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

Over 50 years ago, Edward Thorp, considered the "father of the wearable computer," discovered a tiny computerized timing device that could effortlessly beat opponents in a game of roulette. Since then, the popularity of wearable technology has always been on the rise. Today, we have smart devices like Apple smartwatches, Fitbit fitness bands, Google Glass and Nike Fuelbands that could do some pretty cool things to help improve the quality of our life. Wearable technology refers to tiny electronic gadgets that are worn on the body or clothing. They are capable of monitoring our physical and mental activities and generating stats to help us understand our health and fitness condition better. Whether it’s keeping track of your eating, exercising, or sleeping habits, there is always a smart device to provide you the right data. Insurance companies are taking wearable device reports seriously. You can get up to a 15% discount on your insurance plan by presenting your wearable report to your insurance agent. See also: The Case for Connected Wearables According to The Wearable Future, 20 percent of Americans are using wearables to monitor their day-to-day activities, and the number is expected to grow over the next couple of years. The study suggested that millennials are the biggest users of wearables. It’s estimated that 50 percent of millennials in America will own fitness bands by 2017. Why is the insurance industry paying attention to wearable technology? Here’s an Infographic that presents some interesting stats and information on how wearable technology is influencing the insurance industry. [caption id="attachment_19451" align="alignnone" width="177"] Credit: LifeInsurancePost.com[/caption]

Insurance carriers looking to better market and manage risks should use social media as a rich component of a robust analytics platform. By augmenting existing big data projects with social media feeds, carriers can identify key information about their insureds that would otherwise be difficult to gather in a timely manner. Social media data analytics can be a competitive advantage leading to greater sales, lower claims and increased customer satisfaction. However, insurers should be careful with the data or risk crossing the “creepy line.” With more than one billion users on Facebook and two billion total social media users across all platforms, the data shared is immense. The data that can be extracted from social media varies by platform, but in general the information goes far beyond pure text. Social graphs describe connections and relationships; profile updates highlight life change events such as marriage and the birth of children; geolocation tags highlight travel; and continuing communication can be parsed for activities and attitude. Modern carriers looking to leverage analytics for a competitive advantage should already have a big data capability that pulls data from policy, billing and claims systems, call center logs, portal and app usage, third party enhancement tools such as Dun and Bradstreet and other sources to build a robust picture of each insured. This data can be mined using machine learning and neural networks to identify risks that should be exited, opportunities for cross-selling and best marketing opportunities to insureds and prospects. Social media is not a replacement for this data, rather a rich addition to it. By augmenting known facts with machine processing of social data, insurers can enable a more detailed and nuanced analysis that the same analytics routines can use to further refine analysis. See also: Should Social Media Have a Place? Examples of enhanced capabilities with this more robust analysis include:

• Prescriptive marketing: Asses the marketing mechanisms and messaging that will be most effective in converting the prospect to an insured through analysis of social graphs, profile data and language usage. By parsing the semantics of a user’s language and analyzing their social graph for the type of language they are accustomed to seeing and, importantly, that they have chosen to see, marketing can be best tailored for the prospect.
• Life event based cross-selling: Identify changes in relationship, location, job or family structure that enable marketing or sales to proactively contact the insured to recommend additional products or services. An example is increasing term life coverage for a new parent. By contacting insureds with relevant products at the moment of a life event, agents can be highly effective at converting new sales.
• Continuous risk assessment: Continuously assess insureds’ risk profiles by expanding the analysis of an insured beyond their behaviors with the carrier to their behaviors with all other parties as evidenced in their social media communications. Updates about employment, travel, family circumstances or other items can impact how a framework understands the facts of an insureds’ interactions with the carrier. By understanding this, a carrier can better tailor reserve models or reevaluate whether to renew the policy.
• Claim fraud detection: Identify potential claim fraud activity by monitoring geolocation, language and other data elements to confirm reported stories and check for telling language used in public communications. For example, a claim for workers compensation could be identified for potential challenge if a system identifies geolocation data from a golf course.
• Customer sentiment: Be proactive with alerts of customer dissatisfaction with claim handling or price adjustments through text mining, allowing for remediation prior to losing a customer. By identifying dissatisfaction, the carrier can take better next steps in communication and outreach to maintain a client’s goodwill and business.

