The world of work is facing a perfect storm when it comes to retaining talent and knowledge. As the baby boomer generation – those born between 1946 and 1964 – reaches retirement age, younger workers are changing jobs more frequently than ever before. Youth unemployment is at record levels in many countries, meaning the next generation is failing to pick up suitable work experience. Aon’s 2015 Global Risk Management Survey, which surveyed senior decision-makers across 60 countries, found the failure to attract or retain top talent was the fifth-most significant risk facing businesses worldwide. This has been confirmed by other studies — more than 38% of hiring managers are struggling to find or retain the talent they need, according to a recent survey of 41,700 managers in 42 countries, with 22% citing lack of experience as a key challenge. Aon’s 2015 Trends in Global Employee Engagement report confirmed this — the average employee’s work experience has dropped by 28% since 2013. Skills, knowledge and experience are vital to a successful business, but also necessary to innovate and evolve with the needs of the marketplace. So retaining existing institutional knowledge is an increasing priority. If finding people with the knowledge you need is getting harder, a good starting point is focusing on keeping and developing the knowledge and people you’ve already got. In Depth Although the loss of data is an increasing concern in the age of cyber threats, the primary way organizations lose institutional knowledge is by losing valued employees with that knowledge. Every year, four million baby boomers leave the workforce in the U.S. alone, with 10,000 people a day hitting retirement age. In the U.K. and many other developed countries, more than 30% of the workforce is older than 50. Many baby boomer workers are in leadership positions, and when they leave the workforce almost all are taking with them decades of accumulated skills, experience, networks and personal business relationships, as well as first-hand knowledge of the reasons why their businesses have evolved the way they have. To make sure this valuable experience isn’t lost, organizations need to take a strategic approach, starting with a thorough analysis of their workforce, including:

• How many employees are coming up to retirement in the next five years?
• How many have key skills, knowledge or experience?
• How many have a succession plan in place?

Next, identify key soon-to-be retirees whose knowledge you most want to retain and begin to develop or expand your retiree-specific knowledge retention strategies. Just be aware that one size does not fit all — to get the best results, you may need to tailor your approach to the individual. There are three primary methods businesses are using to pass older workers’ expertise on to the next generation: knowledge hubs, mentoring programs and staggered retirement. Knowledge hubs are familiar to most organizations — a form of corporate intranet that pull together important knowledge in an easy-to-access central digital repository. The challenge is twofold: getting the right information into the hub and making it useable. Older employees, in particular, may struggle with digital technology, meaning you will likely need to provide training or assistance to help them enter the information you require. Equally, identifying what that information is can be difficult, which is why the most successful knowledge hubs are backed up with dedicated teams to manage and maintain them, as well as to measure their effectiveness and use. Apple takes this to an extreme, with dedicated university-style courses organized via an employees-only site backed up with in-person training. Mentoring programs have become increasingly popular over the last couple decades and have been proven to have a positive impact when implemented effectively. However, not every experienced employee will make an effective mentor — clear desired outcomes need to be communicated, expectations need to be set, training may be necessary to maximize benefits and you may need to introduce an incentive program to encourage participation. Both mentors and mentees will also benefit from third-party support. While it’s worth noting that the most successful mentoring programs tend to run over an extended period, there are no immediate, overnight benefits. Staggered retirement is a relatively new concept and one with much to recommend it. There are multiple variations in execution, but the basic concept is simple: Rather than retiring completely, employees are retained by the company in some capacity, perhaps shifting to part-time, perhaps to a contingent or contract basis. There is often a renewed focus on training or advising colleagues over their previous work. This enables the organization to continue to have access to valuable expertise and the retiree to top-up their pension with some additional earnings. However, there are some potential pitfalls, as Bankrate explains; depending on the nature of your retirement and health care plans, the retiree extending their working period may end up losing out, so seeking expert advice is vital. The broader benefits of active knowledge retention An added advantage of encouraging older employees to share knowledge is a boost in engagement — and with that retention levels — of younger employees. Career opportunities were the number one employee engagement driver in every region in Aon’s 2015 Trends in Global Employee Engagement survey, and opportunities to learn and develop new skills are a vital part of career development. Mentoring programs can also act as successor training schemes, giving more junior employees a clearer sense of their career path. Strong training programs are in demand among today’s increasingly mobile workforce, and well-constructed knowledge hubs can be a valuable pull-factor for jobseekers when supported with the right mix of internal communication and encouragement. Finally, while the very act of trying to systematically collate the knowledge and experience of your staff can help to increase their sense of value, it can also increase your organization’s capacity to make the most of its employees’ skills. While conducting an initial workforce analysis to identify key employees whose knowledge you want to retain, it may also be possible to start developing an internal skills database to maximize the potential impact of staff who may not be utilizing all of their expertise in their current roles. With failure to innovate or meet customer needs the sixth biggest concern for businesses in Aon’s 2015 Global Risk Management Survey, knowing what your organization knows is a crucial first step in ensuring that you’re able to adapt. The best way to retain your knowledge is to be aware of what knowledge you have in the first place. Talking Points “Organizations need to get to grips with the aging workforce challenge today or face skills shortages that will affect their ability to grow or deliver key services in the very near future… Too many employers are sleep-walking toward a significant skills problem that risks derailing their business strategy if not addressed. Not enough organizations are thinking strategically about workforce planning or even know enough about the make-up of their workforce.” – Ben Willmott, head of public policy, CIPD “The retirement of the current generation of corporate leaders will lead to cultural changes that most organizations are unprepared for. In order to thrive in the post-baby boomer landscape, companies need to put serious thought and effort into smoothing the intergenerational transition for leaders from generations X and Y.” – Richard Boggis-Rolfe, chairman, Odgers Berndtson “Retirement is currently seen as ‘all or nothing,’ where you are falling off a cliff. This problem comes from the way our public and private pension policies are framed. People would like to be able to work, but not as much, or work part of the year only. Instead of retiring all at once, they could enter phased retirement — that is perfectly feasible from a workplace policy perspective, but goes against some national policies.” – Ruth Finkelstein, associate director, Robert N Butler Columbia Aging Center, Columbia University “This article originally appeared on TheOneBrief.com, Aon’s weekly guide to the most important issues affecting business, the economy and people’s lives in the world today.” Further Reading

