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Why You Business May Not Be Ready for Analytics

January 4, 2018 /

Artificial intelligence is on the minds of business leaders everywhere because they’ve either heard or believe that AI will change the way companies do business.

What we’re seeing now is just the beginning. For everyone’s sake, more thought needs to be given to the workforce impact and how humans and machines will complement each other.

Recently, professional services company Genpact and FORTUNE Knowledge Group surveyed 300 senior executives from companies in the North American, European and Asia-Pacific regions with annual revenues of $1 billion per year or more. According to the report, “AI leaders expect that the modern workforce will be comfortable working alongside robots by 2020.”

However, getting there will require a different approach to organizational change.

“A bunch of people are thinking about AI as a technology. What they’re not thinking about is AI as the enabler of new enterprise processes, AI as an augmenter of humans in enterprise processes,” said Genpact Senior Vice President Gianni Giacomelli. “Right now, 70% of the effort is spent on technology, 20% on processes and 10% on humans as a process piece. I think that’s the wrong way to look at it.”

What is the right way to think about AI? At one end of the spectrum, people are touting all the positive things AI will enable, such as tackling some of our world’s biggest social problems. On the other end of the spectrum are Elon Musk, Stephen Hawking and others who foresee a dark future that involves unprecedented job losses if not human extermination.

Regardless of one’s personal view of the matter, business leaders need to be thinking harder and differently about the impact AI may have on their businesses and their workforces. Now.

How to think about the problem

The future’s trajectory is not set. It changes and evolves with technology and culture. Since AI’s end game is not completely foreseeable, one way to approach the problem, according to the survey, is to begin with the desired outcome, think about the processes required to achieve that outcome and then ponder how machines and humans can complement each other.

“Generally, the biggest impediment we see out there is the inability to create a portfolio of initiatives, so having a team or a number of teams coming back and saying, ‘These are the 50 things I could do with AI based on what AI is able to do today and in the next 12 months,’ and then [it’s up to senior management to] prioritize them,” said Giacomelli. “You need to have people going through the organization, unearthing places where value can be impacted.”

Over the last three decades or so, business leaders have been setting strategy and then implementing it, which isn’t going to work moving forward. The AI/human equation requires a hypothesis-driven approach in which experiments can fail fast or succeed.

“It’s a lot more about collective intelligence than let’s get a couple of experts and let them tell us where to do this. There are no experts here,” Giacomelli said.

Focus on the workforce

AI will impact every type of business in some way. The question is, what are business leaders doing to prepare their workforce for a future in which part or all of their jobs will be done by AI? According to the survey, 82% of the business leaders plan to implement AI-related technologies in the next three years but only 38% are providing employees with reskilling options.

“I think HR functions are completely backwards on this one,” said Giacomelli. “They haven’t started connecting the dots with what needs to be done with the employees.”

Some companies are already working on workforce planning, but they view AI as a means of materially reducing the workforce, such as by 20% or 30%, which Giacomelli considers “a primitive approach.”

“There are jobs that will go away completely. For example, people who do reconciliation of basic accounts, invoices, that kind of stuff,” he said. “Most of the jobs that will be impacted will be impacted fractionally, so part of the job is eliminated and then you figure out how to skill the person who does that job so she can use the machine better.”

What would people do, though? It’s clear that most working professionals have various types of experience. The challenge for HR is to stop looking at a snapshot of what a candidate or employee is today and what prior experience has qualified them to do what they do today. Instead, they should consider an individual’s future trajectory. For example, some accountants have become sales analysts or supply chain analysts.

Looking for clues about what particular roles could evolve into is wise, but that does not provide the entire picture, since all types of jobs will either evolve or become obsolete in their current forms.

“I don’t feel that many people are looking at the human element of digital transformation and AI except fearful people,” said Giacomelli. “Every year, we will see people somewhere making sense of this riddle and starting to work in a different way. I think we need to change the way we look at career paths. We’ll have to look at them in a hypothesis testing way as opposed to have a super guru in HR who knows how AI will impact our career paths, because they don’t [know].”

The bottom line is that individuals need to learn how to learn because what AI can do today differs from what it will be able to do tomorrow, so the human-and-machine relationship will evolve over time.

Even if AI was just a science fiction concept today, the accelerating paces of technology and business underscore the fact that change is inevitable, so organizations and individuals need to learn how to cope with it.

Don’t dismiss the other guy

AI proponents and opponents both have valid arguments because any tool, including AI, can be used for good or evil. While it’s true AI will enable positive industrial, commercial and societal outcomes, the transition could be extremely painful for the organizations and individuals who find themselves relics of a bygone era, faster than they imagined.

AI-related privacy and security also need more attention than they’re getting today because the threats are evolving rapidly and the pace will accelerate over time.

An important fundamental question is whether humans can ultimately control AI, which remains to be seen. Microsoft’s Tay Twitterbot demonstrated that AI can adopt the most deplorable forms of human expression, quickly. In less than 24 hours, that experiment was shut down. Similarly, a Facebook chatbot experiment demonstrated that AI is capable of developing its own language, which may be nonsensical or even undecipherable by humans. So risks and rewards both need to be considered.