These aspects of insurance sales, risk management and claim management are beneficial for carriers. However, there are risks and challenges associated with social media data:  

• Language is complex data: Because social media is so dependent on written words, language analysis is a common basis for analysis. Semantic assessment is useful in identifying underlying emotions and intent. However, words have different meanings in different sub-cultures, geographies, friend groups and even in different transmission medium. As such, language parsing should often be used to augment existing analysis, not to serve as a primary source of facts.
• Usage of social media varies: In general, social media has widely different usage by age group and other demographic segments. Uptake rakes are not the same across all demographic groups, as demographic analysis of Facebook vs. Snapchat bear out and actual usage of the tools varies by group. The amount of data shared by younger users typically, but not always, dwarfs that of their parents. Analytical frameworks need to be configured to account for these differences and not draw unwarranted conclusions from different behavior patterns.  
• Usage of social media starts and stops: Users of social media will start, stop and potentially resume use many times. Details of usage may also change as users’ needs or privacy concerns change. This requires analytical tools to be flexible in analysis — to understand that lack of data, limited data or infrequent posting is not necessarily an indicator of underlying behaviors of the prospect or insured.
• Security is tricky: In the post-Snowden era, concerns about data privacy and usage are increasingly spotlighted by the media. Insurers should be cautious about how they collect, how they store and how they take action based on social media information. De-identification and storing only the analysis of the underlying data are potential paths among others. This should be continuously evaluated.

See also: 2 Concepts on Social Media and Analytics A final note on risks: In 2010, then-Google CEO Eric Schmidt said, “Google policy is to get right up to the creepy line but not cross it.” This brought about much criticism from the public and watchdogs as many took it to mean Google would use the data it had in ways customers were not comfortable with. Insurance is as much about trust as it is about financial contracts. Therefore, insurers should be careful in using data that some may consider private or semi-private rather than public. They should also be cautious in drawing inferences and interpretations from data in a manner which would cause insureds to question them as warranted and justifiable. The use of data to further the carrier’s understanding of its customers must be approached as a relationship that can benefit both parties, and insurers must avoid being seen as “big brother” looking to squeeze extra premium from insureds. Customers may not embrace the concept of their behaviors being analyzed. However, good analytics programs within insurance companies should be doing that today. By combining the facts of policy, billing and claims systems along with behavior evidenced in call center data, portals, digital apps and through other mechanisms, carriers should be analyzing customers robustly. In this framework, social media data becomes an enhancement layered on top that adds new dimensions and nuances to existing analysis. By leveraging neural networking and other machine learning approaches, carriers can better market, rate and manage risk and claims. These are net positives for insurers and potentially positives for customers. But, there are some substantial risks that must be managed as part of the total analytics strategy. By focusing first on the known facts and actual behaviors and only then expanding into the nuances of social media carriers, insurers can better enable robust and sound analysis that generates a return on investment for all parties.

LIMRA and Maddock Douglas embarked on a study that unveils significant findings among mass-market consumers and their attitudes about “retirement.” Retirement is in quotes because the notion of traditional retirement, that is, the stoppage of work at a set age, and saving up enough in advance to prepare for it is likely passé, perhaps even irrelevant. There is significant opportunity for providers who can crack the code in the mass market, also known as the “middle class.” This study aims to learn about the middle class, not from a demographic point of view but from an attitudinal one. Some significant findings include: Middle class is a state of mind, not an asset or income level. Interestingly, 36% of people in lower income ranges and 81%of people in upper income ranges consider themselves middle class. So that state of mind is quite widespread, and 74% agree middle class values are worth protecting. We found out only 25 % of the people who define themselves as middle class are thinking of retirement in the traditional sense (stopping their current work at the age of 65). Another 22% are thinking retirement will be after the age of 70, and 39% think it will be by age 64 or earlier. A full one-third say they very well may not retire at all. See also: 75% of People Not on Track for Retirement In addition, the notion of retreating on beaches and sailboats is also passé, as many report they aspire to a lifestyle that is more down to earth, that makes more time for family, or even for pursuing modest hobbies, health and faith. And the notion of retirement in general is being replaced by the notion of a lifestyle change, but one that is firmly rooted within a middle-class mindset. It’s not about a life of leisure; it is about being active with a different purpose. And this can happen in any timeframe and with many different catalysts. We should stop thinking about retirement as a bright line goal and be more fluid in our ways of helping people navigate their path to “jubilescence,” a new word coined by combining the Spanish translation of retirement (jubilación) and the idea of adolescence, a transition to a future self. Some people may have several jubilescence phases in their lives; some may have one. Some may be brought on in a positive and proactive way; some may be thrust upon people unexpectedly. Either way, the opportunity for professional advice is abundant. And perhaps the planning time horizon should be shorter and make room for more than one transition. In addition, jubilescence is highly individual; we cannot use demographics as an indicator of what people need or want. In an analysis of individuals in the same demographic class and circumstance, we found high degrees of individuality, even uniqueness, in terms of priorities and needs. One size does not fit all. See also: Why People Don’t Save for Retirement About one-third admit they don’t have an advisor and believe that’s appropriate. This suggests that we have a lot of work ahead of us to change the model and change the outcomes for consumers and ultimately the industry. If the current incumbents of the industry don’t, then disruptors will because the new Department of Labor rule will force some players out of the game, making opportunity for others. Finally, this study opens up spaces for new kinds of expertise beyond current products. We should be thinking about developing and delivering expertise that addresses needs that go beyond saving, investing and insurance, and assist in skilling up for new work opportunities, maximizing the value of living spaces and managing crises. This could be a transition opportunity for the advisors of today or a recruiting opportunity for the advisors of tomorrow. So the question is … Can this industry commit to serving the middle class in a way that is attractive, unbiased and also profitable? With the right work, analysis and innovation, the answer is yes.

