Tag Archives: silos

The Silos Are Coming Down

While I’ve heard many too many empty promises of corporate synergies over the years, I’ve learned that one form of cross-selling really does work: “Do you want fries with that?”

So, I’ve been waiting (and hoping) for insurers to find ways to achieve similar sorts of easy, intuitive crossover sales.

There are already a few combo meal sorts of offerings that show promise — e.g., Tesla bundling auto insurance with its cars, or Comcast selling insurance into homes that are tethered to it via coaxial cable — but my ears really perked up last week when stories surfaced about Walmart forming an insurance agency.

It just makes sense. With 5,000 outlets in the U.S. alone and 265 million customers worldwide, Walmart has a target-rich environment for insurance sales. Many, in fact, are visiting Walmart to pick up pharmaceuticals or to buy other items related to their healthcare, so health insurance is on their minds. Walmart, given its relentless efficiency, could easily develop insurance products that undercut competitors’ prices and would have the credibility with customers to sell boatloads of those products.

In fact, Walmart wouldn’t even have to generate the sorts of profit margins that competitors do, because a tighter relationship with customers on their health needs would bring them into stores more often and let Walmart generate profits on groceries, home goods and all sorts of other products. (Regulators will surely weigh in on what constitutes fair competition.)

Walmart signaled that it will begin with a niche, Medicare Advantage, that plays to its price-sensitive demographic. In fact, through a $4 generic drug program, Walmart often provides pharmaceuticals to customers for less than their Medicare Advantage insurance would charge them, so Walmart has already made inroads.

In research I’ve done with Chunka Mui on major strategic mistakes, the kind of adjacency move that Walmart is making raises red flags, because retailing and health insurance have little in common. But Walmart has done all the right preparation, having spent more than 15 years testing the waters in health care and insurance — hosting insurance agents onsite, setting up joint ventures with insurers, putting clinics in some stores, buying and deploying technology to help customers manage medications, experimenting with telemedicine and much more.

Walmart is also starting small with its agency, advertising for employees and building an internal capability, rather than spending a bunch of money on a splashy acquisition or two. (Sears made that mistake in the early 1980s when it bought Coldwell Banker and Dean Witter, only to be distracted by integration issues and take its eye off the ball in its core business, which it ceded to… Walmart.) So, I see no particular obstacles for Walmart.

In fact, health insurance is such a mess that many customers would love an outsider’s approach, especially if the outsider is, like Walmart, known for being straightforward and inexpensive.

Given the battle to the death between Walmart and Amazon, it’s reasonable to think that Amazon might now accelerate whatever plans it has for health insurance. It might behoove insurers to get ready, and even to go on the offensive, looking for partners outside the industry rather than waiting for them to define an opportunity in insurance.

Insurers won’t be pushing fries and, alas, can’t offer dollar meals or dollar anythings, but there are lots of healthy options that can be offered and sold easily if insurers get creative about how to bundle their products with partners’.

Stay safe.


P.S. Here are the six articles I’d like to highlight from the past week:

6 Life, Health Trends in the Pandemic

Life and health carriers are responding with new protection products and services.

Reigniting Growth in U.S. Life Insurance

Agile response to COVID-19 bodes well for returning the life insurance sector to long-term growth and wider financial protection in society.

COVID-19 Highlights Gaps, Opportunities

The pandemic and the response to it have highlighted significant gaps in industry offerings that are yet to be resolved.

Another Reason for Insurers to Embrace AI

AI alerts have played and continue to play a critical role in detecting and controlling future outbreaks like COVID-19.

Wildfire Season Off to Perilous Start

Fires can create their own weather: Smoke-infused thunderstorms produce lightning that starts new fires and can lead to fire tornadoes.

Lasting Impact of Plaid’s Innovation

The temptation to try to own all the value at every layer of a solution can be fatal, and is something Plaid brilliantly avoided.

Time to Reinvent Your Products

In my previous article, I stressed that a new commercial insurance model is about breaking down existing operations and rebuilding a collaborative and innovative model. The rebuilt model would improve operational efficiencies, control costs, create innovative products, improve customer engagement experiences and produce sustained profitability. But, if you think operational silos are challenging, I suggest you suit up and put on your protective gear because I’m about to tackle the cold reality of commercial insurance product silos!

Should the market simplify risk management solutions? Duh!!!