 

How to Get Educated About Analytics

December 26, 2017 /

Analytics education is anything but static. It’s so hot now that lots of education-focused organizations are offering traditional degree programs, online degree programs, certifications and courses.

As we well know, analytics capabilities and best practices are evolving, as is the application of analytics to business problems. In addition, there’s still a shortage of data-savvy people. All of that is creating demand for analytics-oriented education which is and has paved the way for so many new offerings. The question is, which option is best for you?

There are a number of ways to answer that question, some of which are more productive than others.

If you go online, you may find yourself overwhelmed by the choices. If you contact someone from any one of those organizations and ask their advice, they’ll probably tell you their program is the best.

In my view, there is no one best option. The answer depends on several factors which include the amount of time you have to dedicate to the program, the focus of the program and the cost (assuming your employer won’t cover the cost).

Probably the most frustrating approach is to look at the growing haystack using a Google search and start clicking on the endless stream of links. If you do that, you’ll probably be more confused than when you started your search. Lists of “top schools” may help narrow the focus as may a few suggestions below.

Degree or Certificate?

Data analytics degree programs didn’t exist until recently. So, if you lack an analytics degree, you’re in good company. Many universities offer formal BA/BS and/or MA/MS programs now, and they may have online degrees or certifications as well. For example, the W.P. Carey School of Business at Arizona State University offers MA and BA degrees in Analytics which can be earned online or as a full-time student. MIT Sloane School of Managementoffers a one-year Master’s degree program, an undergraduate degree, and a certification program, albeit for graduate students. However, MITx (an online MIT entity) has an online data science certificate program, which I can vouch for personally.

Degrees and certificates don’t carry the same weight, especially if you lack prior relevant work experience. A degree represents a level of mastery and years of dedication. However, employers are also well-aware that analytics degrees are new. Even if the degrees weren’t new, deep experience and a certificate or no certificate might be more valuable, depending on the candidate and position. A certificate also suggests a level of mastery, albeit the kind that can be earned in weeks or months versus years. If you have a some kind of degree, such as a business or information systems degree, analytics-related certification tends to indicate a dedication to continuous learning, which is a good thing.

There are a few other points to consider such as the school’s pedigree, how long they’ve had programs, what students and former students think of them, the companies that work with them, and the companies that hire from them. If you’re using education as a means to a promotion, find out what matters most to your employer.

Also realize that two programs with the same title can differ greatly in terms or course material, focus, faculty competency and how well faculty members communicate. Some professors or instructors are very articulate and easy to understand, even when they’re presenting highly technical material. Some are not.

In addition, understand your limitations because certification courses tend not to list prerequisites, like degree programs. For example, (and not surprisingly), a course may require students to use Microsoft Excel Professional Edition at a minimum. That’s may not a problem if you have access to the program at work, but if you don’t already have the software, be prepared to invest more than you anticipated in your certification. Similarly, some courses require a deeper background in math than others.

Self-study

Online courses tend to emphasize that the coursework can be accomplished on a “flexible” schedule but you may be required to repeat the course in a particular time frame to earn the certificate. You may think that’s not a problem because you’re psyched! Then life happens. If you suspend your study of such a program, you may be required to start from the beginning when the next class begins.

Part of the reason some self-study programs work within a given time frame is that it gives the “class” the ability to interact with the faculty and other students. EdX has many such programs, some from top universities, including MIT.

One of the cool things about EdX is you can take courses for free and only pay if you want the certificate associated with the class. The class may still start and stop at particular dates, but hey, the classes are free so you can get the syllabus, go through a module or two and see whether the course is suited to you. Right now, EdX has 122 online courses available that focus on analytics. Some of them are broad, such as the ColumbiaX Statistical Thinking for Data Science and Analytics. Others are narrow including the UC BerkeleyX https://www.edx.org/micromasters/berkeleyx-marketing-analytics course in Marketing Analytics.

It’s Your Choice

If you ask 10 people about which degree, certificate or course you should pursue, you’ll probably get 10 different answers. Ultimately, your path should align with your interests and career goals.

That said, if your choice requires a heavy investment in time, money or both, don’t make the decision in a vacuum. Consider some of the points above, talk to people and do some research so you have a better idea of what’s really right for you.

One Point the Equifax Breach Drives Home

December 18, 2017 /

oday’s developers use more third-party and open-source components, libraries and frameworks than ever to deliver and update products in ever-shrinking delivery cycles. In the race to get to market, it’s easy to overlook or ignore details that can lead to a security breach.

For example, Equifax blamed its recent security breach on an Apache Struts vulnerability (CVE-2017-9805) and later admitted it failed to install a patch. That patch had been available for six months, according to The Apache Foundation.

