When Elizabeth and Ryan graduated from college, they didn’t have jobs and, frankly, didn’t know what jobs would fit their skills and abilities. Elizabeth was a psychology and history double major who didn’t want to pursue graduate school; Ryan was a biology major, with a minor in chemistry but had no interest working in a laboratory.  When they applied for jobs, they were like a lot of new grads. Both were bright and motivated, but they lacked an understanding of what value they brought to the workforce and which employers would have an interest in their backgrounds. Further, they had a lot of questions about how to conduct a job search. As CEO of a national firm that hires over a thousand new grads every year, I see stories like this every day. According to our research, they are not alone. Only about 20% of graduating seniors actively use career services during their senior years. Further, 60-70% of new grads don’t know where their education and skills fit in the workforce. Combine these stats with the fact that over 75% of new jobs are created by employers with 500 or less employees, companies that typically don’t interview at campuses, and it’s easy to see that the entry-level job market is highly inefficient. Other trends are also having an impact. For example, the larger companies that typically dominate college recruiting significantly reduced on-campus recruiting after the recession. Now, college recruiting is much more targeted, with advances in technology making direct interaction with college students much easier. Initial contacts are often made through social media, and interviews are often completed using video interviewing techniques. See also: The First Step in Recruiting Millennials Further, corporate college recruiters are also focused on high-demand majors in computer science, math and engineering or high performers in other majors with high GPAs. They know the majority of college grads can be easily hired through less expensive conventional recruiting methods after they graduate. The net result of all these factors is that fewer than 30% of graduating seniors have a professional job at graduation. This has led innovators to develop a variety of ways to make the entry-level job market more efficient. From job posting sites targeted on the entry-level to online skills assessment and career counseling to third-party recruiting and placement firms, this market is seeing a high level of activity. Since new grads typically don’t have direct experience in the positions they are seeking, one way to solve this problem is to match the transferrable (or soft) skills possessed by the candidate with positions that require those same skills. Important transferrable skills include critical thinking, time management, effective communication, leadership and initiative. Since the beginning of 2012, Prium Inc., a provider of managed care and medical intervention services located in Duluth, Georgia, has used a third-party career matchmaking firm to recruit, interview and select qualified candidates on behalf of Prium for their entry-level positions. Michael Gavin, Prium’s president, says, “Outsourcing helps take the college recruiting burden off our shoulders. More importantly, it’s incredibly effective for finding the skills and talents we need.” Prium’s experience underscores the value employers see in the outsourced college-recruiting model. Most small and medium employers like Prium don’t hire in the volume to justify building their own college recruiting programs. Using this approach, positions are filled quickly with highly qualified candidates. See also: How Colleges Can Work With Insurers   Since January 1, 2014, candidates from many of Georgia’s great colleges and universities, as well as candidates from other regional and national colleges, have started careers at Prium. For colleges and universities throughout the country, the “matchmaking” model helps them offer their students a proven job search option. Both Elizabeth and Ryan are thriving in their roles at Prium. Reflecting on being placed at Prium, Elizabeth said, “I never thought I would be working in the healthcare industry, and I hadn’t heard of Prium prior to interviewing. I never would have found this job on my own.” The labor market is changing rapidly at every stage of the process. Colleges, job-seeking grads and prospective employers all need a more efficient way to evaluate and select the right entry-level hires. Hearing success stories from young grads such as Elizabeth and Ryan show how effective an outsourced college-recruiting model can be in matching great candidates with rewarding careers in industries like insurance and healthcare — careers that most new grads would never consider.

