If there is one aspect of business building that has confounded even the smartest of entrepreneurs, it’s developing the team. The reality is that we simply don’t have the skills to develop their skills, and that can have a long-term and negative impact on the business. Where Are You Today? In 2015, we conducted research for the FPA’s Research and Practice Institute and Financial Advisor IQ that focused on team compensation and benefits. As part of that study, we examined team development, and I was impressed to see that almost all respondents support their team members’ personal and professional development, through training, financial support or continuing performance reviews. At the same time, I noticed that most development initiatives were informal. Although 60% of respondents administer formal performance reviews, development activities such as new-employee training are overwhelmingly informal. The same is true for mentoring. Have Your Considered Mentoring? Mentoring is one development option that is generally considered very effective. Like all such development tools, of course, it’s only effective if it’s done well. Remember that mentoring can mean you being a mentor to the team, someone else on your team being a mentor to others or simply helping your team find outside mentors. It isn’t just an option for large businesses. The reality is that mentoring doesn’t have to be a “time-suck” for you personally, despite its reputation for being exactly that. Today, I want to help you think about taking the first step to understanding where your team needs help and the role that mentoring might play in helping them maximize their potential. See also: The Keys to Forming Effective Teams   What Are Your Gaps? An obvious first step is to figure out what gaps mentoring (or any development activity for that matter) is going to bridge. A performance review process is clearly an important first step. You may opt for a formal tool (such as DiSC, Predictive Index or any of a range of tools) or you may opt for a good old-fashioned conversation with a team member. Whichever approach you take, consider the following in evaluating your team members, ensuring that you cover three potential types of objectives. 1. Performance Objectives

• Success in meeting specific, measurable objectives based on role
• Joint accountability: the ability to work well with and support the entire team
• Attention to detail within sphere of role
• Timeliness in completing work
• Initiative: goes above and beyond defined role

2. Competency/Development Objectives

• Customer service skills
• Sales
• Time management
• Public speaking
• Business writing
• Leadership
• Software skills
• Graphic design
• Financial planning

3. Personal Development Objectives

• Personal improvement goals that the team member sees as important to moving career forward, for example:
• Professional designations
• Training courses
• Advanced Business Training

You might also consider skills assessment tools, which differ substantially from performance review tools.  These tools can be helpful when you are thinking more about getting the right people in the right roles – or who to hire in the first place. Consider the following: Kolbe. The Kolbe A Index is designed to measure the conative faculty of the mind — the actions you take that result from your natural instincts. The index validates an individual’s natural talents, the instinctive method of operation (M.O.) that enables you to be productive. VIA Strengths Test. VIA has identified 24 character strengths that are universal across all aspects of life: work, school, family, friends and community. Whereas most personality assessments focus on negative and neutral traits, the VIA Survey focuses on what is best in you and is at the center of the science of well-being. Strengths Finder. Based on research from Gallup, you access this assessment by purchasing the book. It’s designed to help uncover your talents and incorporates strategies to leverage the strengths you identify. Mentoring Options Mentoring is an option (whether delivered formally or informally, internally or externally) that I believe has a strong potential to have significant impact. Of course, it’s not always easy to get moving. In an interview with Rebecca Pomering for our Spotlight program, we reviewed the three types of mentoring available at Moss Adams. This is a helpful way to think about what you are trying to accomplish and highlights that mentoring can be more or less involved depending on your needs. At Moss Adams, Rebecca explained that there were three types of mentoring available: 1. The Buddy A buddy might be assigned for a new employee. That individual may or may not be involved in the actual job training, but is there to help navigate the office and company. The buddy is someone a new employee can ask any question of and not feel judged in any way. 2. The Mentor A mentor is more traditionally defined as supporting the team member either on a specific topic or skill or on a longer-term basis. Employees may be asked to identify a mentor or go to management if they are looking for support on a specific issue. On some teams, mentors are assigned, but the jury is out as to whether relationships that are not explicitly chosen are as effective. 3. The Sponsor A sponsor’s objective is to actively support and promote the individual in career advancement and development. Sponsors are typically individuals who have the political and organizational connections to make that sponsorship effective. Sponsors may or may not be mentors and vice versa. See also: How to Pick Your Insight Team   Talk to Your Team (First) If you’re considering implementing a mentoring program, ensure you start with clear direction from the team on what will work and what won’t. Below are a series of questions that could form the basis of a survey or a conversation:

• Have you had experience with any form of mentoring? If yes, what form did it take, and how would you describe the impact?
• Do you think it would be valuable for us to consider implementing a mentoring program, which we’ll jointly define?
• How do you think a mentor could help you?
• How would you describe your ideal mentor? What skills, experience or personality traits would he/she have?
• Specifically, what kinds of issues would you hope to address with a mentor?
• Would you prefer to be assigned a mentor or to have support/guidance in finding someone yourself?
• How would you describe the outcomes of a successful mentoring program for you? What would have to happen for you to describe the process as successful?
• Is there anything that you feel definitely wouldn’t work when it comes to implementing a mentoring system?

Talk to Yourself (Not Literally) You’ll also want to get clear on your own goals and objectives for providing or facilitating mentoring. To that end, consider the following questions if you are thinking about finding your own mentor. Or, if it’s for your team, ensure both the mentor and mentee clarify exactly what they’re hoping to accomplish and how they know if they’ll be successful.