“The Equifax hack is so interesting, mostly because their response to the hack has been so poor. Blaming a hack on any sort of software issue – open source or proprietary – is simply part of their inadequate response. It’s a ‘the dog ate my paper’ excuse,” said James Stanger, chief technology evangelist at CompTIA. “That’s not much of an explanation, especially considering that Equifax disclosed this problem on September 7 after knowing about it since July 29. ”

What if the software you built was compromised and you discovered that the root cause was a third-party building block you used? You didn’t build that piece of software, after all, so perhaps that party should be liable for any damages that piece of software caused.

Practically speaking, good luck with that argument.

Little or No Third-Party Liability

If you’re using third-party building blocks in your software, which you likely are, the buck stops with you. Sure, someone else’s code may have caused a catastrophic failure, but did you read the fine print in the license agreement?  Third-party developers have several ways of dealing with the matter contractually.

“There may be disclaimers, especially in the open source community, that say, ‘This component is [provided] as-is’ and you as the licensee are responsible for its testing and usage in another system,” said Roy Hadley, Jr., co-chair of the Privacy & Cybersecurity team at law firm Thompson Hine “If you choose to use it in a nuclear facility or the space shuttle, that’s on you.”

“This WAS a different cybersecurity conference experience, and I really enjoyed all of the interaction and honest discussions.” (2017 Attendee) LEARN MORE

Those who use third-party software in their products are ultimately responsible because the provider can’t foresee how its software will be used or configured by others. So, the licensor protects itself using an “as-is” clause or a limitation of liability. Alternatively, the licensor may require indemnity from the licensee, which means if you use third-party software, something goes wrong and the provider of the component you use gets sued, you’re liable.

What Software Developers Should Do

Test, test, test. Ideally, developers should take the time to understand every piece of third-party software they’re using to make sure it does what it’s supposed to do and that it’s been tested for security vulnerabilities. They should also have a mechanism to ensure that the associated updates and patches are up-to-date.

“I think you have an absolute responsibility to make sure that third-party components work, work together and work the way they’re supposed to,” said Jason Wacha, an attorney and founder of  WS Law Offices which specializes in software licensing. “One of the things about the open source community is you hear [about a software vulnerability], they announce it and everybody jumps on it and tries to fix it. Certainly this was true for the Struts project. One of the things about proprietary software is if someone discovers a vulnerability, it’s not going to get out there and people aren’t going to talk about it.”

The obvious constraint is time. There just isn’t enough time to test everything.

“The issues we keep confronting or not confronting in the IT industry are ignoring or omitting key steps of the Software Development Lifecycle (SDLC) and then mismanaging how that resulting software is deployed,” said CompTIA’s Stanger. “One of the primary reasons why software issues get missed by the good guys and exploited by the bad guys is because companies, individuals and groups that develop software tend to rush software to market.”

There are also challenges with the way software is configured and deployed.

“Many IT pros and even security pros still tend to think, ‘If I obtain the code from a secure source and run the hash tag, I’ll be fine. I’ll just update the code as necessary.’ Plus, relatively few companies actually test the software properly in a production environment by “throwing rocks” at the code and doing proper threat hunting,” said CompTIA’s Stanger. “Fewer still are able to update software adequately, because updates often break custom code. Imagine how security issues can propagate when you combine installed and cloud solutions.”

While developers should verify that the third-party software they use has been adequately tested by whomever built it, they need to retest it in the context of their own product.

Rob Rosenzweig, Risk Strategies Co.

Rob Rosenzweig, Risk Strategies Co.

“The reality of the current world we live in is that any business must undertake extreme caution and implement a thorough due diligence process when vetting any vendor that impacts their supply chain or is processing or storing any information on its behalf,” said Rob Rosenzweig, vice president and national cyber practice leader for insurance brokerage Risk Strategies Company. “While there is significant upside to the utilization of outsourced vendors in managing expense, obtaining a higher level of security and realizing operational efficiencies; the flipside is that organizations lose control and still retain all of the risk.”

Lesson Learned

The Equifax breach underscores the need for vigilance because hackers are constantly experimenting to find and exploit vulnerabilities, particularly when sensitive information is involved. When a vulnerability is found, it needs to be addressed in a timely fashion, unlike the Equifax breach. Due to the confluence of events, the Federal Trade Commission (FTC) is now investigating Equifax.

As is evident, the failure to implement one patch can have devastating consequences.

You’re Doing Analytics Wrong. Here’s Why.

December 1, 2017 /

Businesses across industries want to compete on insights, and yet many of them aren’t getting the ROI they expect. Somewhere between raw data and actionable insights, processes break down or they don’t exist. It’s not just a tool problem. Organizations need to change the way they think and behave.

Data is data

Every company has data, but not all organizations treat data as a valuable corporate asset.  If they did, they probably wouldn’t have multiple copies of customer records, none of which is “the golden record.”

“There’s no documentation so there’s no traceability,” said Ivan Chen, director of Enterprise Business Analytics at GPU manufacturer NVIDIA. “If you really want to get value out of your data, you have to put structure around it. We realized that, so we’re putting plans in place to provide a foundation for analytics.”