I recently attended the Digital Marketing for Financial Services Summit (#DMFSToronto). Digital leaders from Citi, Facebook, Wells Fargo, MetLife, Allstate, Salesforce and more were there talking about what is working, not working and what is coming next within digital marketing for financial services. Five accelerating trends: 1) It’s all about the data. It has ALWAYS been about the data in digital marketing, but now with so many advancements in programmatic advertising, real-time media buying, CRM, data lake technology and data visualization services, it’s easier than ever to track results, test, learn and optimize your marketing efforts. Hari Pillai from Invesco spoke on a panel about a struggle many companies have — being data-rich but knowledge-poor. His keys to success were to create a strong infrastructure for your data and an API to simply and effectively leverage your data, so you know where the customer is in the journey. In his words, “Data is the secret weapon to move the customer down the journey.” See also: Data Science: Methods Matter (Part 2) 2) Customers matter more than ever. As we all know, the dynamic has flipped to a customer being in charge more than ever in the buying process. Fifty-seven percent of the purchase journey is done before a customer ever contacts a supplier per the CEB, so you need to listen to the key needs of your customers and figure out how to solve those needs. Ramy Nassar from Architech had a great presentation about focusing on customer needs instead of financial products. My favorite line from his presentation was, “Think about the need, not the transaction. No one wants to buy a mortgage, they want a house.” 3) Social will soon rule the world. The typical North American adult checks social media 17 times a day. SEVENTEEN! Combine that with the fact that cold calling and emailing response rates are hovering around 3-4%, and millennials preference for social as the No. 1 method of contact, and social will soon be taking over as the primary communication vehicle for marketing and sales. Any financial professional or salesperson who does not have a complete LinkedIn profile that is optimized for search will slowly begin to lose their client base. I spoke on the value of social selling to financial institutions in this new digital world and how to use the power of social media to generate leads and sales. See also: How to Capture Data Using Social Media 4) Wearables are not going away. If you are looking for the next big thing, wearables are it. How long is it until our Fitbit we use on a daily basis to track our steps starts feeding that information to doctors? Insurance companies? Retail stores? It’s a matter of time until everyone knows everything about everyone else. Enjoy your 15 remaining minutes of privacy! And be prepared to have everything measured and managed in real-time. Rachid Molinary of Banco Popular de Puerto Rico presented an informative use case on how the company quickly integrated mobile banking into wearable technology. Now you can check your BPPR account balance in a matter of seconds on your Apple Watch. What was even more impressive was the processes and systems they have put in place to bring this new tech to market in a short period of time. See also: The Case for Connected Wearables 5) The pace of change is fast (and will get faster). Mitch Joel gave a fantastic keynote about how fast the world is changing and how every company thinks they are being innovative. However, to truly create innovation is to “create something that the market did not know that it needed, that then becomes adopted (and paid for) in a way in which we could have never imagined our lives without it.” Not many companies are doing this today. Erin Elofson from Facebook spoke about their roadmap and how VR is playing a huge role in their future. To get a small glimpse of the company's VR capabilities, check out the first film shot with the new Facebook Surround 360 camera. This is just the snowflake on the tip of the iceberg. So, how will you and your company react to this new digital world in financial services? These changes are coming sooner than anyone expected. Those that adapt quickly will thrive, those that don’t will struggle to survive. Related articles

• The value of social selling
• Invalid traffic becoming a bigger problem in programmatic advertising
• 4 steps to social media content success

The best customer service representatives (CSRs) are a rare breed. Not only do the best understand the technical details, but they also have well-developed soft skills, including communication savvy, and grit. Because let’s face it, CSRs take their fair share of abuse. It’s not easy talking with customers all day, especially when those customers are often unhappy. Yet great CSRs can make or break your company’s image. Hanging on to CSRs who “get it” and are engaged in the essential job they perform is a must. Experienced agents and brokers know that’s easier said than done. Fewer than two-thirds of customer service employees are engaged, according to the 2015 Employee Engagement Trends Report from Quantum Workplace. That’s a lower rate than for almost every other department, including human resources and sales. A study from Bain & Co. looked at Net Promoter Scores (in part, a measure of how likely employees are to recommend their job to qualified family members and friends) and found that customer service ranked dead last among 10 common business departments. Retention rates for CSRs in insurance aren’t much better. Our industry had a 28% turnover rate for CSRs in 2015, according to data from ContactBabel. That’s slightly better than the average across industries, which hovers around 33%. Even Zappos, with its laser focus on customer service and employee culture, suffers a 20% annual turnover for CSRs. The high cost of losing employees and hiring and training replacements is well-established. A CallMe! survey found that the average turnover cost for a CSR is $3,500 per person. That’s the bad news. The good news is that you can take three specific steps to make sure you’re bringing in the right customer service reps—and keeping them. 1. Watch for resume red flags Not everyone is cut out to be a CSR. In fact, the top reason CSRs quit is that they were “just the wrong type of person for the job,” according to the ContactBabel report. Refine your hiring process so you’re employing only the right type of people for the job—otherwise, they’ll never be engaged. Watch for red flags in resumes, including a lot of short stints at past jobs, especially other customer service positions. Also, keep an eye out for experience that didn’t involve a lot of communication, such as in data entry, administration and so on. Give special attention to applicants with an interest in new technology and experience working with social media channels. And that cliché interview question, “Where do you see yourself in five years?” can actually give you a good idea about whether a person’s career goals align with your customer service values. Some agencies play one or two particularly unpleasant customer service calls to measure how a prospective CSR might react to the most difficult calls he may receive. Others role-play an interaction with a customer, headset and all. You want to make sure would-be CSRs know what they’re getting into. A little extra vetting during the hiring process pays off big-time in building an engaged team. See also: A Practical Tool to Connect to Customers 2. Treat them right Study after study has shown that if you want to boost CSR retention, you have to keep reps engaged. A little flexibility goes a long way in keeping people happy at work. Two-thirds of female CSRs are working mothers, meaning unexpected scheduling issues are going to come up. While the job itself requires CSRs to work set hours, finding ways to give CSRs the flexibility to find a suitable work/life balance will help them stay engaged. CSRs also want a chance to advance their careers. The International Customer Management Institute (ICMI) recently surveyed call centers on the top causes of CSR turnover. The most frequent source may surprise you: better opportunities inside the organization. But representatives don’t always see career opportunities within the call center itself. With CSR-to-supervisor ratios (known as span of control) averaging from 12:1 to 15:1, CSRs realize there’s a less than 10% chance they’ll ever be promoted to the level of their direct supervisor. That means you need to spell out the possibilities for advancement within the department. Consider adding titles—mentor, tech expert or shift supervisor, for example—so CSRs can increase their responsibility and compensation. You can’t offer a promotion with a big cash bonus to every representative. But other small rewards, from a quick thank you to public praise for handling a particularly tough call, can make day-to-day work much more enjoyable. See also: 3 Skills Needed for Customer Insight 3. Learn from departing reps If you’re not picking the brains of CSRs who quit, you’re missing out on a valuable source of information that your competitors are taking advantage of. More than 80% of organizations conduct exit interviews with departing agents, according to ICMI. Make sure your exit interviews attempt to reveal specific things your call center can do differently to keep good CSRs on the job. But you don’t have to wait until a CSR is headed out the door to figure out what she wants—instead, ask. A brief, informal survey about the perks they’d value most is an easy way to figure out where to focus your efforts. Armed with more information about the benefits and responsibilities CSRs prioritize, you’ll be better able to keep your best reps engaged and serving your customers.