• Baby Boomer Retirement: Avoid a ‘Senior Moment’ in Your Business – Business.com, 30 September, 2015
• Preparing for the ‘Silver Tsunami’ – Government Executive magazine, 25 September, 2015
• More Employers Want Workers to Put Off Retirement – Benefits Pro, 11 August, 2015
• Phased Retirement Programs: Will They Make a Comeback? – The Huffington Post, 24 September, 2015
• Why Planning to Work in Retirement is a Risky Business – Reuters, 3 September, 2015
• Flexible Working Key to Keeping Singapore Seniors at Work – Enterprise Innovation, 19 August, 2015
• 6 Ways to Turn Managers into Coaches Again – Harvard Business Review, 10 August, 2015
• Avoiding the Demographic Crunch: Labour Supply and the Ageing Workforce – Chartered Institute of Personnel and Development, June 2015
• 2015 Trends in Global Employee Engagement – Aon report
• 2015 Global Risk Management Survey – Aon report

Insurance Europe's International Insurance Conference touched on some critical friction points between government and industry. Capital standards, consumer protection and climate risk resilience have grabbed the headlines, but important new ground was trodden when industry leaders began adding a new policy challenge to the industry’s agenda: the intersection of insurance and technology.

It's a simple question -- can insurance innovate? Think about your answer; I will give you mine at the end of this post.  Here's a quick story from an insurance book that helps set the stage for how the industry got to where it is today: There once was a membership association called the American Insurance Underwriters (AIU). The AIU acted as an agent for member insurance companies in international markets. Each member insurance company held a percentage of the AIU pool by which payments and liabilities were assigned. In the 1960s, an AIU member bid on a contract to insure a large church in Boston. But the insurance company didn't bid the insurance like everyone else. Instead, the insurer created a tailored contract with its own rate calculations, "rather than the standard forms and prices other (AIU) insurers had agreed to use." The incumbent insurer was not pleased: "Executives at Continental Insurance, which held about 27% of the AIU pool, went ballistic.... [Continental Chairman Victor] Hurd objected that this radical maneuver of using competitive pricing and deductibles in fire insurance was somehow going to ruin the insurance industry." Executives at the heretic insurance company convened.  One "old-fashioned insurance man" (the book's description, not mine) argued that the relationship with the AIU must remain intact as it was an important revenue source to the company. The executive urged the group to stick to the AIU practices.   See also: Underwriters Need Some Power Tools Another executive who participated in the custom underwriting urged another path: "We should not be tethered to outmoded practices," he said, "whether the custom of rate-setting associations, the terms of our policies or anything else." Who was that executive? Maurice Greenburg, who later became the CEO of AIG, one of the largest commercial insurance carriers in the world. But before AIG, Greenberg had to fight to change the way things were working at American Home, the heretic insurance company. Greenberg had to argue that remaining a part of an organization that sets international practices and shares profits and liabilities across insurers was not the best approach. Today, this seems obvious; at the time, some viewed this as blasphemy. But Greenberg's innovation didn't stop there. According to Greenberg's book, he used the AIU discussion to point out another outmoded practice relating to insurance agents: "Insurance agents worked for themselves in the field writing policies, yet they possessed the authority to bind the insurance companies they represented.... American Home's agents seemed to care more about commissions than quality. Greenberg envisioned moving American Home away from its reliance on agents in favor of setting its own underwriting standards and moving away from the personal lines that agents tended to underwrite in favor of commercial risks that tended to be identified by brokers." Of course, every insurance company operates this way today. Reading The AIG Story has led me to a couple of ideas. There is absolutely no doubt that insurance companies can and do innovate. Insurance companies create new insurance products every day. For example, AIG launched kidnapping insurance in the 1970s in response to the emerging threat to wealthy individuals. You can see this kind of innovation today in the insurance products that were created to cover the Uber gap. But, as I take a step back and survey the insurance technology (insurtech) scene, I believe we are missing one important discussion: the connection between the technology and new insurance products. How will your mobile app help AIG identify a new product that should be underwritten? How will your health data help Zurich create variable rates for health insurance? How will your technology-enabled policy review software help an insurance company identify outlier language that may create additional liabilities? (I have an answer to this last question!) See also: 6 Key Ways to Drive Innovation The last mile is missing from insurtech discussions. The last mile is showing how your awesome new software can actually improve the underwriting or claims experience for insurance professionals. The last mile requires an inordinate level of expertise by the creators of the new technology. Most technologists won't finish the last mile. Pitch decks and 10-minute question and answer periods won't get you there. So yes, insurance can innovate. The question is, can insurtech truly support this innovation?