Chen is wrapping up the first month of a three-month pilot that will enable self-service analytics.  As a first step, his team is inventorying all of NVIDIA’s data assets, documenting them and putting them in a central repository.

“We’re codifying all the business logic in the repository so that people can see how the transformation that was done,” said Chen. “That way, there’s a baseline for discussion.”

In the next phase, analysts will get access to self-service analytics.

“The fundamental reason analytics is not successful is because different functions have different goals,” said Chen. “Business professionals are trying to answer questions about the market, but the market conditions keep changing so you have to keep enhancing the data in reports. IT is supposed to make those changes, but IT has other priorities, so the whole thing breaks down.”

NVIDIA dedicated three IT professionals to the pilot who are supporting Chen and his team. Before the pilot began, it took IT six months enhance the data in a report. Now it takes two or three days.

Analytics and outcomes aren’t aligned

When analytics and business outcomes aren’t linked, it’s impossible to understand the ROI. All too often, people believe analytics is the outcome, rather than a means to an outcome.

“Analytics are viewed as how many tools or dashboards you have, or how many reports you generate, ” said Isher Kaila, CEO of management consulting firm Sapphire Nine Consulting.  “No one is anchoring that to the amount of insights you are delivering, and by extension, what those insights translate to in terms of business outcomes.”

Visualizing data in different ways can help clarify what the data says. However, it’s also possible to visualize data over and over without producing any insights.

“You have to understand which insights are necessary for you to deliver an outcome, which people are attached to generating those insights, and who you will hold accountable for optimizing the insights linked to your outcomes,” said Kaila. “Most organizations do a pretty good job of managing their reporting tool environment, but someone needs to be accountable for transforming insights into outcomes.”

You’re stuck in the past

More companies are using predictive analytics to accomplish something proactively, although a lot of companies are still doing business through the rear-view mirror.

“If you’re just showing me the same data in a new way, how will that show me what I should be thinking about going forward? Is it challenging me to think about how I can optimize my business model? Are there processes I need to tweak? How much money am I leaving on the table? Are we cannibalizing our own revenue? Those are the kinds of questions you should be able to ask of your data,” said Kaila.

Some organizations have hired a chief analytics officer or a chief data officer to ensure that data can be used as a strategic asset. That person is responsible for bridging the gap between business and IT, orchestrating resources, and driving value from analytics.

“Leaders need to ensure accountability for insights,” said Kaila.  “If you do that, you’ll be able to align the definitions, the processes and ultimately how you operationalize predictive insights.”

[Analytics and advanced use of data in AI and machine learning will once again be featured during Interop ITX in 2018. The Interop team has issued a Call for Speakers. Practitioners and independent experts are invited to submit.]

Analytics work best when they’re executed as repeatable, sustainable processes that transcend any particular role. In many organizations, analytics are executed as a set of discrete functions and tasks, negatively impacting the potential value analytics can provide.

“Executives should be aware that they’re likely not even harnessing the value of their analytics spend today. There’s an analytics value chain in which outcomes are generated by insights, insights are generated by accountable business owners, and the accountable business owners have a strong partnership with their technical partners,” said Kaila. “Too often we see a lack of alignment around metrics and insights.”

Are You Really Ready for Intelligent Automation?

November 28, 2017 /

If you haven’t considered how intelligent automation will impact your industry and company, start now. Automation is going to impact every industry and every business in some way, first as a competitive differentiator and later as a matter of economic necessity.

The average consumer has been interacting with bots online and on the phone for years. However, bots are now reviewing contracts faster than lawyers can and solving scientific problems that have taken scientists decades to solve.

Some vendors already claim that their software can replace salespeople or data scientists, although management and technology consultants tend view automation as “assistive” because humans and machines excel at different things. The manufacturing industry has proven that machines are better at rote, repetitive tasks than humans because they can do the same thing a bazillion times without getting tired or bored, or needing a break. However, machines are also better at pattern recognition than humans, which describes one of the core things researchers, consultants and even journalists do.

Perhaps intelligent automation would be easier to understand if its growth path were linear, meaning that it would replace tasks that don’t require a lot of intelligence or skill first, and then move up over time to tasks that require increasing levels of skill and knowledge.

That isn’t the way things are shaping up, however.

“Outsourcing and offshore manufacturing affected certain categories of jobs and there was job creation in other areas and that played out over a decade,” said Todd Lohr, a principal within  KPMG’s Technology Enabled Transformation practice. “The problem here is this is going to happen faster than other transformation. It’s non-linear, and it’s going to affect all job categories.”

The business view

Lohr thinks automation will become the new corporate responsibility trend, like “green” which has been fashionable for the last three decades.

“The C-suite is enamored with technology. They have Alexa, they’re using Siri, they’re seeing it in their own lives. They’re buying Teslas and seeing self-driving cars are happening,” said Lohr. “This will impact them as leaders. What is their responsibility to their workforce and society?  It’s not just a cost/benefit analysis, so I think there’s going to be another paradigm for them to make those decisions.”

