address a low-complexity property loss (mostly in the auto segment), but the possible combination of these and other solutions (and how they are used depending on type and complexity of claims) could begin to amplify the impact of technology innovation in claims.