For years, the go-to approach with clients for discussing long-term care insurance (LTCi) solutions has been from an educational perspective. The idea was that if we could just get a prospective customer to lower his guard long enough to understand the strong statistical rationale or risk in favor of LTCi, the decision would become clear to him, and coverage would be purchased. As logical as all that sounds, maybe our logic is flawed? The reality we’re facing in the LTCi industry is that this approach is likely not the most effective way to lead Americans into action on LTCi. What we’ve experienced is that, despite our best efforts and compelling factual arguments in favor of LTCi, adoption rates have consistently hovered around 8%, which corresponds with the percentage of the population that is predisposed to long-term planning by nature. So why isn’t the traditional approach to planning for LTCi working for the other 92%? The answer, it turns out, might be found in some fascinating recent research into “behavioral economics,” which considers economic decision making from a psychological perspective. Best-selling books such as Nudge (Richard Thaler and Cass Sunstein) and Thinking Fast and Slow (Daniel Kahneman) have explored the ramifications of this fascinating topic. The idea is that people really don’t act rationally, as classical economics assumes. Instead, people are motivated to act based on their emotions and impulses. Moreover, the choices we make are very dependent on how options are presented to us. See also: Can Long-Term Care Insurance Survive? Companies and governments have recently used the findings of behavioral economics to try and "nudge" people to take actions. For example, more companies now auto-enroll employees in 401(k) plans and make them opt-out if they don’t want to join. The result has been a big increase in 401(k) participation. Another finding—that too many choices lead to inaction—has led to a narrowing of investment options. Similarly, “default” choices, such as target date funds, are now part of many 401(k) plans. Here are six ways in which the findings of behavioral economics can help improve your closing rate when doing LTCi planning with clients:

1. Keeping choices as simple as possible. As an adviser, you may think your job is to give a possible buyer multiple options for planning for care, such as spread sheeting several insurance carriers or comparing standalone and linked products. However, the reality is that consumers don’t want this—they want a recommendation with just a few choices. Share your due diligence, but limit the information to what you consider the best options for them to consider.
2. Focus on the possible gain LTC will provide instead of the possible loss. Research has shown that, just like gamblers, we all want to win, and we don’t like to think about losing. People who are considering LTCi don’t want to think about loss when planning for care, such as how their retirement savings may be depleted. Instead, focus on the fact that a small LTCi premium gives the policyholder the possibility of a big payoff in benefits. For example, a $2,000 annual premium could result in $300,000 to pay for high-quality care at home.
3. Use stories, not statistics! Statistics are important for discovering trends and insights, but they are awful when used for discussing LTC planning. People are way too optimistic about their future and think they will be on the winning side of a statistic. Focusing on stories and experience that motivate prospects is much better than using statistics that can destroy empathy when talking about planning for LTC.
4. Focus on “now” benefits, not the future.  It's incredibly difficult for people to imagine aging and needing help. Instead, focus on the “now” benefits of LTCi.  The now benefits are more difficult to quantify, but they can include peace of mind, good health underwriting and locking into a lower premium before a birthday.
5. Help guide heuristics (rules of thumb). For analytical advisers, it's tempting to use tools such as cost-of-care surveys that project the cost of care 40 years in the future when designing plans. A better approach is to “follow the crowd” and recommend benefits similar to what policyholders are actually buying. You may think people want customized solutions, but most would feel more comfortable picking options similar to other buyers. Recommend they do what most people are doing.
6. “Nudge” a choice.  When people have to make a decision, such as actively signing off on the fact they have been offered LTCi but declined, they will be more likely to buy. LTC planning is easy to delay, and people need motivations to keep them from delaying the decision forever.

See also: Long Term Care Insurance: Group plan vs Individual Behavioral economics is a controversial topic, but we think it offers an important critique of the way we have traditionally approached LTCi planning with prospective clients. Employing some of its findings might move us beyond the 8% threshold of highly motivated long-term planners to help the remaining 92% of the population engage in meaningful consideration of their long-term care needs.

The possibilities of a fully connected world are unfolding before us. Technological progress has always been about making our lives easier and providing us with more options to enjoy life – to travel, be entertained, buy stuff and communicate with others. But, the connected world promises to shift progress into overdrive. Many of the smart home, connected car and sharing economy capabilities already allow us to sit back and control the world with our mobile apps or via voice commands. Even today, a person can adjust a thermometer, launch a music playlist, check flight schedules and order a box of Twinkies – practically without lifting a finger or moving a muscle. Will this ultimately result in a populace that doesn’t think, exercise or know how to do anything except control the world through devices? Will we all end up as unthinking, lethargic, good-for-nothing sloths?

I suppose some would argue that we are already there. The YouTube-Netflix-Facebook culture spends enormous amounts of time entertaining themselves, and it conjures up images of people with eyes fixed on screens, ranging in size from tiny handheld devices to enormous, wall-mounted TVs to those giant screens on buildings in places like Times Square. Those at home are in danger of becoming couch potatoes. Others in more public places are just as mesmerized and are so attached to their devices that some fall into fountains in shopping malls or risk walking into traffic on busy streets.