In an age of increasing technological disruption to business around the world, almost every organization is looking for ways to keep on top of innovation. A classic Forbes study found workforce diversity and inclusion to be a key driver of internal innovation, as alternative perspectives challenge assumptions and lead to new approaches.

Numerous other studies have had similar findings. Diversity has also been proven to be good for business, with a recent McKinsey study finding that gender-diverse companies are 15% more likely to outperform their competitors, with ethnically diverse companies 35% more likely to do better.

However, simply hiring people from different backgrounds — or setting quotas for the number of women or people of different ethnic backgrounds — is not enough to benefit the company. If your company culture ends up treating all employees the same way, they will soon become assimilated into your existing working patterns, and the benefits of their diverse perspectives can be lost.

How do you encourage the continuance of the alternative approaches that diverse teams bring while sustaining the advantages of diversity for the long term? Getting the balance right is increasingly a challenge — efforts to support diversity, if implemented poorly, can seem at best patronizing, and at worst insulting and discriminatory.

In Depth

The work world is changing fast. The concept of a job for life has disappeared, with employees more likely to switch jobs than ever before. Generations are shifting as baby boomers retire and millennials seek rewarding work. The rise of the internet has made the world — and our workforce — more globalized than ever. New technologies continue to disrupt and threaten further disruption to a broad range of industries. Emerging markets are growing fast, and their rising businesses could overtake previous industry leaders in the developed world.

As the business world has become more global, so too has the value of workforce diversity increasingly been recognized; a broader mixture of employees has demonstrated to have multiple benefits in terms of productivity, innovation and adaptability in an ever-shifting economy. But how can we maximize the advantages of a diverse workforce?

The different types of diversity

The Society for Human Resource Management, a global professional organization operating in 140 countries, notes that while most people will think of gender and ethnicity when they think of diversity, there are plenty of other traits that should be factored in. They can be split into two types: visible diversity traits and invisible diversity traits, with some falling into either category depending on the individual.

• Visible: Skin color, gender, age, body size/type, physical abilities, physical traits

• Possibly invisible: ethnicity, religion, socio-economic status, marital status

• Invisible: Sexual orientation, native-born or non-native, nationality, parental status, level in organization, education, work background, culture, functional specialty, beliefs, values, habits, personality, military experience, geographic location

Each of these diversity traits can give their owners alternative perspectives that can be valuable for business — but some approaches to diversity and inclusiveness have sought to downplay rather than acknowledge differences.

The importance of differences

As the concept of diversity has gained traction over the last couple of decades, many companies around the world have made concerted efforts to avoid discrimination and embrace the hiring and promotion of people from less traditional backgrounds.

Much of the language has been around emphasizing similarities, rather than differences — trying to create harmony by encouraging employees to see what they have in common. However, the benefits of diversity come from the very differences this approach can seek to downplay.

“As hard as getting the mix in the workforce is, most companies have gotten used to the idea that we need the mix,” says Andrés Tapia, author of The Inclusion Paradox: The Obama Era and the Transformation of Global Diversity (and the former chief diversity officer at Aon Hewitt), “but they have not been ready for making the mix work, or how difficult it is. Because the more diverse a workforce is, the more difficult it is to manage … It’s not just about people looking differently, but thinking and behaving differently.”

Diversity of thought

This is why we are increasingly seeing an emphasis on encouraging and accepting diversity of thought as the most important aspect of diversity initiatives, rather than the traditional focus on simply opening up the workplace to people from different genders, ethnicities and disabilities.

“Diversity is the mix, and inclusion is making the mix work,” Tapia says. By adopting an inclusive approach to diversity, where cross-cultural differences as well as similarities are celebrated, the advantages of a diverse team can be sustained over the long haul.

Building trust

Of course, encouraging employees to express their different opinions presents another challenge: building the trust needed for them to feel comfortable to speak up. The key is to encourage acceptance of and respect for differences in approach, which can be incredibly complex and nuanced depending on the mix of visible and invisible diversity traits that make up your team’s background.

Rewarding ideas, praising suggestions and cross-cultural team-building exercises can all play a part, and there are too many approaches to fostering inclusiveness and acceptance of diversity to list here (see further reading, below, for a few overviews). However, absolutely vital to success is ensuring there are clear feedback channels to help shift approaches to encouraging inclusiveness of diversity if any employees feel them to be inappropriate. Because, while it’s unlikely you’ll ever be as excruciatingly bad as Michael Scott of The Office in his attempts to celebrate diversity, the delight of appreciating and encouraging diversity of thought is that you can be sure that you won’t be able to please everyone all the time.