• Exactly what are you trying to solve for? Are you looking to develop a specific skill, gain general insights into a specific topic or have someone you can go to for continuing advice?
• How long do you anticipate the mentoring relationship to last?
• How often will you meet, where and for what length of time?
• How will you both prepare for those meetings?
• How do you define success?

Personally, I consider team development one of the most challenging aspects of running a business. We surround ourselves with these incredibly talented people, and it’s easy to feel like you are letting them down. Ultimately, development is about prioritizing and booking the time to do something, even if that something isn’t perfect. Thank for stopping by, Julie

In reading recent reports on insurtech, it was heartening to see the number of insurers that have chosen to gain the market-leading capabilities and tools they need to succeed by partnering with innovators. Many of the major insurers on the list are seeking differentiation, focused on augmenting their product lineup with a new offering, such as State Farm’s and Allstate’s partnerships with Openbay to provide non-collision auto repair services. Others are expanding distribution through a new channel such as an app. In our experience, insurers that start a partnership with an insurtech that focused on a narrow goal, such as gaining homeowners coverage to enhance their existing auto, inevitably expand the relationship, because the right insurtech partnership rapidly positions insurers for greater growth and prosperity. Banking on the Power of an Insurtech Partnership Banking on the digital savvy of an insurtech innovator can deliver powerful results, but in our experience focusing on the following three areas produce the greatest overall outcomes:

• Empower agents: In the initial talk about digital distribution, many assumed that agents would be ousted from their traditional roles and forced into a position of obscurity. We don’t see this happening, and neither do leading insurers, as 50% of consumers still want to speak with an agent when they have questions or concerns.

The problem is, when you put an agent up against the Amazon experience, the agent comes out as woefully inefficient, taking too much of the consumer’s time to manually plug reams of information into multiple back-office systems to generate a quote. See also: What’s Your Game Plan for Insurtech?   Agents are still a powerful force in the industry, but to keep their competitive edge they need the ability to speed the quote-to-issue lifecycle. One leading insurer stands to improve premiums by $100 million to $150 million by the end of this year because it streamlined the agent’s tasks to offer seamless product bundling in a single transaction. Overhauling legacy systems won’t get other insurers there fast enough, but partnering with the right insurtech will.

• Add product and channel choice: I mentioned the Amazon experience above, because it has shaped so much of consumers’ shopping preferences and expectations. As we see by following insurtech funding and partnerships, traditional insurers are realizing the direction that consumers are pushing the industry and, in an attempt to get ahead of the game, are differentiating themselves and the service they provide by partnering with insurtechs to add channel and product choice.

We see tremendous benefits for insurers that focus on meeting more of the customer’s needs. Consider a leading insurer that introduced coverage options by selling other carriers’ products to augment the insurer's auto lineup and added 72,000 policies in less than 10 months. Another gave agents access to additional home products and grew policies sold from less than 8,000 a month to 57,000 a month. Of course, product choice isn’t complete without giving consumers the ability to engage with insurers through their channel of choice. One top-five insurer, well known for digital prowess, has been reported to own quote conversion rates of 35% through agent channels and as much as 53% through direct purchasing. The problem for most insurers comes in attaining digital capabilities and the extensive range of products they need to acquire and retain customers. Developing products can take a year or more, and overhauling legacy technology to add digital channels of engagement and efficiently distribute new offerings is an arduous task. Neither course of action will make traditional insurers competitive before leading digital rivals pass them by. Partnering with insurtech innovators to bundle products from other carriers with their own and distribute them with top-tier digital capabilities, can.

• Streamline the quote-to-issue lifecycle: During a recent advertising campaign, one client generated 3,000-4,000 quotes a day, but not by simply cranking up advertising power or frequency. Instead, the client supported the extended marketing campaign by digitizing the quote-to-issue lifecycle for 80% of desktop traffic and 100% of mobile users. Smart app capabilities and automation allowed consumers to enter minimal information and automatically generate rapid quotes. The experience is similar to Amazon’s product purchasing environment, where customers search for a product, are immediately presented with options and click to buy the items they want. This is the future of insurance, and, by partnering with a leading insurtech provider offering a SaaS-based digital distribution platform, this insurer is providing the future today.

Coming Back for More Insurers that focused on a simple goal, say of improving product selection or extending delivery channels, often expand the relationship to include more offerings and new distribution capabilities. One top-five insurer partnered with a leading innovator to enhance product selection for in-house agents by bundling products with those from other carriers through a digital distribution platform, and three years into a five-year contract signed up to offer additional product options, added 367 agents and extended the relationship to also offer the insurer's products and carrier appointments direct-to-consumer via digital channels. See also: 3 Misconceptions on Insurtech   Why? Because within the first two years, the company found itself presenting 70% of customers with an offer, converting 35% of those quotes and doubling sales year-over-year. With outcomes like these, who wouldn’t expand the relationship? To learn more about selecting the right insurtech innovator to power your growth, download our infographic: InsurTech Innovators Arm Incumbents to Meet the Customer-centric Imperative.