See also: How to Think About the Rise of the Machines

But the developments in the emerging tech arena are made for more than just entertainment purposes, and the resulting changes in society demand a deeper exploration. The full truth is always a bit more complex. Consider the following connected world possibilities and the positive effects they can have on individuals and society:

• Fitness Wearables: Sales of wearables for fitness and health monitoring continue to climb rapidly. Athletes and non-athletes alike are tracking a variety of biometrics and being given incentives to improve their health.
• Smart Homes: In addition to entertainment and convenience capabilities, smart homes offer considerable opportunities to improve security and safety, reduce accidents and enable the elderly or disabled to have more options for independent living.
• Robotic Exoskeletons: Workers in warehouses, airports and other locations are being outfitted with exoskeletons that allow them to lift heavy weights while reducing injuries.
• Connected and Driverless Vehicles: Developments in advanced driver assistance systems (ADAS) and progress toward autonomous vehicles hold the promise of dramatically reducing vehicle accidents and the related injuries and deaths.

These are just a few of the hundreds of examples of the emerging, connected-world opportunities that may improve our health, promote wellness and enrich our quality of life. In addition, the entrepreneurial spirit and venture capital related to emerging tech and the connected world are engaging legions of individuals, both young and old. There may be one group of individuals that is looking forward to binge-watching Netflix while interacting with their world from the comforts of their living room couch. But there are many others that are actively engaging in the connected world to better themselves and the world around them.

See also: How Connected Will Connected World Be?

You may be wondering what this has to do with insurance. The answer is – a lot. Just as mobile and social media technologies have changed expectations, patterns of communication and the business environment, so will the connected world. Positive and negative implications of the connected world will affect human health, traffic patterns, accidents, population distribution, employment opportunities and many other areas of life and society. In short, virtually everything that the insurance industry covers will be affected in some way. There may be some who will sit on the couch as their health deteriorates and their societal contributions decrease, but there will also be many more who thrive on the opportunities of the connected world. Either way, the needs and risks of customers will change.

We didn’t need Dolly Parton to tell us that the classic 9-to-5 office routine can be a draining experience. The routine developed at a time when only one member of a household, typically the husband/father, held a full-time job; today, it is far more common for both partners in a relationship (regardless of gender) to work. So a 9-to-5 approach can create considerable challenges for those caring for children.

With childcare costs rising and services in short supply, workplace flexibility is increasingly important to working parents. Today, lack of workplace flexibility is pushing some parents out of the job market, which is especially bad for the still-struggling world economy. Women, in particular, are more likely to rank flexible working and work-life balance as important considerations, according to Aon’s 2015 Workforce Mindset Study.

The same study found that a flexible work environment was the second most important factor in deciding whether to take a job, and a-top five-most-desired area for improvement. Confirming this, three of the top six factors causing full-time workers to quit their jobs were because of difficulties in maintaining a work-life balance, according to a recent EY global survey.

Now that the world’s working-age population is on the decline, according to the latest World Bank figures, maximizing the number of people on the job is set to become an increasing concern for governments. With the proportion of women participating in the workplace also in decline over the last decade and the percentage of women in the global labor force stagnant at around 40%, making it easier for women to work could add $12 trillion to global growth, according to McKinsey.

At the same time, the world is experiencing a growing global skills shortage, meaning that businesses are eager to discover new ways to attract and retain top talent. Introducing more adaptable ways of working to enable people to fit their careers around their non-work commitments could be a solution to all these challenges — maximizing workforce participation, reducing gender inequality and boosting global growth and productivity.

This is part of the reason why the U.K. introduced a legal right to request flexible working in 2014. But with a combination of the rise of new technologies and an increasingly globalized workforce, there are a number of ways to reduce the barrier to workplace participation.

In-Depth

Thanks to the huge changes in communications technology that many have predicted could revolutionize the way we work in the 35 years since Dolly Parton’s hit song and film came out, there are now more alternatives to 9-to-5 than ever. Here are some of the most popular:

Flextime Employees work a set number of hours over a given period but can choose when they start and finish work (usually agreed in advance with their employer).

• Pros: Employees can arrange their workday around non-work commitments such as childcare; employers can increase the hours during which they have staff working without increasing their workforce.
• Cons: Ensuring clear communication and arranging meetings when employees are on different flextime schedules can be complex, while employees’ preferred hours may not fit client/customer needs.

Telecommuting Employees work remotely, using the internet and phones to stay in contact with their colleagues.

• Pros: Reduces the need to maintain expensive office space; saves employees money and time on their commutes; gives maximum flexibility to workers to balance their work and private lives as they see fit.
• Cons: Unless properly managed, telecommuting can reduce cohesiveness of teams; while vastly improved in recent years, the technology of remote working isn’t yet quite reliable enough, some feel; lack of visibility on colleagues’ availability can lead to frustration and delays.

Shift working  Employees work at staggered times, allowing multiple people to use the same workspace at different times of the day and night, or on different days of the week.

• Pros: Employees can work at times that suit them, while employers can maximize the efficiency of their workspaces by running facilities for longer.
• Cons: Can be complex to administer.

Job sharing Two or more people share a job, working part-time.

• Pros: Enables employees with other commitments to continue to work and employers to benefit from different approaches to the same job.
• Cons: Maintaining consistency and quality levels can be challenging for employers.

Staggered hours Workers have different start and finish times.