Business leaders need to consider how intelligent automation will impact their business model, goods and services, or they may find themselves disrupted. Similarly, a disruptor who understands the technology but fails to consider cost may find itself disrupted by a company that can deliver the same result at a lower cost.

“We’ve been talking about AI forever and nothing has happened, but people don’t recognize that the last 20 years was the very slow part of [the] exponential growth curve,” said Lohr. “Organizations need to think about how they handle this today because it’s going to happen faster than they think. They have to think about what it means to their organizations and the societies in which they work.”

Technology implementation matters

Intelligent automation, like any other technology, needs to be considered in the context of the existing infrastructure and how well it will scale. As always, what works well for a proof of concept may not scale well enough for a large enterprise implementation.

“You need to think about design in terms of what is going to be done digitally. You also have to think about governance,” said Sanjay Srivastava, chief digital officer at global professional services firm, Genpact. “If 50 employees failed to come to work in a 250-person firm, you’d have policies around that and visual clues. If 50 robots stopped working because of a password change, it might not be immediately obvious.”

Srivastava raises a good point: The policies that apply to people today need to be revisited in light of digital transformation and intelligent automation. Srivastava recommends business leaders and IT consider how the existing architecture and IT infrastructure need to evolve so any automation can align with what a company is trying to achieve and can change as needed.

The operating model also needs to be considered, and that includes the functions being automated, the role of that function in the enterprise and end-to end-processes. Finally, governance will be necessary to avoid or reduce the risks of errant bots and biased AI.

“You have to look at end-to-end processes in terms of integration and visibility,” said Srivastava. “If it’s designed right, it works well.”

Stop and think

Business leaders need to consider how automation will affect their operations, workforce, technology stack and offerings. Importantly, they should ponder what they want to (or would want to) achieve with automation, such as efficiency gains or cost reduction.

Ignoring the situation is unwise given the rapid pace innovation. Some will disrupt. Others will be disrupted.

How to Modernize Business Intelligence for Self-Service

November 23, 2017 /

One thing that drives analytics consultants absolutely batty is clients who believe their data is inherently clean, regardless. That’s on the business side, of course. IT, data science, and data engineers are all too familiar with what it takes to get data in order, but one thing even they may overlook is the usefulness of that data over the long term. Some are throwing everything into a data lake hoping for the best later, which is fine, as long as there’s some structure and governance in place.

GPU manufacturer NVIDIA is addressing that very problem as it attempts to enable self-service analytics. If the analytics are going to be reliable, then data quality and documentation need to be considered. As I write this, there’s a pilot project unfolding, and a big part of the effort is focused on the data itself.

“There’s not enough emphasis on data assets. It’s more like a byproduct of your systems,” said Ivan Chen, director of Enterprise Business Analytics at NVIDIA. “The first we’re doing is taking inventory of all our data assets, documenting them, and then trying to figure out how we can use that data effectively to make decisions and understand what it means.”

As part of the project, Chen and his team are documenting all the steps needed to meet a performance metric, so everyone can agree not only to the KPI but how that it is achieved.

“I want enable analysis, not give you a debatable report because neither of us really understands the nuances of the data,” said Chen. “If we define and document everything, then we can agree about what a data field is and how it’s used. That way, we can have a conversation about what to do with the data instead of debating about what wasn’t considered.”

The scope of the documentation includes memorializing the data transformation so people can understand how it was done now and later.

Modernizing the BI Platform

NVIDIA is in the process of modernizing its BI platform to enable self-service capabilities. Like other companies, NVIDIA has struggled to leverage pockets of data owned by different people, even though the data came from the same source, such as an ERP system.

“What we’re doing now is we’re bringing it all together in a central repository and documenting all that, so analysts can use it in a self-service way,” said Chen. “I’d like to scale our documentation that so more people understand what’s available and how they can use it, because we’ll be able to create more insights.”

The effort is an attempt to overcome what so many organizations have experienced which is business requirements that move and change at an Agile pace, and the Waterfall nature of IT creating reports, which is gathering requirements, building something, and then finding out whether it really meets the needs of the business or not.

“NVIDIA has a very progressive IT shop where they want to partner with and help business,” said Chen. “As part of the three-month trial, we’re testing the Agile method. There’s a dedicated team from IT that’s solely working on this so there is some sustainability.”

Part of working with IT is resolving the Agile-Waterfall disconnects because the point of self-service analytics is to enable faster and more timely insights.

“Analytics really needs to be treated differently than an implementation project,” said Chen. “I think IT has accommodated this because they recognize that Waterfall reporting is not going to work in today’s fast-changing environment. That’s why we’re able to try this new [Agile] method.”

If everything goes well, the project will scale up to the enterprise level eventually, which will enable more and different types of insights than are achievable today.

Achieving a holistic view is very important if you want to answer important cross-functional questions,” said Chen. “There are a lot of connection points that need to be understood and reconciled if you want to get to an accurate, holistic view. Most companies don’t have that yet.”