The role of a corporate risk manager is to protect the employees, clients and balance sheet of his or her company. The manager looks to the commercial insurance markets for risk management solutions but, instead, receives product responses that create a patchwork of protection.

When the markets can only provide products in lieu of risk management solutions, a variety of customers’ risk exposures are left uninsured — they must now consider self-insuring or creating alternative financing vehicles, including captives. Creating risk management products and simplifying risk management solutions for corporate customers should be the goal of any commercial insurance broker or company.

See also: Leveraging AI in Commercial Insurance

If companies eliminated product and service silos to create a collaborative risk solutions environment, big data collection and analysis could be implemented across all existing products and customers’ uninsured exposures. This collaborative environment would also minimize current big data challenges, including:

  • Unstructured data identification
  • Weak processes to capture and manage data
  • Poor data quality and accuracy
  • Unused data

By eliminating product silos, I’m not suggesting that you eliminate your product experts. On the contrary, each product expert has a vital role to play in challenging and supporting how new and existing products will function.

The removal of internal product silos broadens products expertise and knowledge, thus enabling product experts to further comprehend the risks that corporate customers manage every day.

You already have the clients – start implementing the tools to create risk management solutions!

Currently, commercial insurance brokers and companies are better placed to respond to insurtech competition as, unlike most insurtech startups, they have a large pool of existing customers and the ability to access or create extensive risk management data. When combined with additional imported data such as ISO, ERC and AAIS, an integrated dynamic financial model (IDFM) can be easily created to capture industry, claims, exposure and risk management patterns.

Capturing and codifying risk management data is absolutely crucial, as it elevates existing industry claims and exposure models. In addition to creating new risk management products, the IDFM data outcomes can also create a variety of new risk management services, thus creating additional revenues.

I’m not a data scientist, but I have always been fascinated with risk identification. Many years ago (more than I care to remember!!!), I created an IDFM model with the crudest of tools. The model outcomes enabled me to create risk management products and services that customers want to buy and eliminated the “one-size-fits-all” product response embedded in the commercial insurance market.

Now, by incorporating new technologies such as AI, machine learning, bots and smart sensors to improve risk management analysis, this model becomes even more dynamic! These technological additions to the IDFM model, along with the use of blockchain, enhance the model’s ability to:

  • Gather and store even more data elements;
  • Improve decisions based on that data; and
  • Provide relevant answers to improve the company’s abilities to create risk management products.

Additionally, the IDFM model enables the creation of revenue streams such as usage-based and peer-to-peer commercial insurance. These opportunities will be further examined in future articles.

All geographic regions are not the same! Expand your mind and create something new!

The ability to capture and codify the elements noted in the IDFM model, including the client risk management review, is particularly important for global commercial insurance companies and brokers expanding into Africa, Asia and Latin America.

See also: Innovation Challenge for Commercial Lines  

Risk managers in these regions continue to express their frustration with market responses as local agents, brokers and insurance companies are not expanding their product portfolios. Global companies are extremely slow in creating products that are specific for the risk management needs of these diverse local markets – instead, companies aggressively sell Europe-centric or North American-centric policies while supporting low margins. These diverse local markets would benefit from improved innovation and increased investment in technology and will be explored further in future articles.

And finally ….

Commercial insurance brokers and companies must stop viewing insurance through the prism of products and, instead, recognize its true potential as a service. Remember, it is all about the customer! Or, simply put, no customers, no business.

Cutting renewal prices and watching margins decline every year is not a sustainable business plan for incumbents or insurtech companies. Instead, the commercial insurance market must break down and rebuild product and operational silos to create a collaborative and innovative model to improve their abilities to package complex risk management products and services. Products and services can be presented in a simpler/intuitive manner, with plain language and processes that clearly manage customer expectations and increase customer satisfaction. Breaking down existing products and operations and rebuilding a collaborative and innovative model will also improve operational efficiency, control costs, increase revenue streams and produce sustained profitability. Let’s break down these barriers!

Innovation Challenge for Commercial Lines

Let’s be realistic. Managing customer requirements is expensive and exhausting with current structures for commercial insurance operations! While insurtech is currently seen as incorporating technology into an organization to produce new products or touch customers in new ways, it also must mean breaking down existing operational silos and building new, streamlined structures.

Any reengineering should incorporate strategic innovation and technology to ensure that all parties have aligned objectives to rapidly respond to new opportunities and exit unprofitable ones while improving operational efficiency and controlling costs.