As with most articles I read at Insurance Thought Leadership, I enjoyed The Myth of the Protection Gap. I do agree with the author (Paul Carroll) that not everything that can produce a negative outcome or loss needs to be insured. In fact, we are now in an era where we can buy insurance for nearly any property we own with a swipe of an app on a smartphone. Assuming that these companies are not charities, this approach is counterproductive, simply because it forces users to waste time having to remember to insure the thousands of small dollar items we own, when we can just afford to replace them. So place me in the camp that says insurance is for instances where we could not otherwise reasonably expect to be made whole again. But the protection gap itself is very real. I will use Paul’s hypothetical example to illustrate a counterpoint to his conclusion: “To make the math simple, let’s pick a country at random and make up some numbers out of whole cloth. Let’s imagine we’re Gabon, and we, as a nation, incur $1.5 billion of losses a year, while only $500 million is covered by insurance. We’re told we have a protection gap of $1 billion. We should buy $1 billion of additional coverage. It’ll only cost us $1.3 billion. That’s because — again, in very rough numbers — the insurer has to tack on 20% on top of the losses to cover expenses and needs its 10% profit margin to keep shareholders happy.” Let’s break this down: If the losses for Gabon are $1.5 billion per year, with $500 million covered, then how much insurance do they need to buy? The article is suggesting the answer would be an additional $1 billion. But that is not the right answer. The right answer is that Gabon should not buy any insurance! How is that possible? Well, if I know with certainty that my losses over time will be $1.5 billion, then instead of buying insurance I can set aside funds to pay those anticipated losses. To put it another way, if I were insuring an entity that will have $1.5 billion losses each year, then the premium I would charge MUST start at $1.5 billion (because I know for sure that those will be the losses ) and then tack on expenses for managing those claims, issuing paper and, of course, my profit margin. Am I nitpicking? Yes, I am. The hypothetical example likely meant that losses would average $1.5 billion per year and not BE $1.5 billion. But words matter, and, in this hypothetical example, the word “average” changes enough of the example to magically make the protection gap appear in full vengeance. How? Well, averaging $1.5 billion per year in losses can mean lots of things. It could mean $1.5 billion each year, every year, OR it could mean a $30 billion loss happening exactly once in the next 20 years (or an infinite set of other combinations). Uh-oh. It is this uncertainty in the losses that makes insurance such a valuable tool for risk management. Insurance is that tool that allows Gabon to manage its cash flows in such a way that it can function day after day and not have to worry about finding $30 billion at a moment’s notice. Insurance is not about paying for the average annual losses, it is about paying for the extreme losses and avoiding the cash flow crunch associated with that. The smoothing out of volatile cash flows IS the peace of mind that is often marketed to consumers of insurance. 90% of California homeowners lack earthquake insurance. The take-up for flood coverage is similar. These perils have caused hundreds of billions of dollars in property loss, the bulk of which were uninsured. Tens of thousands of families became homeless. We’ve seen it In Louisiana after Katrina and in the tri-state area after Sandy, and we will see it again. The protection gap is not a myth, it is very real, and these perils will continue to cause hundreds of billions of dollars in damage. These are losses that homeowners and businesses cannot fund themselves. They require insurance to protect them from these catastrophes. This fact alone provides a wonderful opportunity for our entire industry to grow by solving huge and emerging problems faced by societies. This is why we exist; this is our irreplaceable contribution to society.