Insurance Struggles with Lead Gen & Data Analytics

November 22, 2017 /

The International Institute for Analytics (IIA) recently published a report stating that the insurance industry was the least mature of 12 vertical markets it studied. Insurance companies have lots of data, but they’re having trouble making sense of it.

“We have this data, but we can’t make heads or tails of it because we have data integration problems and there’s no data governance,” said Samantha Chow, senior analyst at market research firm Aite Group. “[Insurance carriers] are hiring data analysts and data scientists, but it’s very fragmented. They don’t have the support they need [to improve] their targeting, products, pricing — all of these things they’re trying to do.”

Lead generation is a huge problem. Older agents are retiring and more business is transacted online, which means the approach to lead generation must evolve with the industry. At the present time, lead generation involves a complicated web of data, external partners, and internal systems, all of which need to be orchestrated into compelling offers that are relevant to individual consumers “in the moment.”

Insurance companies also want to improve their ability to act on “triggers” that suggest a prospect’s interest in a particular product. For example, multiple mortgage loan pulls on a credit report indicate that the prospective home buyer will probably need homeowners insurance. To get information they lack, insurance companies use third-party sources such as credit information provider Transunion, data company Lexis/Nexis, and partners who specialize in social media analytics.

Addressing lead generation

Aite Group recently published a report based on interviews with 80 lead generation vendors and more than 30 insurance company and agency lead-generation and marketing executives. Chow said orchestrating information is the biggest problem the insurance industry faces today, which is why some carriers turn to vendors such as data integration platform provider LeadCloud.

Meanwhile, data acquisition costs are rising because insurance companies don’t know how to target prospects younger than the Baby Boomer generation.

“Getting a 30-year-old to understand the value of life insurance is difficult,” said Chow. “Learning how to target them and speak to them adds to the acquisition costs.”

It doesn’t help that the information insurance companies provide to consumers can be more confusing than clarifying. Because consumers have trouble differentiating products, insurance companies such as Geico, Progressive, MetLife, and Allstate spend lots of money on radio, TV, and pay-per-click advertising promoting their brands.

“This WAS a different cybersecurity conference experience, and I really enjoyed all of the interaction and honest discussions.” (2017 Attendee) LEARN MORE

To reduce lead-generation costs, insurance companies need to improve their ability to use data and analytics.

“We’re seeing acquisition costs go down [among auto insurance carriers] but [for the rest] it’s going to be learning who your target market is, having the supporting data, and being able to hone in on that particular consumer. It’s not going to be easy,” said Chow.

Making sense of data still difficult

The insurance industry also has challenges with data access. Data quality is a problem because different systems say different things about the same person or issue.

Further complicating the matter is the number of systems insurance companies have. They have dedicated systems for claims, underwriting, new business, customer service, and policies. Worse, there are often duplicates of systems because one may cover claims from 1990 to 2000, while another covers claims from 2001 and later, for example.

“On average, some of the top tier carriers have over 26 or 27 legacy policy administration systems they’re running on at one time,” said Chow. “If you have a life insurance policy and an auto policy or a dental policy with [a particular carrier], they can’t get data from one policy to the next policy. They can’t merge that together so they can learn more about you.”

Even if insurance companies could unearth “the golden leads,” loyalty may be an issue for some types of insurance. Chow said most people won’t move their life insurance policy from one carrier to another. Yet, most consumers shop for auto insurance based on price. When it comes to health insurance, customer loyalty depends on the carrier’s willingness to make good on its promises and streamlining the claims process.

Perhaps the insurance industry lags behind in its intelligent use of data because its technology stack and business processes are complex and fragmented. Still, if insurance companies want to remain competitive, they must be able to use data more adeptly to quickly identify quality leads and compete more effectively.

How Customer Intelligence Impacts Customer Loyalty, Wallet Share

November 22, 2017 /

Many of today’s companies talk about getting a 360-degree view of their customers and how that will enable them to increase share of wallet and improve customer loyalty. As a consumer and an industry observer, I would argue that these “360-degree views” are aspirational at best. Striving for a holistic view of customers is a noble goal and a necessary one; however, achieving customer intelligence nirvana is easier said than done.

“The vast majority of the people we talk to aspire to get a 360-degree view of the customer, but the reality is they may not have closed the circle,” said Julio Hernandez, partner, global customer Centre of Excellence Lead and US Customer Advisory Practice Lead at KPMG . “A 360-degree view of the customer is really knowing who the customer is, what they’re doing and why they’re doing it. It’s also bringing in the right information sources, and the information sources are continuously evolving.”

Companies should also understand how valuable their customers are and where they are on their journeys. However, truly understanding customers and marketing to them appropriately is still difficult despite all the technology and data that’s available now.

Part of the problem is what Hernandez calls “The New Year’s Day” problem, which is saying one thing and doing another.

“It goes back to the 360-degree view and having multiple sources of data, combining them, and combining [different] types of analysis to get a better picture of what the customer wants and is doing,” said Hernandez. “You have to start with what you’re trying to achieve with customer insights. That drives how you harness the analytics and how you look at the data. If you expect to just look at all your data and [get] all the insights in the world, you’re going to come up short.”