It seems as if everything in the world is becoming “smart” – with intelligent devices and artificial intelligence automating activities and providing new capabilities. There are thousands of examples of “things” that contain embedded sensors or chips that generate information and enable control through apps or automated actions. These come together as part of the Internet of Things (IoT) in various ecosystems – such as smart homes, connected cars, smart farms, and many others. One of the most significant new ecosystems developing has to do with smart cities. The concept of smart cities is gaining momentum, and many cities around the world are developing smart city strategies and implementing specific projects. In fact, it is becoming evident that smart cities are catalysts for the movement to a connected world.

See also: Smart Things and the Customer Experience  

SMA’s recent research report, Smart Cities and Insurance: Exploring the Implications, provides a definition for a smart city. It also profiles leading smart cities around the world, identifies specific benefits and projects underway, discusses how each insurance line of business will be affected, and identifies insurers that are already involved in smart city initiatives. Since the concept means different things to different people, SMA has developed a broad definition:

“A smart city is one that is leveraging connected world technologies to gather, analyze, and act upon real-time data to improve the lives of citizens; enhance mobility; create safer environments; optimize energy consumption and waste management; and contribute to the urban center of the future.” Strategy Meets Action 2017

The findings of the SMA research reinforce the potential for smart city solutions:

• As the global population continues to migrate to cities, smart city solutions will become more and more essential.
• The smart city movement is in full swing in many cities around the world, with hundreds of use cases that have important implications for insurers.
• Mobility, sustainability, and public safety are today’s top areas of focus for the smart city movement.
• Global insurers such as AXA, Allianz, Zurich, and Swiss Re are already engaged in smart city initiatives.
• Every line of business in insurance will be affected as new risks emerge, existing risks are amplified, and opportunities for new insurance products increase.

See also: How Smart Is a ‘Smart’ Home, Really?  

Smart cities may seem like a far-off dream with limited implications for insurance in the next few years. It would be a mistake to take this view. Over half of the world’s population already live in cities, and that percentage will inevitably increase. Some cities already have dozens or scores of smart projects underway, many of which are aimed at reducing vehicle accidents, thwarting crime, improving health, avoiding or mitigating losses to property due to a variety of perils, and many other areas that will result in reduced risks. At the same time, the introduction of new technologies may introduce new risks or increase certain existing risks (like cyber-risk). All in all, it is imperative that insurers take active roles in collaborating with cities and smart city organizations in the reshaping of the modern city.