• Pros: Employees can set their hours to suit their needs; employers can extend their effective hours of business operation.
• Cons: Can lead to resentment from employees who are unable to secure the staggered hours that best suit them, and can hurt team coherence.

Compressed hours Employees work their full-time hours in fewer than the normal number of days, such as working 40 hours in four 10-hour days rather than five 8-hour days.

• Pros: Employees have more extended periods at home and save money on commuting; employers can cut office costs by closing down on the extra off day.
• Cons: Interacting with other businesses and with clients/customers on a four-day schedule when they are working to a five-day week can be difficult, and potentially lead to negative impressions.

Annualized hours A more extreme form of flextime, the employee has to work a set number of hours a year but has some flexibility over when she does it, usually with some guaranteed hours based around peak periods.

• Pros: Significant employee flexibility, and some benefits for employers with strong seasonal variance in demand.
• Cons: Can lead to long hours being worked at peak periods, which can lead to reduced quality of work.

Commissioned outcomes Employees have no fixed hours, just set output targets/deliverables.

• Pros: Employees have maximum flexibility.
• Cons: May require considerable project management to ensure that both employer and employee remain happy with the value for money of the arrangement and that targets are hit.

Term-time working Staff attend the workplace only during school term times, going on leave (or shifting to telecommuting or part-time work) during school holidays.

• Pros: Enables parents to spend more time with their children and save on childcare.
• Cons: Means the business has to fit in with school schedules rather than market needs.

Zero-hours contracts Employees have no guarantee of a minimum number of working hours but are called on as needed and are paid only for the hours they work.

• Pros: Maximum flexibility for employers and beneficial for some employees who are unable to commit to regular hours.
• Cons: Have developed a bad reputation and can be seen as exploitative, as the timing of the available work tends to be set by employers rather than employees; can make maintaining quality and training levels difficult.

When considering whether flexible working could work for your company, remember there are potential downsides as well as upsides to most forms of flexible working. What could lead to benefits for one industry, job type or employee could be detrimental to others, and, as with any project, the key is to be clear on what the intended outcomes are and how to measure success.

Talking Points

“The eight-hour work day is not as effective as one would think. To stay focused on a specific work task for eight hours is a huge challenge. In order to cope, we mix in things and pauses to make the day more endurable. At the same time, we are finding it hard to manage our private life outside of work.” – Linus Feldt, CEO, Filimundus

“The benefits of implementing flexible working policies are absolutely clear: happier staff, increased productivity and positive attitudes towards employer and business, to name but a few.” – Manesh Patel, senior benefits consultant, Aon Employee Benefits

“To boost employee freedom while also ensuring productivity, there are numerous flexible working options that businesses can offer… We have invested significantly in changing workplace culture, empowering employees to work from anywhere, while celebrating performance over presenteeism. These changes have led to great results, including a 20% boost in productivity and significant operational cost savings.” – David Langhorn, head of corporate and large enterprise, Vodaphone UK

“Bias toward stereotyping later starters means employees risk being inadvertently punished for taking advantage of flexible work time programs… Firms should be aware that simply introducing flexible hours on their own can have ramifications that should also be addressed. Indeed, without changes to their review procedures and other practices, they may ultimately be counterproductive.” – Sam Kai Chi Yam, assistant professor of management and organization, National University of Singapore Business School

“This article originally appeared on TheOneBrief.com, Aon’s weekly guide to the most important issues affecting business, the economy and people’s lives in the world today.” 

Further reading:

• Working Nine to Five? Not Any More… – The Daily Telegraph, 8 September, 2015
• Why Sweden is Shifting to a 6-Hour Work Day – Fast Company, 29 September, 2015
• Is it Time for a Four-Day Week? – Management Today, 21 August, 2015
• Why Flexible Working is Smart Working – Director Magazine, 6 October, 2015
• Why Flexible Working Can Hurt Your Career – The Sydney Morning Herald, 1 October, 2015
• Why a ‘Work from Home’ Option is a Necessity but not a Cure-All – The Boston Globe, 2 September, 2015
• Flexible Working Should be for the Many, Not the Few – HR Magazine, 14 September, 2015
• The Want-to-Work Mothers Trapped at Home by Prohibitive Cost of Childcare – The Guardian, 5 October, 2015
• Flexible Working – A Missed Opportunity? – The Huffington Post, 24 September, 2015
• 2015 Workforce Mindset Study™ – Aon report