No matter how robust a company’s cyber defenses, the bad guys seem to find a way to get in. And when — not if — they do, it could take weeks, or even months, to detect them and assess the damage. Building off the premise that spending a lot of money “trying to prevent the bad guys from getting in” is an imperfect approach, Vectra Networks wants to help cybersecurity teams track down and stop attackers once they’re inside the network — not before they get there. “The core problem is that all the sensors the company has invested in — firewalls, sandboxes, AV — act as a good filter, but they don’t stop everything from getting in,” says Vectra’s chief technology officer, Oliver Tavakoli. “We’re single-mindedly focused on finding that intruder inside your network before the FBI calls you and tells you about it.” Using machine learning and some of the same techniques used to sequence DNA and improve search engines, the company has developed a platform that looks at patterns to detect anomalies and trigger a mitigation response. Vectra isn’t advocating forgoing the traditional filters like firewalls and reputation lists — it’s still important to practice good cyber hygiene, Tavakoli says. But that’s no longer enough. “Presuming the filters are 100% perfect is a recipe for the kind of breaches we see in the news,” he says. So Vectra’s product, a platform software called X-series, picks up where those traditional security tools stop and provides real-time detection of an attack that’s in process. Instead of signature- and reputation-based methods, Vectra uses machine learning, data science and behavior analysis — an approach that’s much more effective in stopping the types of high-profile breaches that have dominated headlines of late. See also: What You Must Know on Machine Learning The platform, which was launched in 2014, is typically deployed with an on-premises appliance that sits within the data center and monitors packet traffic. Customers also can opt for a virtual appliance using another product, S-series sensors. The service is subscription-based, based on the amount of traffic that’s being processed.

Vectra’s chief security officer, Günter Ollmann, says, in the past, traditional tools relied on blacklists, two-dimensional signatures and behavioral analytics, which are all driven by human decisions. But the threats develop so fast that those techniques don’t keep up with the bad guys. “Machine learning is doing a much better job of … creating multidimensional signatures for detecting what’s going bad,” Ollmann says. Machine learning works in two ways: supervised and unsupervised. With supervised learning, humans tell the machines which behaviors are good and which are bad, and the machines figure out the commonalities to develop multidimensional signatures. In the past, Tavakoli explains, humans had to look at large sets of data to try to distinguish the good characteristics from the bad ones. With machine learning, it’s essentially about training the computer to find those differences — but much faster. “Supervised machine learning involves the machine doing 95% of the work and the data scientists doing the 5%,” Tavakoli says. With unsupervised learning, the machines develop the algorithms without having the data labeled, so they analyze the clusters to figure out what’s normal and what’s an anomaly. “That’s a slower detection, but it detects things that humans and those high-fidelity signatures would never be able to see,” Tavakoli says. Founded in 2012, Vectra set its sights on machine learning when the concept was still novel. The company, which came out of stealth mode in March 2014, immediately focused on a broad range of sectors. Now in what Tavakoli calls its “adolescent stage,” Vectra has gone through several phases of funding (for a total of about $75 million) and has grown to 125 employees as well as sales offices in Europe. See also: How Machine Learning Changes the Game “We believe the market is not limited to a few verticals because it’s a broad problem,” Tavakoli says. That means that for the next year or so, the company’s energies are focused on gaining sales momentum and scaling all its processes and operational capacity as the organization matures. The timing seems fortuitous, now that machine learning and automation are becoming the new frontiers for cybersecurity. And that’s what’s given the platform a broad appeal, according to Tavakoli: the ability to do the heavy lifting for humans, especially as the industry is experiencing a shortage of human resources. “You see a real renaissance nowadays when you hear about machine learning in all types of markets, and those techniques are being applied to a much broader set of problems than they were historically,” Tavakoli says. He believes it’s the machine learning that will fulfill the promise that big data holds, not yet through complete autonomy but rather as a leveraging point. “The whole world is swimming in a large amount of data being collected from all sorts of things, and people are struggling to pull value out of that data,” he says. “Machine learning and data science are at the vanguard of unlocking the information that’s hidden inside the data — and cybersecurity is just one such application.” This article first appeared at Third Certainty. It was written by Rodika Tollefson. More stories related to data security : JP Morgan Chase caper offers frank lessons about insider theft Predictive threat intelligence roots out cyber threats before they occur Biggest identity theft threat? Downplaying your risk