A major part of Healthcare Consumerism (HC) is related to stress and depression in the workplace. Stress and depression costs (including co-morbid costs) for U.S. businesses are over $200 billion per year according to a 2015 study by the Journal of Clinical Psychiatry. Recognition of the need for stress management can link healthcare, consumerism, and organizational quality, safety, and error reduction programs. In addition, improved product quality and productivity can result with focused efforts to address areas such as stress and depression in the workplace. One thing is certain – if an organization does not have a structured stress management program for employees, it is 100% certain that employees will deal with their stress in other ways (e.g. comfort food, alcohol, drugs, smoking, etc.) U. S. Surgeon General David Satcher once said, “There is no health without mental health.” Similarly, there is no effective program of HC without mental healthcare consumerism. It is a basic requirement for any employer implementing HC plans to deal with stress, depression, and more serious mental illnesses. It is important for employers to understand the clinical and cost inter-relationships between “mind care” and “body care.” Studies show that stress affects an organization in many ways: 1. Healthcare - 21.5% of total health care costs 2. Turnover - 40% of the primary reasons that employees leave a company 3. Impaired Presenteeism - 50% of impaired presenteeism is a function of stress 4. Disability - 33% of all disability and workers’ compensation costs 5. Unscheduled Sickness - 50% of the primary reasons that employees take unscheduled absence days To work for everyone, HC must help the sickest and most vulnerable. Mental illnesses present a unique challenge. Depression is a sickness where patients tend to push away care givers. Many with depression and co-existing physical illnesses will deny their need for care, ignore treatment advice, skip appointments, and are highly non-compliant with medications. A 2014 Kaiser poll showed 48% of employers offer wellness in the workplace. But, a 2013 survey by the American Psychological Association's Center for Organizational Excellence found that despite growing awareness of the importance of a healthy workplace, fewer than half of employees said their organizations provide sufficient resources to help them manage stress (36 percent) and meet their mental health needs (44 percent). See also: How to Improve Stress Testing   Stress has a distinct correlation with medical issues in other body systems. Stress Directions, a leading consultancy on stress, found: “44% of all adults suffer adverse health effects from stress; 75 to 90% of all physician office visits are for stress-related ailments and complaints; stress is linked to the 6 leading causes of death - heart disease, cancer, lung ailments, accidents, cirrhosis of the liver, and suicide.” Stress Directions, Inc. outlines the following relationships: If your plan is not properly dealing with member stress, you will increase the cost of treating the manifestations of stress in those body systems where health costs are covered. These correlations are why well-being is a growing area of interest. Providing support programs for the whole person whether at work or at home will lower health costs and improve productivity. The Occupational Safety and Health Administration (OSHA) has declared stress a "hazard of the workplace.” There are at least three separate, but related costs of stress in the workplace: 1. Direct Mental Health Costs – as separate diagnoses these costs can range from low to high costs. 2. Co-Morbid Condition Costs – many times the more obvious physical health symptoms are treated, but the underlying mental health issue is ignored. 3. Indirect Corporate Costs – these are costs from absenteeism, disability, unscheduled sick days, loss of teaming, relationship conflicts, etc. With the assistance of many national mental health experts and organizations, Healthcare Visions, Inc. has organized a chart showing the relationships among the three types of corporate costs. Companies can no longer treat stress, depression, or any mental illness as a single diagnosis. Because of coexisting mental illnesses, many employees will not effectively recover from or stabilize chronic and persistent conditions such as diabetes, asthma, heart conditions, hypertension, or cancer unless an effective stress management program is implemented. A 2005 study for Dupont Company by the University of Pennsylvania showed that depression, when measured by its impact on total costs (direct and indirect costs), was the highest corporate cost medical condition. The second highest total cost was from musculoskeletal issues that likely also involved stress related costs. See also: Consumerism: Good, Bad, Future   Medical, clinical, and medication therapies have advanced such that clinical depression and other mental health conditions have cure rates equal to and greater than many medical conditions. Clinical depression can be cured. Treatments work. Medications are effective. No company, large or small, can avoid the costs of depression. Divorce, disability, and violence in the workplace can hit anyone at anytime. According to the Institute of Medicine 30,000 people die each year from suicide, and 90% had diagnosable and treatable depression. For a small employer the results can be devastating if a key employee or executive suffers from clinical depression. Tom Johnson, former CEO of CNN News, likes to say, “If a company’s computers crashed and corporate production ground to a halt, the CEO would demand immediate action to re-establish the “corporate brains.” In developing a “knowledge-based” workforce, it is just as important for CEOs to take care of mental health and the “central computer” – the brain - within each employee.” Most employers do not understand the complexities of clinical mental health diagnoses. They do not know what it means to have schizophrenia, a somatoform disorder, a factitious disorder, or get a multi-axial assessment. Tom Johnson understood as he often suffered from serious bouts of clinical depression. Tom has dedicated his life to helping others deal with the debilitating effects of depression. Case Study As an actuary and mathematician, I was trained in numbers and actuarial science. Many of you may also be analysts, doctors, lawyers, CEOs, economists, or researchers. Let’s throw away the numbers for a moment and look at the lives of real people. Let me tell you about a young man, age 30, who suffered multiple inherited physical problems: a blood disorder, clotting concerns, pulmonary hypertension, and other unfathomable sources of pain and suffering. Combined with depression and the stigma of an emotional disorder, this young man was frequently non-compliant with care and treatment. Unlike other physical illnesses, depression typically causes the patient to avoid care. He pushed away the very help that was needed. He pushed away family support and friends that cared. No young strapping 6’5” 260 pound young man wants his forehead stamped with the stigma of mental illness. He was not going to be classified as “crazy”, see a “shrink”, or go to a “nut house” for care. No, he was a high school basketball star with the athletic promise most boys just dream about. In his mind, he didn’t need care, he was who he was. He didn’t accept or understand chemical imbalances. In his mind, "Real men are strong enough." In 2005 the years of depression and physical decline took its toll. The death certificate read pulmonary hypertension. But, I can tell you the real cause was stigma and major depression that prevented this young adult from seeking or accepting the medical and life saving care that he needed. Chris Golden was my step-son. His mother and I buried Chris on May 5, 2005. Look at all the ROI numbers, but never forget. This is not about numbers. It’s about people and saving lives. It’s about the Chris Goldens of the world.

As companies become more data-driven, so have their employee performance metrics. Yet the very metrics that are often used to gauge employee performance might actually discourage the behavior those companies want to promote. This common workplace pitfall is grounded in two basic realities. What gets measured gets managed. Employees tend to behave in a manner that is aligned with how they are evaluated and rewarded. What’s easy to measure isn’t necessarily what’s right to measure. Organizations often gravitate toward easy-to-measure performance metrics, even though the behaviors they wish to cultivate are relatively complex. Examples abound of how organizations fall victim to the “folly” of employee performance metric design:

• Service centers that measure how quickly staff handles calls then wonder why employees don’t spend ample time to completely resolve a customer’s issue.
• Companies that obsess over quarterly sales targets then are surprised when executives make short-sighted decisions which compromise the business’ long-term health.
• Organizations that focus on individual performance to assess employee success are then dismayed when they observe a lack of team work and collaboration.
• Manufacturing firms that measure workers on the volume of product they deliver then struggle with widespread quality issues on the finished goods.
• Sales divisions that measure employees purely on top-line growth are then surprised to see how unprofitable newly -acquired accounts are.
• Human resources departments that measure recruiters on candidate “yields” from job fairs then find many unqualified applicants in their interview pipeline.