What makes data science a science? Methodology. When data analytics crosses the line with simple formulas, much conjecture and an arbitrary methodology behind it, it often fails in what it was designed to do —give accurate answers to pressing questions. So at Majesco, we pursue a proven data science methodology in an attempt to lower the risk of misapplying data and to improve predictive results. In Methods Matter, Part 1, we provided a picture of the methodology that goes into data science. We discussed CRISP-DM and the opening phase of the life cycle, project design. In Part 2, we will be discussing the heart of the life cycle — the data itself. To do that, we’ll take an in-depth look at two central steps: building a data set, and exploratory data analysis. These two steps compose the phase that is  extremely critical for project success, and they illustrate why data analytics is more complex than many insurers realize. Building a Data Set Building a data set, in one way, is no different than gathering evidence to solve a mystery or a criminal case. The best case will be built with verifiable evidence. The best evidence will be gathered by paying attention to the right clues. There will also almost never be just one piece of evidence used to build a case, but a complete set of gathered evidence — a data set. It’s the data scientist’s job to ask, “Which data holds the best evidence to prove our case right or wrong?” Data scientists will survey the client or internal resources for available in-house data, and then discuss obtaining additional external data to complete the data set. This search for external data is more prevalent now than previously. The growth of external data sources and their value to the analytics process has ballooned with an increase in mobile data, images, telematics and sensor availability. See also: The Science (and Art) of Data, Part 1 A typical data set might include, for example, typical external sources such as credit file data from credit reporting agencies and internal policy and claims data. This type of information is commonly used by actuaries in pricing models and is contained in state filings with insurance regulators. Choosing what features go into the data set is the result of dozens of questions and some close inspection. The task is to find the elements or features of the data set that have real value in answering the questions the insurer needs to answer. In-house data, for example, might include premiums, number of exposures,    new and renewal policies and more. The external credit data may include information such as number of public records, number of mortgage accounts, number of accounts that are 30+ days past due among others. The goal at this point is to make sure that the data is as clean as possible. A target variable of interest might be something like frequency of claims, severity of claims, or loss ratio. This step is many times performed by in-house resources, insurance data analysts familiar with the organization’s available data, or external consultants such as Majesco. At all points along the way, the data scientist is reviewing the data source’s suitability and integrity. An experienced analyst will often quickly discern the character and quality of the data by asking themselves, “Does the number of policies look correct for the size of the book of business? Does the average number of exposures per policy look correct? Does the overall loss ratio seem correct? Does the number of new and renewal policies look correct? Are there an unusually high number of missing or unexpected values in the data fields? Is there an apparent reason for something to look out of order? If not, how can the data fields be corrected? If they can’t be corrected, are the data issues so important that these fields should be dropped from the data set? Some whole record observations may clearly contain bad data and should be dropped from the data set. Even further, is the data so problematic that the whole data set should be redesigned or the whole analytics project should be scrapped?   Once the data set has been built, it is time for an in-depth analysis that steps closer toward solution development. Exploratory Data Analysis Exploratory data analysis takes the newly minted data set and begins to do something with it — “poking it” with measurements and variables to see how it might stand up in actual use. The data scientist runs preliminary tests on the “evidence.” The data set is subjected to a deeper look at its collective value. If the percentage of missing values is too large, the feature is probably not a good predictor variable and should be excluded from future analysis. In this phase, it may make sense to create more features, including mathematical transformations for non-linear relationships between the features and the target variable. For non-statisticians, marketing managers and non-analytical staff, the details of exploratory data analysis can be tedious and uninteresting. Yet they are the crux of the genius involved in data science project methodology. Exploratory Data Analysis is where data becomes useful, so it is a part of the process that can’t be left undone. No matter what one thinks of the mechanics of the process, the preliminary questions and findings can be absolutely fascinating. Questions such as these are common at this stage:

• Does frequency increase as the number of accounts that are 30+ days past due increases? Is there a trend?
• Does severity decrease as the number of mortgage trades decreases? Do these trends make sense?
• Is the number of claims per policy greater for renewal policies than for new policies? Does this finding make sense? If not, is there an error in the way the data was prepared or in the source data itself?
• If younger drivers have lower loss ratios, should this be investigated as an error in the data or an anomaly in the business? Some trends will not make any sense, and perhaps these features should be dropped from analysis or the data set redesigned.

See also: The Science (and Art) of Data, Part 2 The more we look at data sets, the more we realize that the limits to what can be discovered or uncovered are small and growing smaller. Thinking of relationships between personal behavior and buying patterns or between credit patterns and claims can fuel the interest of everyone in the organization. As the details of the evidence begin to gain clarity, the case also begins to come into focus. An apparent “solution” begins to appear and the data scientist is ready to build that solution. In Part 3, we’ll look at what is involved in building and testing a data science project solution and how pilots are crucial to confirming project findings.