Operational Silos – Release the wrecking balls!!!

Commercial insurance companies consist of various operational silos. Unfortunately, over the years, these silos have subsumed the key functions of underwriting and claims and, in effect, are controlling the overall strategy and direction of a company’s risk appetite without substantive feedback from underwriting and claims – the teams that actually interact with customers! There are numerous reasons why these operational silos have been implemented, but a key reason is the inclination to avoid risk.

Yes, there is a touch of irony here, as the industry is supposed to be in the business of assuming risk — but these companies are protecting their balance sheets while attempting to manage increased regulatory requirements. If you are an underwriter or claims manager, climbing over the ice walls in the Game of Thrones must appear easier than dealing with the daily internal operational challenges.

The primary support that operational silos receive means that underwriting and claims team struggle to receive resources and appropriate technology investments to support existing business, improve service and produce innovative, effective and profitable risk management products in an extremely competitive market.

See also: How Insurtechs Will Affect Agents in 2017  

We are repeatedly informed that insurers spend between 20% and 40% of each dollar/pound/euro of premium on costs of operations and customer acquisition costs, marketing and distribution. I would argue these costs do not factor in costs due to internal frictions — and they are VERY expensive! Prioritizing operational silos means that internal imbalances affect all areas of the organization:

Product deliverables – Whose team are you actually on?

For those who would argue that the structure of commercial insurance companies is not a hindrance to producing business or creating products, I’d like to share a real-life example of how one commercial insurance company saw its market share and resulting profitability significantly reduced due to its own operational silos:

The underwriting teams’ inability to respond quickly to market conditions was driven by a lack of support and priority by the legal and governance departments. The company had no streamlined collaborative protocols between departments to support new product or policy form development, nor was technology used to manage the product development process.

Company A’s internal operational silos restricted a path for innovation, reduced long-term value and allowed competitors to reduce Company A’s market share. The company’s poor execution also evidenced the inability to respond quickly to market changes — brokers and competitors began to challenge Company A’s market leadership abilities.

Compliance operations – The growing beast

The disconnect between regulators and commercial insurance compliance is a pet peeve of mine — instead of investing in systems that improve compliance by streamlining internal processes, risk identification and risk management, companies have greatly expanded compliance staff numbers over the years and added another silo of operations. This operational expansion slows customer support, increases costs and still contains high levels of inefficiency. Of course I’m aware that compliance is critical, but there are easier and more cost-effective ways to achieve compliance goals and improve regulatory reporting.

My team at Artemis Specialty conducted a London market broker survey in 2015 to identify how quickly the market develops products and the quality of service — the results were depressing. Brokers expressed a growing concern that underwriters were spending as much as 40% of their time on internal and regulatory functions in lieu of servicing business.

Further discussions indicated that many commercial insurance companies have inadequate technology in place to support their business. Effective technology will provide underwriting and claims personnel with the required tools to meet corporate underwriting, claims and regulatory guidelines and reduce the number of compliance employees (no, I’m not anti-compliance employee). Additionally, underwriting and claims teams can focus 100% of their time on new and existing customers — the key reason they are employed!

Innovation labs – Another operational silo?

A number of commercial insurance entities have created innovation labs, which, at first glance, is an admirable step to introduce disruption — but it does raise a number of questions:

  1. Will the lab be viewed and managed internally as an additional operational silo?
  2. If the innovation lab is separate from existing operations, how will it challenge the status quo?
  3. Where is the buy-in at all levels of the company? How do you create excitement across the entire organization to participate in innovation experiments?
  4. Can the lab be described as innovation if it is only created to digitize existing legacy products?

Internal disruption is difficult, but M&A is easier? Seriously?

Over the past 15 years, it has become glaringly obvious that it is time to develop a new business model for our customers — they deserve it! So, why is internal disruption difficult?

During the last 10 to 20 years, there have been numerous commercial insurance mergers and acquisitions. Companies instill a new corporate identity in to the acquisitions and new employees while integrating legacy systems. If a company is capable of a merger and acquisition, why is it not capable of implementing and managing its own internal disruption to create innovative, efficient and customer-focused environments?