See also: Risk Performance Metrics   Without careful and thoughtful design, metrics that are meant to manage employee performance can actually sabotage business success. To avoid that outcome, keep these three points in mind: 1.  Think about what employee behaviors are most valuable to your customers. What do your customers care about most? Perhaps it’s how long they have to wait in line, or be on the phone with your staff. Even more likely, it’s getting their issue resolved on the first try. Make sure your employee performance metrics are aligned with your customers’ interests. If customers value speed of service above all else, then put that at the center of your measurement methodology. If other considerations are just as critical to them (such as the quality of the product, or the efficacy of the staff), then gauge performance on those dimensions as well. For example:

• Conduct post-purchase customer surveys to assess overall satisfaction with product quality (and, indirectly, the performance of those making the product).
• Track the number of employee-submitted product enhancement suggestions, thereby encouraging staff to translate customer feedback into constructive improvement ideas.
• Or measure how frequently customer inquiries are resolved on the first contact, indicating the staff’s effectiveness at understanding and addressing customer needs.

2.  Use metric “checks and balances” to avoid over-rotating on any one measure. A singular focus on a particular performance metric can be counterproductive. The behaviors that businesses try to encourage among staff can rarely be tied to just one metric. Doing so usually ends badly. Employees become obsessed with outperforming on that single metric, regardless of the consequences. Guard against over-rotation on any single metric by creating a balanced system of measures. For example, let’s say you want to encourage a sales-oriented culture, but want to avoid misconduct. Rather than measuring staff only on sales generated, complement that metric with ones that gauges account profitability and customer satisfaction. Then, only reward salespeople for achieving revenue targets while also meeting those other performance thresholds. See also: New Way to Evaluate Captive Performance   3.  Consider unintended consequences and perverse metric-driven behavior. This is perhaps the most important element of good employee performance metric design. Look at your employee performance metrics through a critical lens. Carefully consider all of the ways by which a metric, engineered with the best intentions, might nonetheless promote undesirable (or at least customer-unfriendly) behavior. Based on how detrimental and probable those unintended consequences are, tweak your approach accordingly. That might mean abandoning some metrics in favor of new ones. For example, consider a call center that chooses to measure customer satisfaction instead of call handle time. (The latter metric often leads service representatives to rush callers off the phone.) It may also mean adding “check and balance” complements to existing metrics. For example, an organization that uses 360-degree evaluations to ensure that individual achievement does not come at the expense of collaboration and collegiality. The development of effective employee performance metrics requires a delicate touch. Success measures, and the reward systems they support, shape employee behaviors in meaningful and sometimes subtle ways. A thoughtful approach to performance metric design can help companies use metrics to their advantage. The result is a powerful “behavioral current” that steers employees in the right direction. And the value of that is…  immeasurable. This article was originally published on Monster.com.

In the wake of Hurricane Harvey and now Hurricane Irma—and with Hurricane Maria now pummeling the poor Caribbean again while Hurricane Jose looks likely to lash Long Island—it's becoming clear how much people have avoided buying flood insurance and how expensive their decision may be. The question is: Why don't people buy insurance?

The answer seems to be that people often don't think they need insurance and find it expensive. For good measure, people complain about the complexity of insurance and how unpleasant it can be to deal with insurers.  

The problem isn't just with flood insurance, either. Far from it. Life insurers, in particular, face dwindling interest, but the lack of demand for insurance is widespread. Some are now saying that flood insurance should be required, and I've heard others suggest that life insurance should be mandatory. Those ideas may or may not make sense—but shouldn't the insurance industry aspire to producing products that people want to buy, not ones that, like auto and home insurance, they only buy when forced to do so?

That's a bit of a roundabout way of saying I think insurtech can solve many of the broad problems facing insurance, slashing costs while reducing complexity and smoothing interactions with insurers. Exhibit A is chatbots.

The bots use artificial intelligence to answer routine questions, generally through some form of texting. Customers don't need to sit on hold for minutes listening to sales pitches, be chastised because they don't have all their documents in front of them, then get transferred twice because it's not clear which department they should be calling. So, customers are happier. Insurers get to save gobs of money because a call center rep can handle five to 10 times as many customers as a rep can now. Insurers are increasingly using chatbots to simplify purchasing, not just service or claims processing—attacking what Brian Duperreault, now CEO of AIG, identified in an ITL article a year and a half ago as the "massive cost of doing business...[that] puts our industry at risk."  

An article in the past week by three senior partners at McKinsey identifies the sorts of efficiencies that are possible—a British broker that automatically processes 3,000 claims a day, managed by four employees; a department of 250 employees turned into 110 bots and 11 human supervisors; 160 bots that process 500,000 transactions a month. Remember, the changes make life simpler for customers and come at a time when the insurance industry faces a talent shortage. 

At the risk of being repetitive: An article I highlighted last week provides a host of additional examples of how chatbots are ready to take on a huge role. 

In addition, Pypestream, the company that we believe is the leader in chatbots in insurance, is announcing that it has received a round of financing from W.R. Berkley and will have a Berkley executive join the board. Pypestream, which raised $15 million in Series A funding in February, isn't disclosing the amount that Berkley is investing. "We will use this additional investment to fuel growth across more industries and use cases, and to help more businesses provide 24/7/365 experiences that their customers not only love but expect," said Richard Smullen, CEO of Pypestream. 

Chatbots, alone, likely won't be enough to get people to buy flood insurance, I'm sorry to report. But they can get us started on the sort of radical reduction in expense and improvement in simplicity that will lead the charge for insurtech. Perhaps the industry can even get to the point where people look to buy insurance, rather than only doing so when a regulator or mortgage bank forces them to do so.  