In today’s search for bigger and bigger big data, I fear metadata is getting overlooked. Put that way, it sounds ironic. Given that many organizations are almost desperate to mine their data assets for advantage, why would anyone intentionally overlook metadata? But, in fact, this is nothing new. Thinking back to when I successfully led my first data warehouse project in the 1990s, it was an uphill struggle to make progress on metadata then, too. (Those of a certain age may recall lots of enthusiasm for data warehouses and data mining.) But the less glamorous aspects of data quality management and metadata were all too set aside to save money or hit deadlines. At its most basic, this is just human nature. We get bored or distracted easily and crave reinforcement or short-term reward to persist with tasks. But metadata just might turn round and "bite you on the bum" if you ignore it for too long. Let me explain, briefly, why I think this matters: The domain knowledge gap Data science and analytics work relies on not just robust coding and appropriate use of statistics but also an understanding of the real world being explored through the proxy of data. Too many projects fail to have any impact in organizations because interpretation or recommendations were naive or irrelevant (which was obvious to those who actually knew what was going on around them). Put simply, metadata is just data about data. Knowing what variables mean really does matter to designing and interpreting analysis. In fact, metadata can help to get your data scientists or analysts closer to the real data issues as part of their induction. Understanding the data landscape, perennial problems and causes of systemic data quality pitfalls can greatly improve their later analysis. At the very least, the understanding opens eyes to possible data sources and people with expertise. See also: Data Science: Methods Matter   Short-term-ism always robs effectiveness and often efficiency  Any apparent time-saving (or boredom avoidance) that comes from skipping the work to create/maintain data dictionaries and reference data is normal in the short term. Looking longer-term, you often see repeated work needed or further costs incurred through fixes needed because the initial analysis lacked proper understanding of data item meaning. At the most extreme, findings can be directionally wrong and misleading if built on the shaky foundation of misinterpreted data items. However, I should also point out that metadata is not just an arduous maintenance task; it can be a gold mine of opportunity and time-saving in the medium term. Information about data that is easily updated by those who use those data items and discover meaning/problems/gaps/workarounds can be not just time-saving but feel life-saving in some cases. Empowering your analysts to share, in a collaborative working ecosystem, the most up-to-date understanding of what each data item means, data quality issues to avoid and any workarounds or other data to use is very powerful. See also: How to Use All the New Data   GDPR may force a metadata revival Although this topic has been buzzing around in my brain for months, I was prompted to post about it after reading an article in Data IQ magazine. The flamboyant editor, David Reed, rightly explains that one of the implications of the EU’s General Data Protection Regulation (GDPR) will be a need for better metadata. For permission evidence and to enable rights like the right to be forgotten, data owners/controllers/processors will need data and time stamps for data items. They will also need better records about the meaning of data items and how they were obtained, probably with expiration dates, as well. So, whether it’s to avoid costly mistakes, help your analysts be more efficient, or to ready your organization for GDPR, please reconsider your need for metadata. It just might be the biggest improvement to your data that you can make. What about your experience? Have you seen the benefits of accurate metadata, or do you have war stories caused by lack of metadata? Please do share.

During the ‘90s, a new medical plan, called consumer-directed healthcare, was introduced. It was based on the premise that through a high deductible coupled with a funded account, employees would have incentives to become better consumers of healthcare. To maximize the account dollars, employees received access to a transparency portal, either through their carrier or a private vendor, that helped them make more informed healthcare decisions. The belief was that physicians and hospitals would compete on price and quality to win patients, and the consumerism movement would finally reduce healthcare costs. But let's do some math. A recent article from Health Care Cost Institute (HCCI) reported that only 43% of healthcare expenses are for services that may have been shopped for by a motivated employee. For the 8% of the population consuming 80% of plan dollars, how motivated are they to shop for healthcare services if they are receiving 100% coverage once their deductible is satisfied? They aren't. So the consumerism approach doesn't apply to that 80% of healthcare spending. See also: 3 Tips for Improving Healthcare Literacy For the other 20% of the spending, having 43% relate to “shoppable” healthcare services means 8.6% of total spending can be influenced by consumerism. That’s not much, and many shoppable healthcare services don’t cost much, anyway, so any decline in costs would be a minimal percentage of total spending. The vast majority of a covered population accesses healthcare on an occasional basis; do we really expect them to remember the various portals and 800-numbers available to them, so that they can consider the cost and quality of the recommended provider for the prescribed service? How does infrequent healthcare use correlate to the effectiveness of the transparency portals? One of the private transparency portals recently released its fourth quarter results, and there was a decrease in the number of clients. See also: A Hospital That Leads World on Transparency So how do we solve the healthcare spending challenge? As in most industries, the purchaser (the employer) has the opportunity to work closely with the supplier (the healthcare providers) to remove waste and cost inefficiencies. The silver bullet to solving the healthcare challenges isn't employees – it's the employers! There are employers taking this logical next step to address their challenges. Are you ready for meaningful solutions?