The key is to ensure that you acknowledge and learn from this and use any inadvertent missteps to progress. The biggest benefit of workplace diversity, after all, is in learning from and adapting to alternative viewpoints.

Talking Points

“Employing people from different backgrounds and who have various skills, viewpoints and personalities will help you to spot opportunities, anticipate problems and come up with original solutions before your competitors do.” – Richard Branson, founder, Virgin Group

“Ideas from women, people of color, LGBTs and Generation Ys are less likely to win the endorsement they need to go forward, because 56% of leaders don’t value ideas they don’t personally see a need for… the data strongly suggest that homogeneity stifles innovation.” – Center for Talent and Innovation

“Multi-cultural teams produce different results depending on the level of inclusiveness. When a company has diverse talents but leaders ignore or suppress cultural difference, the cultural differences become obstacles to performance… When a company has diverse talents and leaders acknowledge and support cultural difference, the cultural difference becomes an asset” – Park Gyone-me, CEO, Aon Hewitt Korea

“The world is evolving at an unparalleled pace… The most successful leaders will be those who possess cross-cultural competence, a deep understanding of various peoples and a sincere appreciation for diversity.” – Donna Shalala, President, University of Miami “

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

• How Can You Ensure That Diversity Starts at the Top? – Entrepreneur, June 10, 2015
• Diversity of Thought is the Key to Global Competitiveness – IndustryWeek, July 16, 2015
• The Importance of Diversity of Thought for Solving Wicked Problems – Forbes India, July 8, 2015
• The Business Cast for Building a Cross-Cultural Workforce – Inc., June 1, 2015
• How to Create a More Inclusive Workplace for Your Diverse Employees – Forbes, June 11, 2015
• Diversity and Inclusion: Making the Mix Work – Aon white paper

Chief information officers (CIOs) are responsible for decisions and implementations that promise to deliver on enterprise goals. A CIO’s job is not only to invest in projects that are going to improve and streamline a company’s internal processes but to keep an eye out for initiatives and capabilities that will keep them ahead of industry shifts — shifts that can potentially challenge the company's core business. Increasingly, improving customer engagement to promote loyalty and drive growth is becoming important to most insurers. Understanding the scope of the process, where to begin and how to monitor progress remains problematic, so here’s a quick checklist of things CIOs can focus on today to start improving the consumer experience: Start from the customer’s perspective —

• Know who your customers are comparing you against:

Keep in mind (and remind your colleagues, whether they are in senior management or in the mail room) that consumers are not comparing you solely with other insurance companies. They are also comparing you with the other places they do business — and that includes online businesses (Amazon, for example).

• Understand what their expectations are.

Here is a reality check: No consumer will be thrilled to fax a wet-signed renewal application. Although there are good historical and legacy system justifications for demanding it, this is no longer acceptable for today’s consumers, who rightly demand immediacy.

• Meet them where they are… or will be.

Online is outdated; mobile is the new norm. You need to be thinking about how even mobile devices will be replaced by something newer and greater. In an age where cars can drive themselves and televisions are ”smart,” how much harder do you think it will be to sell insurance? See also: Tips on Improving the Customer Experience Follow up by looking at things from your employees’ point of view.

• What skills do your product development and marketing teams possess?

They most likely know a whole lot about insurance — its concepts, how to make it work from a business perspective and even how to present it to customers. Chances are, however, they are not versed in software engineering and technical concepts or tools.

• What tools are employees familiar with and which do they use in their daily work?  

Can tools like Word, spreadsheets, email and interactive shared drives or repositories be leveraged?

• How much IT engineering goes into translating a product vision into actual products (forms and online/offline interactions, whether direct or through agents and brokers)?

If you are like most carriers, once an insurance offering has been defined on the business side (product, marketing, claims, legal), IT steps in. How much time and money do you spend recreating what was already done in Microsoft Office? Would it not be more efficient if the subject matter experts were able to handle more of the load on their own? See also: Keen Insights on Customer Experience Take it all in from a systems and processes perspective.

• What core systems do you have in place today?

It is a safe bet that you have many systems in place, many of which overlap or are similar in features and purpose.

• When — and how — are you going to consolidate, upgrade or replace those systems?

Realistically, this will take time. A long time. Probably too long to afford waiting for it to be done.

• Look for plug-and-play capabilities and opportunities for an enhanced experience that do not force you to throw away all of your investments.

At the end of the day, you have a lot of smart people in your organization. Listen to what your customers are telling you, empower your people by removing extraneous and overly technical steps and look for ways to enhance your company’s communication capabilities without having to start everything over from scratch.