Cheers,

Paul Carroll,
Editor-in-Chief

According to a new study from the Insurance Institute of Canada (IIC), the sharing economy presents both an opportunity and a threat to the insurance industry. In the U.S., the sharing economy has already created 17 companies valued at $1 billion or more, including Uber and Airbnb. Some 27% of the U.S. population participate in this type of consumption. Now, with millions of Canadians who use the sharing economy seeking unconventional coverage as a result, innovative startups are threatening Canadian insurers. See also: Opportunities in the Sharing Economy   Opportunity – Widespread Use Forty-five percent of Canadians report being interested in sharing underutilized assets to generate income. In Montreal alone, Uber provides roughly 300,000 rides per month. This means that new types of insurance policies are needed to support the emerging car-sharing and home-sharing industries. For example, because the sharing economy often includes short-term asset sharing, there is an opportunity for insurance companies to provide unconventional coverage options. Some insurers are already creating products to satisfy this demand. For instance, Aviva Canada has a policy for ride-sharing drivers, and Square One Insurance developed a product specifically for Airbnb hosts. Threat – New Competition All of this new opportunity is fueling the creation of nimble and mobile-friendly insurtech startups such as Prvni Klubova, Lemonade, and Metromile. These companies provide insurance in innovative ways using mobile and AI-driven technology. Companies like these three are potential threats to traditional insurers in Canada. In fact, Lemonade has already gained more than $59 million in funding and is quickly becoming a major player in the industry. According to a recent study, nearly half of traditional insurance companies are concerned that as much as 20% of their businesses could be lost to new insurtech players. If insurers fail to adapt to new competition, these fears could become reality. And insurance carriers are not the only companies experiencing disruption. Insurance brokers also face competition from new platforms such as Friendsurance. The Solution There are two options for traditional insurers to consider when it comes to dealing with swift insurtech startups -- compete or partner. Competition has been attempted by a number of traditional insurers, such as Economical Insurance, who launched Sonnet Insurance, an online-only insurance provider. However, due to the rapid pace of emerging technologies, head-on competition presents many challenges. Launching an insurtech solution from the ground up is resource-intensive, especially for companies who are not as familiar with a technological terrain. See also: Sharing Economy: The Concept of Trust   Partnering can be a more productive endeavor. Many traditional insurers have recognized this and have already formed key partnerships. For example, Intact and Aviva Canada have partnered with Uber. Intact is also a partner with Turo and an investor in Metromile. Additionally, Northbridge has partnered with RideCo, a Waterloo-based ride-sharing startup. Through this partnership, ride-share drivers can receive as much as $1 million in third-party liability coverage. Final thoughts Sharing economy valuation is projected to top $335 billion by 2025. Its impact on the Canadian insurance market will only continue to grow. While many Canadians will benefit from the expansion of the sharing economy, traditional insurance companies will need to adapt in order to keep up with new competition from insurtech newcomers. As a result, we are likely to see more partnerships between traditional insurers and insurtech companies in the years to come.

Once your analysts have a clear business question to answer, do they start new analysis each time, potentially reinventing the wheel? After creating or leading data and analytics teams for many years, I began to notice this pattern of behavior. What we seemed to lack was a consistent knowledge management solution or corporate memory that could easily spot what should be remembered. Funnily enough, as I became convinced of the need for holistic customer insight, I found a partial answer among researchers. Avoiding reinvention is such an important issue for analytics and insight teams that I’ll use this post to share my own experience. The lack of secondary research approach for analytics Researchers do a somewhat better job than insight teams because of their understanding of the need for secondary research. Experienced research analysts/managers will be familiar with considering the potential for desk research, or searching through past research, to answer the question posed. Perhaps because of the more obvious cost of commissioning new primary research (often via paying an agency), researchers make more effort to first consider if they already have access to information to answer this new question. But, even here, there does not appear to be any ideal or market-leading knowledge management solution. Most of the teams I have worked with use an in-house development in Excel, interactive PowerPoint slides with hyperlinks to file structures or intranet-based research libraries. Whichever end-user computing or groupware solution is used, it more or less equates to an easier to navigate/search library of all past research. Normally, a user can search by keywords or tags, as well as through a prescribed structure of research for specific products/channels/segments etc. See also: Why Customer Experience Is Key   Some research teams use this very effectively and also recall those visualizations/graphics/VoxPops that worked well at conveying key insights about customers. It is worth investing in these area as it can save a significant amount of research budget to remember and reuse what has been learned already. However, while also leading data or analytics teams (increasingly within one insight department), it became obvious that such an approach did not exist for analytics. At best, analysts used code libraries or templates to make coding quicker/standardized and to present results with a consistent professional look. Methodologies certainly existed for analysis at a high-level or for specific technical tasks like building predictive models, but there was no consistent approach to recording what had been learned from past analysis. I’ve seen similar problems at a number of my clients. Why is this? Perhaps a combination of less visible additional costs (as analysts are employed already) and the tendency of many analysts to prefer to crack on with the technical work together conspire to undermine any practice of secondary analytics. The many potential benefits of customer insight knowledge management Once you focus on this problem, it becomes obvious that there are many potential benefits to improving your practice in this area. Many analytics or BI leaders will be able to tell you their own horror stories of trying to implement self-serve analytics. These war stories are normally a combination of the classic problems/delays with data and IT projects, plus an unwillingness from business stakeholders to actually interrogate the new system themselves. All too often, after the initial enthusiasm for shiny new technology, business leaders prefer to ask an analyst than produce the report they need themselves. So, one potential advantage of a well-managed and easily navigable secondary analytics store is a chance for business users to easily find past answers to the same question or better understand the context. But the items stored in such an ideal knowledge management solution can be wider than just final outputs (often in the form of PowerPoint presentations or single dashboards). I have seen teams benefit from developing solutions to store and share across the team:

• Stakeholder maps and contact details
• Project histories and documentation
• Past code (from SQL scripts to R/Python packages or code snippets)
• Metadata (we’ve shared more about the importance of that previously; here I mean what’s been learned about data items during an analysis)
• Past data visualisations or graphics that have proved effective (sometimes converted into templates
• Past results and recommendations for additional analysis or future tracking
• Interim data, to be used to revisit or test hypotheses (suitably anonymized)
• Output presentations (both short, executive style and long full documentation versions)
• Recommendations for future action (to track acting on insights, as recommended previously)
• Key insights, summarized into a few short sentences, to accumulate key insights for a specific segment, channel or product

Given this diversity and the range of different workflows of methodologies used by analysts, it is perhaps not surprising that the technical solutions tried vary as well. Where is the technology analytics teams need for this remembering? As well as being surprised that analytics teams lack the culture of secondary analytics, compared with the established practice of secondary research, I’m also surprised by a technology gap. What I mean is the lack of any one ideal, killer-app-type technology solution to this need from insight teams. Although I have led and guided teams in implementing different workarounds, I’ve yet to see a complete solution that meets all requirements. See also: Why to Refocus on Data and Analytics   An insight, data or analytics leader looking to focus on this improvement should consider a few requirements. First off, the solution needs to cater with storing information in a wide variety of formats (from programming code to PowerPoint decks, customer videos to structured data sets, as well as the need to recognize project or "job bag" structures). Next, it has to be quick and easy to store these kinds of outputs in a way that can later be retrieved. Any solution that requires detailed indexing, accurate filing in the right sub-folder or extensive tagging just won’t get used in practice (at least not maintained). Finally, it also has to be quick and easy to access everything relevant from only partial information/memories. Imperfect solutions that I have seen perform some parts of this well are:

• Bespoke Excel or PowerPoint front-ends with hyperlinks to simple folder structures
• Evernote app, with use of tags and notebooks
• SharePoint/OneNote and other intranet-based solutions for saving Office documents
• Databases/data lakes capable of storing unstructured or structured data in a range of file formats
• Google search algorithms used to perform natural language searches on databases or folders

These can all fulfill part of the potential, but the ideal should surely be a simple as asking Alexa or Siri and having all completed work automatically tagged and stored appropriately. I’m sure it’s not behind the capabilities of some of the data and machine learning technologies available today to deliver such a solution. I encourage analytics vendors to focus more on this knowledge management space and less on just new coding and visualisations. Do you see this need? How do you avoid reinventing the wheel? I hope this petition has resonated with you. Do you see this need in your team? Please let us know if you’ve come across an ideal solution. Even if it is far from perfect, it would be great to know what you are using. Share your experience in comments boxes below, and I may design a short survey to find out how widely different approaches are used. Until then, all the best with your insight work and remembering what you know already.

Last week, we started a conversation about some of the common insurtech claims. Last week, we mentioned the statement from one particular company about all the good that they do. If you missed last week’s post, here’s a link to A Response to Some Insurtech Claims. Let’s get into statement #2. Statement #2: It’ll just take a few seconds! Swyfft wants us to believe that it only takes an address to get a solid quote on a homeowners’ policy. Going to the website, you’ll find only a few lines of text and a place to enter your address, press the button and “Get Quote.” Implication: Your insurance company is wasting your time by asking you all of those questions. We’ll give you insurance. All you have to do is give us your address; we’ll search publicly available information and give you a quote instantly. We don’t want to waste your time. Response: I don’t buy this. I tried this website out, too. It was pretty simple to get a quote. I put the address in and then they asked a few more questions. Then they asked a few more questions. Then they gave me a quote. It was a pretty good quote as far as insurance quotes go. See also: What Incumbents Can Teach Insurtechs   The problem is the lack of honesty when they say that they’ll give you a quote with just an address, or the auto insurance company that says that they’ll give you a quote without any personal information. That’s just nonsense. Their system is not making underwriting decisions based only on what their data collection algorithms can gather from the internet. Even when they say that they can give you a quote with minimal information, it’s at best a preliminary quote. It’s not a full quote. That’s when they turn around and become those they cry out against. That’s when they start asking other questions, just like I would if I was the underwriter. Here’s my next concern and its a question for the carrier. When the customer has a loss, will they have a person review the file and try to underwrite the risk at the time of the loss to avoid paying on the claim? This is a tactic that other companies have used to their detriment. Let me be clear. If a company is going to have a person underwrite the risk, it must be done prior to accepting the risk, or early in the life of the risk. This includes underwriting upon renewal. Underwriting is the end result of risk analysis and data validation and must never be done as a means of rejecting claims as part of the claims process. If a company trusted their software to make the decision to write the risk, they should stand by that trust at the time of the claim My final concern here is that the applicant doesn’t necessarily understand what they’re buying or rejecting. The company is making offers of coverage, including changing coverage A for their home, which an experienced insurance professional might look at and provide advice about. Without that advice, the customer might look at the options and reject them, leaving them open to retain certain losses that they shouldn’t. Those are the losses that they’ll try and file as claims later and the company will reject the claims. See also: 3 Misconceptions on Insurtech   I will honestly admit that some of this is my conjecture. I’m making guesses about problems that may pop up for the customer if they choose this particular sort of insurance company. I may be wrong, but I’d rather make my concerns known and be wrong than be right and keep silent. Next week, we’ll talk about statement #3: You’ll save so much money! This article first appeared at www.insurancejournal.com.