Increasing Share of Wallet

Businesses purchase a lot of third-party data to better understand their customers’ economic means, what they’re buying and where they’re buying it to understand their share of wallet. If they have a loyalty program, they have insight into what their share of wallet looks like.

“You have to make some inferences about what’s your share in the marketplace is in different categories,” said Hernandez. “You can also triangulate and come up to a number about what I’m actually selling to that person versus the inferred wallet [because] you won’t know for sure exactly what their wallet is.”

Businesses should also consider the attributes of their best customers and then identify customers who share the same attributes but spend less. That way, the company can intervene with some sort of marketing campaign that encourages the latter group to spend more.

Improving Customer Loyalty

Businesses with loyalty programs get varied results depending on the benefits their programs provide and the degree to which companies leverage that information.

“Loyalty cards are interesting because they’re trying to [get] you to clearly state who you are when you’re using the card and then they can track your basket and your purchases,” said Hernandez. “But you have to step back and ask how do you as an organization define loyalty? Is it someone who stays with you on an ongoing basis? If so, that’s great, but if you’re a utility and I continue to business with [you], that doesn’t necessarily means that I’m loyal. It means I’m lazy or I don’t have substitutes.”

Money isn’t everything. If two customers spend the same amount of money, but one is a brand advocate on social media, the latter is considered more valuable now.

“When you think about loyalty, it’s also about what are they’re doing with their loyalty,” said Hernandez. “Are they engaging with your services? Are they proponents of it? Those are things that help you determine what kind of loyalty you have.”

5 Things to Know About IT Candidates

November 2, 2017 /

Hiring and retaining IT talent is difficult. Part of the problem is that some companies don’t understand what IT professionals want and why they want it.

Manpower Solutions Group recently published a survey-based report that sheds some light on the matter. More than 14,000 currently-employed individuals between the ages of 18 and 65 participated, across industries. Some of the results are specific to IT professionals and they may surprise you.

#1: Expect turnover

IT professionals who change jobs frequently do it for two reasons: to increase their compensation (43%) and to advance their careers (60%). Employers should appeal to those desires.

“Candidates within the IT space shouldn’t be measured solely on their time spent within a specific role,” said Stephen Rees, Director of Program Delivery at Manpower Group Solutions, in an interview. “A review of a project’s purpose, the candidate’s role and [her] accomplishments within the timeframe of the project should be the key areas of focus. Seasoned recruiters and hiring managers will need to account for the time needed to ramp up performance in order to understand the value of work delivered.”

Technology is constantly changing which impacts what IT does and what IT professionals must know. Those who learn the newest must-have skills, whether it’s DevOps or virtualized IT infrastructures, tend to be in high demand. When skills are in high demand and there’s a “skills shortage,” companies will pay handsomely for the right talent.

IT professionals have to acquire those new skills somewhere, however. If they can’t learn those skills at their present companies or their present company doesn’t invest education or training, they may seek opportunities at a company that provides such benefits.

#2:  Monetary compensation isn’t everything

IT professionals weigh several factors before making a decision. The top three of seven options are compensation (23%) opportunity for advancement (22%) and benefits (21%). Schedule flexibility, type of work, geography and the company’s brand reputation rank lower. Of those, schedule flexibility ranks the highest.

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Interestingly, opportunity for advancement is almost twice as important to IT professionals than individuals who work in financial services, healthcare/pharmaceuticals and retail. Benefits are more important to IT individuals than others too and not just traditional benefits, such as a 401K program or health and dental insurance. They tend to value non-traditional benefits such as game areas, rest areas and perhaps a healthy drink on tap. Although benefits hold some value in themselves, more importantly, they tend reflect a company’s culture.

“Today’s benefits are becoming more lifestyle/non-work specific,” said Rees. “The emphasis is shifting from the immediate short-term benefits that tie employees to the office and are instead focusing on the broader impact on an individual’s life such as PTO, sabbaticals, learning and development, diversity and inclusion, etc. While the specific role, project or product is still important, the company the work is being done for is increasing in importance as candidates increasingly want to align themselves with an organization that shares their values.”

#3: Your digital presence and industry associations matter

Most survey respondents, including IT professionals, use company websites and search engines to research career opportunities. However, IT professionals are more likely to rely on social media (55%) and industry associations (33%) than the U.S. average of 38% and 18%, respectively.

In the IT world, associations are where standards are defined. Defining standards involves a lot of intellectual banter and collaboration among individuals who work at competing companies. The comradery can result in very compelling career opportunities that don’t appear on a job site or a company’s website.

Manpower notes that some of these IT associations have emerged around certification, training programs and hacking events. Within those groups knowledge exchange and mentoring happen.

“Networking has always been a core component of the IT space. For IT professionals, their work is typically their passion,” said Rees. “This participation is also seen as a way of giving back and helping others develop – there is a true desire to share experiences and knowledge, helping others to learn instead of keeping information to themselves.”