I have restructured numerous departments over the years to refresh the innovation culture, create products, improve efficiencies and increase customer service and satisfaction — surely this can be replicated throughout an organization and at the corporate level? How many operational meetings have I attended over the years to push for improved internal collaboration, efficiencies and the transformation of the broking, underwriting or claims operations and processes? Why is the response almost always: “It’s too difficult.”

See also: 10 Predictions for Insurtech in 2017  

Many analysts cheer when companies are acquired or merged, as there is now “scale” and a reduction of costs through layoffs and other efficiencies. I have attended numerous analysts’ calls throughout my career and noted they rarely question M&A technology efficiencies in depth; in fact, it’s rare when technology questions are raised during annual or quarterly financial investor and analyst updates. Will analysts and investors now raise more technology questions due to the increased insurtech enthusiasm and press? I would be a bit more curious about how a company is meeting new technological challenges and its impact on future company profitability.

Existing commercial insurance strategies of top-line growth or releasing underwriting reserves are not sustainable — nor is it a sustainable strategy to create mass layoffs when the former strategies no longer work.

A new commercial insurance model is not about implementing a digital front end to create a smoke-and-mirrors modernization image to support existing products — nor is it simply about partnering with or acquiring an insurtech company. It’s about breaking down existing operations and rebuilding a collaborative and innovative model to improve operational efficiency, control costs, create innovative products, improve customer engagement experiences and produce sustained profitability. Let’s break down these barriers!

4 Steps to Ease Data Migration

Mobile has been a huge change agent for technology across all industries, and insurance is no different. The demands of today’s customer have dictated that legacy systems with siloed data be re-examined and replaced with modern, digital-ready solutions. With 64% of insurance employees willing to use a mobile app or site to improve access to sales information in the field, data must be accessible across all channels of an organization.

Migrating data from siloed, disconnected systems to a new cutting-edge platform is no easy task. A successful data migration requires extensive preparation, custom software architecture and knowledge of both old and new systems. Before moving to new business software systems, developing a plan to streamline the transition and to prevent major hiccups is imperative.

Get Rid of Unnecessary Data

The longer that insurance providers have been in business, the more data there is to deal with. Additionally, legacy data that is no longer necessary for current business operations accumulates for a variety of reasons. Before moving to a new house, most owners take the opportunity to clean the attic and get rid of items that have accumulated and are no longer needed; the same idea applies when migrating data from a legacy system to a new solution. When preparing to migrate, insurance providers should take a close look at data in legacy systems and only migrate data that is necessary for today’s business operations.

See also: Why Exactly Does Big Data Matter?  

Rethink How to Map Data to New Systems

Demand for real-time data access and frictionless user experiences has led many digital-ready software solutions down different paths than those taken by legacy systems. Both the underlying technology that stores the data and how the data is structured relationally is very different from what was seen decades ago when insurance providers were developing their first software systems. Insurers need to account for these changes while helping data make the transition to restructure it to best suit today’s needs. Because this process is time-consuming and complex, many providers benefit from third-party digital transformation partners whose expertise can be leveraged to provide a best-of-breed solution.

Use Out-of-the-Box Best Practices

Legacy systems have been unable to adapt to business processes that have evolved dramatically in recent years, meaning many insurance providers have been forced to rely on outdated practices. When rolling over to a new system, starting with the best practices contained in the new software and modifying only when necessary is a key best practice. The software vendor has evolved its out-of-the-box processes over the years, and they should be considered best-of-breed. As a rule of thumb, an insurance provider should only modify these processes because of some unique part of the business that is key to its strategic goals. Migrating old processes or modifying recommended ones can be inefficient and costly, so providers shouldn’t throw away time-tested solutions unless there’s a critical strategic reason to do so.

Plan Ahead for a Smooth Rollout

Making the transition to modern software solutions can easily derail day-to-day operations if providers don’t take the right precautions. To make sure the rollout is seamless, providers must develop a strategy to “keep the lights on” that often involves mixed-mode operations between the legacy systems and the new digital solutions. This strategy involves a great deal of up-front architectural planning to ensure the data is in sync between the old and new systems, along with a road map that sunsets the legacy solution piece-by-piece in a surgical fashion. A smooth rollout also requires training on buy-in and training on how to use the new technology, which, along with an extensive beta testing phase to gather feedback, are wise investments to the overall long-term success of the rollout.