Automation and robots are not just revolutionizing work in factories and warehouses but also in offices, including insurance companies. According to a study by the McKinsey Global Institute, in around 60% of all occupations, 30% or more of all tasks could be performed by machines—and even 20% of management tasks could be performed by robot workmates. How will companies change when office work is automated? If robots and software programs replace human work, this costs on average around 13% of the wage bill paid for work in a developed country like the U.S. At a stroke, moving this work to low-wage economies becomes less attractive because offshoring on average costs almost 40% of the wage bill in developed countries. A British insurance broker today automatically processes 3,000 claims a day—all managed by a grand total of four employees. And the subsidiary of a major European energy utility has automated several important processes in administration—from billing and collection of consumption data to consumption management. What was previously handled by 250 employees is now managed by 110 robots, overseen by 11 human supervisors. One of the biggest wireless providers has automated 15 complex administrative processes, which is equivalent to 35% of its work volume: 160 robots process around 500,000 transactions a month. And it doesn’t just save costs. Since the results are more reliable than those produced by human employees, sales staff on the front line have more capacity because they don’t keep having to check back with head office to query an incorrect entry. See also: Robots and AI—It’s Just the Beginning   Machines, then, are superior both in terms of cost and quality, with robots and computers producing more accurate results. They rigidly follow their programming—errors are not a factor. And even if production is ramped up, the same quality is achieved with large volumes as with smaller volumes. Robots don’t even need breaks—they can work around the clock if necessary. And something else that’s particularly important in times of increased compliance regulations, machines record their activities in seamless logs, and any activity can be verified later. However, because it will only be possible to fully automate a handful of jobs in the foreseeable future, work content and processes will need to be redefined. For example, if banks use machines to review loan applications, employees have more time to advise customers, thus producing more applications a day. Financial advisers no longer need to analyze the financial data themselves and can therefore work more on creative investment strategies. Robots can even help develop investment strategies—meaning recommendations that were previously only given to the best customers because they tied up so much adviser capacity, can now be granted to every customer as “robo-advice”. Automation is even relevant for complex jobs The opinion still persists that automation is only suitable for the work of poorly qualified and low-paid workers. However, the study by the McKinsey Global Institute comes to a different conclusion: Even around 20% of management tasks can be handled by machines. They can analyze reports and presentations for operational decisions, check status reports for compliance with targets and even prepare HR decisions. In turn, managers have more time for thinking, for communicating and for managing—and the time needs to be used wisely. The more intensive the use of data, the more managers can benefit from automation—for example, in investment management where data volumes can be leveraged and turned into recommendations far more systematically using artificial intelligence and machine learning systems than is possible by a human. Automation is more than a technological decision Technology is, of course, a key element on the road to intelligent process automation; however, this is primarily a strategic decision that must be made by top management. The management must assess the extent to which the company is affected by the changes and decide whether to develop a specific strength in the area and to be at the forefront of change, or whether to hold back as a follower and avoid the mistakes of the pioneers. Ultimately, managers must decide how to adjust the operational business model of their company—from the organization and culture to the development of talent and skills. Experience shows that companies that selectively automated their processes and reduced costs quickly and easily in those areas with robotic process automation had to redefine all of their processes on the road to intelligent process automation—entirely in the spirit of the business process re-engineering of the 1990s. The key objective isn’t simply far-reaching automation of all processes, but to improve the overarching business system. It is still uncertain how soon automation will become widely adopted in offices. On the one hand, the timing depends on the pace of technological developments, and on the other how quickly the technological possibilities will be accepted and implemented in companies. Industries with a strong reliance on pure software solutions lead the way. They quickly achieve significant savings with manageable investment—the finance industry, where processes can be automated at relatively little cost, is a good example. The more hardware that is required, or the more security provisions and legal regulations that have to be met, the longer the switch to automation takes. See also: A Key Misconception on Digitization   Management must have a good overview of how their own industry’s parameters are developing, while at the same time developing a feeling for the economics of automation. This specific IQ of company leadership could become the difference between success and failure in the business world of tomorrow. Adapted with permission of the publisher, Wiley, from DIGITAL@SCALE: The Playbook You Need To
 Transform Your Company
 by Anand Swaminathan and Jürgen Meffert. Copyright (c) 2017 by McKinsey & Company. All rights reserved. This book is available at all bookstores and online booksellers.