The recent refugee crises in Southeast Asia and the Mediterranean demonstrate how developing world problems are increasingly becoming the problems of the developed world. Instability and economic weakness in poorer countries are leading to significant challenges for richer nations. Aon’s Political Risk Map analysis finds significant instability across much of the developing world, compounded by cycles of war, famine, drought and disease, and this is only likely to get worse as climate change and rising populations make sustaining poorer countries more difficult than ever. But the developing world also has huge potential. According to a recent PWC report, leading up to 2050, the 10 fastest-growing economies are all likely to be developing countries, while many developed economies will find their growth hampered by slowing productivity and the needs of their aging populations. For the health of the global economy — as well as to relieve pressure on developed world countries’ ability to cope with increased migration — helping the developing world become more stable and sustainable is in everyone’s long-term interests. Yet, until recently, most attempts to help had been based around charities and aid. This is starting to change. Below, we round up some interesting, innovative projects — many driven by the private sector — that could have a significant positive long-term impact on the developing world. In-Depth The reasons for the slow growth of the developing world economies are well-documented: poor infrastructure, lack of education, lack of money, high levels of disease, susceptibility to extreme climate events, political corruption and instability. Solving this is a long-term challenge, not something that can be fixed with a bit of international aid to mitigate the effects of the latest crisis. With governments often focused on the short-term periods before the next election, it is increasingly business that is starting to come up with innovative and effective solutions. Improving access to knowledge It might seem strange to suggest technology-based solutions to education in societies where many struggle to earn enough to feed themselves. But to build viable societies and thriving economies, we need to provide the workforce of the future the skills it needs. Everything starts with education — but how can we provide access to reliable, quality education in underfunded countries with poor infrastructure and a serious lack of trained teachers? According to recent Pew Research Center data, a majority of people across the developing world now have access to a mobile phone. This is a real game-changer. Access to a mobile means having access to information, and access to information means having the ability to make improvements to your way of life. Even basic feature phones can improve literacy rates, according to the World Bank, while smartphones, computers and tablets have the potential to radically change the educational landscape of developing countries. By enabling access to the internet, a single connected device shared by a community can provide access to structured remote learning programs, as well as all the knowledge on the World Wide Web. And while internet access may still be a challenge for the most remote communities, there are several initiatives under way to provide universal global Internet — Google’s Project Loon, which uses high-level balloons to provide wireless connectivity, and Facebook’s satellite-based Internet project are merely two of the most high-profile. Access to the internet can also bring significant health benefits. Connected devices are increasingly being used for some remote medical examinations through organizations such as Peek and CardioPad. Education campaigns to improve knowledge about nutrition and basic hygiene via mobile could also have immense impact; improving knowledge about child nutrition in the poorest countries could boost their GNP by 11%, cut child deaths by a third, and increase wages by up to 50%, according to the Scaling Up Nutrition movement. Even simple text message alerts about disease outbreaks, such as those used in Sierra Leone during 2014’s Ebola outbreak, have the potential to save tens of thousands of lives. Improving access to finance Technology could also help tackle the developing world’s funding challenge. According to the Bill and Melinda Gates Foundation, only 41% of adults in developing countries have bank accounts. Without bank accounts, saving for the future — to invest in improving farms and businesses and to weather unexpected financial shocks — becomes much harder, as well as far less secure. It can also restrict the ability to buy products and services that people need to improve their lot in life. Access to physical banks remains a serious challenge for remote communities — which is where mobile phones again come in. Vodafone’s M-Pesa money transfer system is one of the best-known examples of mobile-based payments, reducing the need for a traditional bank account, but there are plenty of alternatives (such as Africa’s Airtel Money, or Bangladesh’s bKash). “The mobile phone is becoming ubiquitous and is a natural distribution channel,” says Aon’s latest Global Insurance Market Opportunities report. “It offers the promise of more efficient distribution and an improved ability to scale quickly.” Yet the ability to make payments is one thing, but getting hold of the money to pay them is quite another. This is where microfinance comes in. First established in the 1970s, the microfinance concept is simple: provide reliable, low-interest loans of relatively small sums to the poorest in society to enable them to invest in essential equipment or materials to start or improve their businesses. With the rise of mobile, the logistics have become considerably easier — and the concept has been spreading exponentially. With basic seed capital becoming more accessible to small businesspeople across the developing world through organizations such as the Nobel Peace Prize-winning Grameen Bank, the potential for economic growth is stronger than ever. But while loans are a good start, the next phase in microfinance is set to focus on providing additional financial security through microinsurance. Funded by low payments, if crops fail, natural disasters strike or illness or injury hit, low-cost insurance for the world’s most vulnerable can help them recover — where previously they may have had no safety-net. People with microinsurance have also been shown to invest more in developing their businesses. This has been shown to encourage the use of healthcare services, prevent the spread of diseases and help reduce the burden on government budgets for pensions, healthcare and aid. Teach a man to fish The key to both these approaches is to help the world’s poorest help themselves — not merely teaching them to fish rather than giving them a fish but providing them with the ability to buy their own fishing nets, rods and boats and with the security of knowing that if any of these are broken, they will be able to replace them. Where previous efforts at helping the developed world to develop have focused on providing vital infrastructure, healthcare or nutrition one community at a time, the shift in recent years toward helping the developing world help itself is proving a revolutionary innovation. It’s still early days, but the signs are that by focusing on improving access to knowledge and finance and empowering communities to focus on building sustainable improvements, the developing world is starting to have a better chance of developing than ever before. Talking Points “From better health to increased wealth, education is the catalyst of a better future for millions of children, youth and adults. No country has ever climbed the socioeconomic development ladder without steady investments in education.” – Irina Bokova, Director General, UNESCO “There has been a strong social mobilization to use cell phones, television and whatever technology the government and private health care sector can to disseminate public health messages... Modern technology is vital here, and it can be this simple.” – Ladi Awosika, CEO, Total Health Trust “The problems and risks facing low-income populations are vast and complex. Offering microinsurance to these segments brings with it all the complexities of their daily life which need first to be understood and then addressed by microinsurance stakeholders; education levels, house-hold budgeting, behavioral economics, choice, priorities and inconducive infrastructure to name but a few. These barriers change from community to community, from region to region and are often vastly different to those faced by the more traditionally served clients in developed insurance markets.” – Marco Antonio Rossi, President, Brazilian Insurance Federation “This article originally appeared onTheOneBrief.com, Aon’s weekly guide to the most important issues affecting business, the economy and people’s lives in the world today.” Further Reading

• Mark Zuckerberg Calls for Universal Internet Access to Combat Poverty – The Daily Telegraph, 26 September, 2015
• Micro-Insurance Offers Families in Poorer Countries Protection from Destitution – The Guardian, 1 September, 2015
• Shortage of Long-Term Finance Blunts Progress in Developing Countries – The World Bank, 14 September 2015
• How Mobile Phones Are Changing the Developing World – UNICEF, 5 August, 2015
• 6 Lessons from Mobile Money Ventures in Developing Countries – Forbes, 28 September, 2015
• Global Insurance Market Opportunities 2015 – Aon report