Heart disease, lung cancer and other non-contagious health issues, many of which are at least partially avoidable through changes in lifestyle, are costing the economy hundreds of billions of dollars every year. Today, non–communicable diseases (NCDs) are already responsible for half of all deaths worldwide – and this figure is projected to increase by 17% over the next decade. Of particular concern for businesses: More than half of those affected by NCDs are of working age. This is why this isn’t just a human tragedy, it’s an economic one — which is why combating the rise of NCDs should not only concern public health authorities. It could even be a sensible investment for encouraging future economic growth: The World Economic Forum estimates that costs related to NCDs will account for as much as 4% of annual global GDP by 2030. That is a staggering $47 trillion. Perhaps surprisingly, these silent illnesses are affecting more people in the developing world than in the developed. The greatest increase, 27%, is projected in Africa, with sub-Saharan countries stuck with the worst predictions. In lower-income countries, it is primarily respiratory diseases that are the biggest killer, often linked to smoking and poor air quality, while heart disease and stroke, associated with sedentary lifestyles, are the biggest killers in richer countries, according to WHO data. The rise of NCDs is increasingly undermining the productivity of workers all over the world and has devastating effects on the economic potential of the poorest of nations. Boosting the health levels of employees and participating in public-private partnerships to reduce the impact of NCDs in wider society should be seen as a profitable strategy, not a burden. In Depth Two myths surround non-communicable diseases: that they primarily affect people in wealthy countries and that they are a disease of the old. Historically, that was the case. Cancer, diabetes, respiratory or heart diseases were an illness of the developed world, largely caused by risk behaviors such as smoking, drinking, living a sedentary lifestyle and having a bad diet. Today, of the 38 million people who die each year from NCDs, 28 million live in developing countries. That is a 40% increase since 1990. “While it may seem easy for businesses to ignore this trend, especially in markets with government-centric health systems,” says Jim Winkler, chief innovation officer of Aon Health, “organizations need to focus on the adverse impact poor health has in the ability for working people to do their jobs effectively.” Business leaders are beginning to take notice. The World Economic Forum’s Global Competitiveness Report shows that about half of all business leaders worry that at least one of the four biggest NCDs (heart disease, cancer, diabetes and lung disease) will hit their company’s bottom line, especially where the quality of local healthcare is poor. A disproportionate 80% of deaths from NCDs are premature, taking the lives of people during their most economically productive years. The WHO says that 23% of Indonesian people between the ages of 30 and 70 are expected to die from NCDs. In the U.S., this figure is 14%. “Chronic and complex diseases such as heart disease, diabetes and other obesity-related conditions lead to declines in physical output, mental acuity and emotional resiliency,” Winkler warns. All of these will affect productivity — which is why this is a growing crisis not just for people’s health but also for the global economy. The Economic Burden of NCDs Hundreds of studies have linked individual NCDs with economic losses. The World Economic Forum and the Harvard School of Public Health estimate that people dying of heart disease in India (26% of all deaths) will cost the economy $2.7 trillion from 2012 to 2030. Along with other NCDs and mental illnesses, the total economic loss — measured by taking into account money spent by health providers on treatment and the reduction in the number of working people due to deaths — will be two and a half times the country’s GDP in that period. Productivity losses for businesses due to NCDs can be measured by calculating the cost of Disability Adjusted Life Years (DALYs), sick leave, unemployment and days lost by caregivers. In Nigeria, more than half of stroke survivors take a year and a half to return to work. A comprehensive study by the European Journal of Epidemiology found that the workplace productivity of stroke victims’ caregivers also continues to fall one to two years after they become carers. The same study found that, in the U.S., absenteeism one year after a cancer diagnosis costs the economy $20.9 billion annually. Aon’s European Sick Leave Index report, meanwhile, found the average direct cost per individual sick leave day was at least €160. How Can Business Help? The WHO has put combatting NCDs at the forefront of its agenda, with businesses playing an important role in helping stop the spread of the epidemic. The 2013–20 Global Action Plan for the prevention and control of NCDs calls for a collaboration between states, NGOs and the private sector to develop affordable strategies that would help prevent the continued rise of these diseases. The cost of inaction far outweighs the potential economic benefit of taking action on NCDs. The WHO calculates that implementing its Global Action Plan proposals would come in at just $1.20 per person per year. Business leaders are increasingly aware of the benefits that health programs bring to the organization. Aon’s 2015 Health Care Survey found that the top change U.S. employers want to implement in their rewards system to appeal to the 2020 workforce is “more opportunities and support to connect health and wealth.” The spread of NCDs is a trend that businesses should not ignore. They are increasingly taking the lives of people during their most productive years and have a huge impact on productivity before, during and after their development. The question is not whether businesses should act upon this global epidemic, but how. These initiatives not only save lives but help businesses reduce healthcare costs and productivity losses. For instance, Johnson & Johnson’s health and wellness program saved the company $250 million on health care costs over 10 years. The return on investment was $2.71 per dollar spent on tackling smoking and physical inactivity. To tackle this growing global crisis, targeting the risk behaviors that increase the chances of dying from NCDs is key. This is where businesses can have a significant impact — by improving availability of healthy food, promoting physical activity, setting up programs to help employees quit smoking and giving better access to preventative healthcare. Talking Points “The challenge… goes beyond health ministries… Non-communicable diseases undermine productivity and result in the loss of capital and labor. These costs are unbearable and clearly call for innovative solutions and an all-of-society approach, with strong partnerships between government, the private sector and civil society.” – David Bloom, member of the World Economic Forum Global Health Advisory Board and professor at the Harvard School of Public Health “Creating an effective, collaborative response against NCDs requires cross-sector and cross-industry action – it can’t be achieved by any one business, nor one sector alone.” – Dr. Fiona Adshead, chief wellbeing and public health officer at Bupa “We should encourage individuals to make the smart choices that will protect their health.  Exercise, eat well, limit alcohol consumption and stop smoking. We can do more than heal individuals — we can safeguard our very future.” – Ban Ki-moon, secretary-general of the United Nations “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 to Shrink Employees’ Waistlines to Help Your Bottom Line – The One Brief, Sept. 8, 2015
• People Are Living Longer — But There’s a Catch – Business Insider, Sept. 10, 2015
• Blueprint to Combat Non-Communicable Diseases Released – BusinessWorld, Oct. 29, 2015
• WHO Decision Is Critical to the Fight Against Obesity and Non-Communicable Diseases – The Lancet Global Health Blog, Oct. 21, 2015
• Wanted: A Road Map to Tackle Non-Communicable Diseases – The Hindu Business Line, Oct. 16, 2015
• European Sick Leave Index – Aon report
• 2015 Health Care Survey – Aon report