Companies can create their own hubs for interaction, whether that’s offering training or certification at an event or hosting informational sessions that enable IT professionals to meet with some of the company’s engineers.

#4:  They want you to reach out to them

More than half (55%) of IT professionals said they prefer weekly emails from potential employers of interest, which is considerably more than retail (37%), financial services (37%) and healthcare/pharmaceuticals (33%). Manpower equates this finding with the fact that 65% of IT professionals are always looking for the next job opportunity.

If you’re going to reach out to IT professionals and you’re truly interested in maintaining a dialog, don’t send out a general email blast. Instead, engage in a meaningful conversation.

#5: They’re more willing to relocate than others

IT professionals are more likely to relocate to a new city (38%) or a new state (40%) than the U.S. average of 30% and 29%, respectively, but less willing to move to a different country (8%) than the U.S. average (10%). Manpower attributes the greater degree of mobility to the lure of California locations.

While Skype interviews are common, be ready and willing to reimburse top candidates for their travel to and from an on-site interview. It demonstrates a willingness to invest in your employees.

Conclusion

Companies should avoid cookie-cutter approaches to IT recruitment because they tend to overlook some of the important things andidates value. What they value changes with time.

Manpower’s report can provide more insight into what IT professionals really want. It also includes some great advice. Happy reading.

Hotels Check In with More Analytics

October 28, 2017 /

Hotels continue to invest in analytics so they’re in a better position to optimize revenue, deliver better customer experiences and improve operations. Like other organizations, hotels realize they can improve their competitive position using data and analytics more effectively than others. To do that, they need to integrate data coming from different functional areas and connect internal data with external data to make material improvements across the board.

Revenue Optimization

Hotels are moving past historical data and current bookings to maximize room occupancy and profitability. To improve their effectiveness, they’re using competitive data, weather data, event data, predictive capabilities, and more. Starwood Resorts is experimenting with machine learning and neural networks to change pricing dynamically, rather than twice or three times per day or seasonally.

The goal is to optimize the profitability of each room, not just hotels at large

Customer Loyalty

Customer loyalty programs have evolved with data analytics capabilities to provide guests with better, albeit different, experiences. For example, some guests care more about the quality of concierge services than Wi-Fi. Hotels must understand such differences to understand a guest’s preferences and cater to those preferences. After all, every customer has an individual expectation of what a “good” hotel experience is, not just the Premier or Platinum members. While the most profitable and loyal customers deserve exclusive benefits, catering to them should not be done at the expense of other guests.

To provide better experiences at all levels, hotels are attempting to understand their customers more holistically than they have in the past to provide a relevant experience. Having a “special requests” textbox in a booking application yields some information, so are customer requests and feedback recorded at the front desk. Another way to understand customer preferences is to slice and dice room offerings based on non-traditional amenities, such as allergen-filtering, in addition to the usual size, price, category and smoking/no smoking designations. Tracking a customer’s preferences over time, helps too in an effort to anticipate guests needs and desires.

These days, loyalty isn’t something that kicks in at check-in. Hotels are using search, online bookings, social media, call center data, front desk data and surveys to better understand customer journeys and what people want.

Moving up a level or two, some are targeting Millennials, which included Pokemons in the pool and on beds at Marriott hotels, clearly a non-traditional “benefit,” though an attractive benefit for those caught up in the Pokemon Go craze. The campaign happened to be a very smart marketing move from a social media point of view — free advertising.

The relationship among marketing, customer loyalty and revenue optimization enables a continuous feedback loop where insights from one bucket inform the others. And that’s not all.

Operations

Third party data can be very valuable from a predictive point of view when it impacts hotel occupancy and profitability. Weather and event data are two examples. Here in Sedona, Ariz., wildfires and heavy monsoon rains can cause massive hotel room cancellations. In other cities, popular concerts, sports games and flight cancellations cause a spike in demand. While those things may seem intuitive, actual data feeds can help hotels plan for the dips and spikes more accurately, so they can right size things like staff on hand and supply orders.

From an internal perspective, hotels need to monitor and constantly improve the efficiency of individual functions such as housekeeping, not only to reduce costs, but to keep up with competitors’ improvements. Some operational information is used to craft marketing messages such as Starwood Hotel’s “Smart check-in.”

Analytics is also providing insight into age-old issues such as sluggish room service. Is the problem too many simultaneous orders, too few members of the kitchen staff, poor kitchen management, something else or a combination of things? Operational analytics provides some insight as will guests’ social media posts, survey data, call center data, front desk data, etc.

Mobile

Hotel chains have mobile apps that give them even more insight into customer behavior, especially as they expand out from reservations made using a mobile device to keyless entry (using a smartphone), mobile food orders and more.

Some hotels are adopting “mobile first” strategies given the popularity of the devices and the fact that more hotel customers are using mobile devices instead of laptops to book rooms.

Hotels face many of the same problems enterprises face generally, not the least of which is connecting dots in a way that is valuable to their organizations and customers.

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