Data science has grown in inevitability as it has grown in value. Many organizations are finding that the time they spend in carefully extracting the “truth” from their data is time that pays real dividends. Part of the credit goes to those data scientists who conceived of a data science methodology that would unify processes and standardize the science. Methods matter.  In Part 1 and Part 2 of our series on data science methods, we set the stage. Data science is not very different from other applied sciences in that it uses the best building blocks and information it can to form a viable solution to an issue, whatever that issue may be. So, great care is taken to make sure that those building blocks are clean and free from debris. It would be wonderful if the next step were to simply plug the data into the solution and let it run. Unfortunately, there is no one solution. Most often, the solution must be iteratively built. This can be surprising to those who are unfamiliar with data analytics. “Doesn’t a plug-and-play solution just exist?” The answer is both yes and no. For example, repeat analytics, and those with fairly simple parameters and simple data streams, reusable tools and models, do exist. However, when an organization is looking for unique answers to unique issues, a unique solution is the best and only safe approach. Let’s consider an example. See also: Forget Big Data -- Focus on Small Data In insurance marketing, customer retention is a vital metric of success. Insurance marketers are continually keeping tabs on aspects of customer behavior that may lead to increasing retention. They may be searching for specific behaviors that will allow them to lower rates for certain groups, or they may look for triggers that will help the undesired kind of customer to leave. Data will answer many of their questions, but knowing how to employ that data will vary with every insurer. For example, each insurer’s data contains the secrets to its customer persistency (or lack thereof), and no two insurers are alike. Applying one set of analytically derived business rules may work well for one insurer — while it would be big mistake to use the same criteria for another insurer. To arrive at the correct business conclusions, insurers need to build a custom-created solution that accounts for their uniqueness. Building the Solution In data science, building the solution is also a matter of testing a variety of different techniques. Multiple models will very likely be produced in the course of finding the solution that produces the best results. Once the data set is prepared and extensive exploratory analysis has been performed, it is time to begin to build the models. The data set will be broken into at least two parts. The first part will be used for “training” the solution. The second portion of the data will be saved for testing the solution’s validity. If the solution can be used to “predict” historical trends correctly, it will likely be viable for predicting the near future as well. What is involved in training the solution?   A multitude of statistical and machine-learning techniques can be applied to the training set to see which method generates the most accurate predictions on the test data. The methods chosen are largely determined by the distribution of the target variable. The target variable is what you are trying to predict. A host of techniques and criteria are used to determine which technique will work best on the test data. There is a bucketful of acronyms from which a data scientist will choose (e.g. AUC, MAPE and MSE). Sometimes business metrics are more important than statistical metrics for determining the best model. Simplicity and understandability are two other factors the data scientist takes into consideration when choosing a technique. Modeling is more complex than simply picking a technique. It is an iterative process where successive rounds of testing may cause the data scientist to add or drop features based upon their predictive strengths. Not unlike underwriting and actuarial science, the final result of data modeling is often a combination of art and science. See also: Competing in an Age of Data Symmetry What are data scientists looking for when they are testing the solution? Accuracy is just one of the traits desired in an effective method. If the predictive strength of the model holds up on the test data, then it is a viable solution. If the predictive strength is drastically reduced on the test data set, then the model may be overfitted. In that case, it is time to reexamine the solution and finalize an approach that generates consistently accurate results between the training data and the test data. It is at this stage that a data scientist will often open up their findings to evaluation and scrutiny. To validate the solution, the data scientist will show multiple models and their results to business analysts and other data scientists, explaining the different techniques that were used to come to the data’s “conclusions.”  The greater team will take many things into consideration and often has great value in making sure that some unintentional issues haven’t crept into the analysis. Are there factors that may have tainted the model? Are the results that the model seems to be generating still relevant to the business objectives they were designed to achieve? After a thorough review, the solution is approved for real testing and future use. In our final installment, we’ll look at what it means to test and “go live” with a data project, letting the real data flow through the solution to provide real conclusions. We will also discuss how the solution can maintain its value to the organization through monitoring and updating as needed based on changing business dynamics. As a part of our last thoughts, we will also give some examples of how data projects can have a deep impact on the insurers that use them — choosing to operate from a position of analysis and understanding instead of thoughtful conjecture. The image used with this article first appeared here.

Most entrepreneurs don’t just want to be entrepreneurs—they have to be entrepreneurs.   As a driven entrepreneur in the insurance industry, you will encounter both challenges and rewards far beyond that of the average employee. Navigating these ups and downs can be as challenging as steering a ship through a storm on the high seas, but I’ve done both—and lived to tell the tale. The lessons I learned sailing the seas have served me just as well on land. Here are five tips about entrepreneurship that sailing has taught me:

1. Know the terminology

In sailing, understanding boating terms like aft, starboard and leeward is vital to working with your crew and operating your vessel. The same is true in business. If you can`t speak the language of your clients and your competition, your next deal may get lost in translation.   Attending conferences and taking courses are both great ways to learn new terms and highlight that there`s a reason why you’re the expert.

2. Use trends like the wind

When sailing, jibing and tacking help you manipulate the winds to steer your vessel in the right direction. In business, trends are your winds, and you need to understand which direction they`re heading. Take a few minutes every day and bring yourself up to speed on the latest global and local trends. Aggregators like Feedly or SmartNews, along with social media feeds, keep you on the cutting edge and aware of which way the wind is blowing.

3. Learn when to tighten or ease the sheet

The sheet is a line or rope used to adjust a sail against a force of wind.   In business, you need to think about when to tighten or loosen your budget and your business’s growth in line with your sales cycle and market forces. Markets ebb and flow, and your business will, too. Tracking these fluctuations over time will help determine the ideal time to launch marketing campaigns and hire employees, or to tighten the purse strings.

4. Adjust quickly and wisely to a changing climate

The weather can change in an instant when you’re sailing, and you need to know how to use the sails to compensate, navigate under tough conditions and capitalize on whatever’s thrown at you. It`s not much different when you`re a leader in business. Like the weather, business is always moving and changing. Whether you`re steering your ship at sea or driving your business on land, it takes experience and at times raw courage to weather a storm. See each storm as a chance to gain experience for the next one and know that sometimes you simply need to batten down the hatches – and wait it out.

5. Be a decisive captain

It can take an entire crew to run a sailboat, but they won’t work effectively without a captain calling the shots. The crew rely on your vision, tenacity and experience to guide their actions. Without this direction, no one will know which way to travel. As the captain of a ship or a business, you spend your days adjusting your sails, guiding the crew and at times navigating dangerous waters. If you’re on the verge of starting a business or taking it in a new direction, remember one thing above the rest – always keep your hand on the helm and keep in mind: The pessimist complains about the wind. The optimist expects it to change. The leader trims the sails and sets a new course.

This is Part 3 of a four-part series. Part 1 can be found here. Part 2 can be found here. What if Leonardo Da Vinci had been alive to witness the digital revolution? Perhaps he would have been a sought-after consultant and speaker (after his start-up had gone public and his paintings were selling for millions)! Da Vinci was, according to historian Will Durant: “The most fascinating figure of the Renaissance… [He] took fondly to mathematics, music and drawing. In order to draw well, he studied all things in nature with curiosity. Science and art, so remarkably united in his mind, had one origin — detailed observation.” According to Da Vinci, a scientist should look at experience and observation before applying reason to any experiment. He uniquely had both a right brain and left brain perspective, the art and the science view, that looked at facts but then creatively used them to innovate — highlighting the power of observation. And Da Vinci’s observations are still with us today. For insurers, the power of observation is no less important than it was during the Renaissance. In fact, observation’s power for change and growth, using nearly any measurement (e.g. dollars, longevity, capacity for change, lowered risk) would certainly far exceed its Renaissance power. Insurance’s pervasiveness and necessity (it underpins economies to enable them to grow) make it globally and individually life-altering. If insurers wish to tap into the power of observation, in which direction should they look? The simple answer is that they should look at trends. But to fully explore trends, it will help us to split them into subcategories, such as purchase trends, lifestyle trends, customer preferences and commercial/industrial trends. Observing Purchase Trends This is the most obvious of the trends, yet it may be one of the most overlooked trends. How do people buy? What differences are there between segments such as millennials, baby boomers and small business owners? This goes beyond, “Well, they seem to be using the internet and mobile phones.” Observing purchase trends takes everything into consideration — Where are people when they are using their mobile phone or other mobile device? Where are people when they realize they have the time, need and inclination to purchase insurance? Is there a cosmic moment when the right offer at the right time with the right channel yields a magical response? See also: Data Science: Methods Matter (Part 2) This kind of observation can certainly be informed by trends and disruption within other industries. For a quick example, consider how iTunes created a profitable shortcut in the music purchase process (as well as dispensing with a physical product, all of its delivery methods and costs). Then think about how Spotify, Amazon Music, YouTube, Pandora and SoundCloud have all dented iTunes demand and caused its prices to look exorbitant. The lesson for insurers is twofold: 1. Capitalize on opportunities to be in the right place at the right time with market targets, and 2. Be vigilant in price response, service response and capitalizing on the next idea. Now that insurance is changing, it won’t stop. Perpetual observation, along with incubation and concept testing, will provide a foundation of market safety — if the organization is committed to acting on what it learns. This means continuous incubation and market testing of innovative products and services, likely outside of the normal insurance operations and systems structure — being creative and acting like a start-up. Observing Lifestyle Trends Insurance is so tightly bound to lives and lifestyles that it is imperative that insurers keep tabs on how lifestyles are changing. For example, in 2014, single adults in the U.S. began to outnumber married adults. How does that affect insurers with products that may seem to reward families with discounts and lower rates (i.e for multiple vehicles)? The sharing economy is also becoming mainstream, not only with services like Uber and Lyft, but also with shared office spaces, shared living arrangements and shared vacation residences growing in popularity. The sharing economy is all about the sharing of assets rather than ownership of them. Is it time for insurers to start thinking less in terms of insuring property owned or mortality and instead begin thinking in terms of insuring life experiences that may occur over short spaces of time, rather than for years? The rider in the Uber and the vacationer in the Airbnb may feel far more comfortable if they have the insurance for that specific time and need  — knowing that no matter where they are, and no matter what happens, they have access to insurance. Once again, this requires direct observation and then using the observations to creatively rethink insurance. Demographic studies that account for the next three, five and 10 years can even help insurers predict lifestyle patterns before they become mainstream, capturing the opportunity early and gaining market share. Observing Customer Preferences Many newspapers are losing money or are fading away. Bookstores are closing. Large department stores are somewhat outmoded. Bricks and mortar retail outlets are struggling to stay relevant. Purchases of used goods have never been higher. Online purchases have never been higher. What does this tell us about consumer buying preferences? What does it mean to insurers? The digital transformation of buying that is playing out is unprecedented. But does it mean agent sales aren’t the future or that un-tailored, high-volume products are no longer needed? The answer is no. In many cases, the answer is to increase an understanding of preferences at both a high level (market trending) and an individual level (preference trending). Preferences change frequently, so market analysis and segmentation underpinned by data and analytics play an important role in understanding where reality is at any one point in time. For observant insurers that care about growing their business, building an excellent customer experience and acting on a real knowledge of market trends and individual preferences will strengthen customer satisfaction and retention. It will also build loyalty among market segments that are changing or traditionally hard to keep. See also: 3 Skills Needed for Customer Insight Observing Commercial/Industrial Trends   What do Samsung clothes dryers, FitBits and connected cars have in common? All of them have IoT sensors, all of them have digital connectivity to mobile devices and … they are all relevant to insurers. When skateboarders started using GoPros (and posting videos to YouTube) and iPhones started locking themselves in cases of theft, insurers should have started paying attention. Drone technology, camera technology, GPS tracking, step measurement — all of these advances will play a role in insurer offerings, capabilities and services. But technological advancements are only the beginning of commercial trends that insurers can use. As commerce changes and as processes and products adapt, informed insurers will be able to support the changing needs of organizations. Start-up businesses and small businesses will be looking for ways to insure venture capital and other investments against loss. Drone and unmanned aircraft insurance needs will grow. Data protection and cyber security insurance needs will continue to grow. The insurance Renaissance will change the needs of companies and individuals as they embrace new market trends, technologies and as they reshape their preferences. This will likely mean a decrease in demand for some traditional products such as auto insurance or individual life insurance. But, at the same time, it opens the door for new products that embrace the changes. Just look at companies like John Hancock with its Vitality product, as well as insurers providing risk avoidance services using IoT in their homes or those offering shared transportation insurance. For observant insurers that grasp the way financial and business models are changing, there will be excellent opportunities to supply innovative products and risk preventive services. The key will be in the observation. Insurance is the economic foundation for economies, businesses, families and individuals, enabling them to operate or live life fully and with confidence. Our responsibility as an industry is to continually observe the changes that are happening inside and outside of the industries we serve, adapt to those changes with innovative products and services that meet changing customer needs, and do it with speed, capturing the opportunities unfolding before our eyes. In my next post on the insurance Renaissance, we’ll see how re-envisioning financial and business models may be one of the ways that insurers can prepare for a new era of progress and success.

For a while, I have been saying that one of the reasons for the disconnect between senior executives and risk practitioners is the latter’s language. Leaders of the organization speak in plain English about the achievement of corporate objectives such as earnings, profits and projects. Leaders of the risk management function talk about risks, impact or consequences and sometimes talk in technobabble about terms that only risk practitioners and statisticians understand, such as “risk capacity,” “alpha” and “residual risk.” See also: How to Remove Fear in Risk Management The traditional way of explaining the risk management process is (per ISO 31000):

• Establish the context
• Identify risks
• Analyze risks
• Evaluate risks
• Treat risks
• Communicate and consult (throughout the above)
• Monitor and review (continuously)

Can this be translated into plain English? How about this:

• Anticipate what might happen
• Analyze the possibilities
• Ask: Is there a problem? Can we do better?
• What are the options? Can we improve them?
• Which is best?
• Decide
• Act
• Review/monitor/learn

I especially like the work anticipate. It’s better than talking about “uncertainty,” another word that risk practitioners understand (I hope) but that executives find difficult. See also: How Risk Management Drives Up Profits Isn’t risk management all about anticipating what might happen between where we are and where we want to be? I welcome your thoughts. Can we practice risk management in plain English and help leaders make intelligent and informed decisions without even knowing that this is “risk management”?