See also: 3 Types of Data for Personalization  

Migration of mission-critical legacy business systems to modern digital-ready solutions is not easy. Up-front planning for data migration, training, business rules, process, architectural evolution and both short-term and near-term business goals are all key considerations that should factor into the overall migration road map. Rushing a digital transformation effort can result in incredibly costly mistakes down the line, so insurance providers need proper planning to ensure a smooth transition. Providers should strongly consider enlisting the help of a partner that is skilled in digital transformation to help guide them along the journey.

How Technology Breaks Down Silos


New digital technologies and the data they are producing have forced collaboration among senior business leaders across all levels of all organizations. To obtain insights from data to drive decision-making and embed a data-driven approach within a company’s culture, it is critical for the C-suite to lead the way.

It’s easy to talk about collaboration, but much harder to act. Analyzing information, deriving insights and responding with effective strategies requires an understanding of the analytical tools themselves, as well as collaboration. As technologies get smarter and various functional groups collaborate, simply moving to single systems can give broader teams greater visibility to inefficiencies and broken processes.

But how does a business get to such a place? What tools and strategies bring about successful coordination of activities in such dynamic situations? And what are the challenges of working together that C-Suite executives should anticipate?

In Depth

Just about every functional group within an organization can now collect, connect and analyze data. But big data – from keyword searches, social sites, wearables, mobile devices, customer feedback and so on – presents challenges as well as opportunities for business leaders. One of the biggest is how to maximize the potential of this data by transcending organizational silos to unlock its true potential.

Technology is also transforming how businesses develop and deliver goods and services and is placing enormous new demands on those responsible for strategies to navigate the challenges. These are the people who need to apply institutional knowledge, implement changes and allocate resources toward new ways of working on a day-to-day basis.

Paul Mang, Global CEO of Analytics and leader of the Aon Center for Innovation and Analytics in Singapore, says there are two types of data analysis that can be leveraged to accomplish this: business analytics and enterprise analytics. Business analytics focus on the use of established tools and capabilities, while enterprise analytics “create new product or value propositions for existing clients or new client segments altogether.”  Short-term, enterprise analytics can lead to disruptive innovation while quickly contributing to improved long-term performance.

“Business and enterprise analytics should work side-by-side and complement each other” to support decision making, Mang says.

The Changing Role of the CIO

The need to become an effective data-driven organization has dramatically increased the importance of the chief information officer (CIO), a role that John Bruno, chief information officer at Aon, says is that of “an integrator – someone who works across the entire organization to embed data within the business.”  He sees the value that information technology (IT) brings, and notes that “IT is less about bits and bytes of data, but more about bringing them together to extract specific insights.”

The need to centralize and mine big data for market opportunities and to parse out weaknesses is also prompting some firms to create a C-suite level position of chief data officer (CDO). This role would be responsible for working with business managers to identify both internal and external data sets that they may not even realize exist, as well as continually looking for new ways to experiment and apply that data.

Equally critical to communicating changes in customer preferences and behaviors, and for their ability to leverage insights from customer purchase patterns into developing new products and services, is the chief marketing officer (CMO). Like the CMO, the effective CIO needs an intimate understanding of how current technology can increase the company’s sales.

However, Bruno says, “in any large organization, there are multiple leaders in different parts of the organization who address different elements of the same challenges. It’s the CEO who can see the whole view and works to have teams bring forward integrated solutions to distributed problems.” He sees the role of the CEO as one who looks beyond short-term disruptions and organizational adjustments to seize opportunities that ensure long-term growth.

This is why, increasingly, the role of the CIO/CDO is about balancing business needs against an incoming stream of opportunities – and risks. This broad cross-business knowledge can only come from constant and deliberate collaboration with the rest of the C-level executive suite. Above all, the CIO has to be able to effectively show how technology and the subsequent data it brings are assets rather than cost centers. For CIOs to really succeed, this means informing C-level colleagues about technology and the opportunities it can create.

Making Collaboration Count: Finance and HR

The role of the CFO is increasingly about analyzing data to give it meaning and partnering across the organization to make the information actionable. One area that is seeing CFOs use data to drive real results is in collaboration with the chief human resources officer (CHRO).

Eddie Short, Aon Hewitt’s managing director, Global Data & Analytics, says that in most organizations the C-Suite has not been getting sufficient insight into people-related business issues, typically owned by human resources (HR) teams. Today, with the CIO’s help, digital tools are increasingly being used by leading organizations to measure employee performance, reduce attrition and cultivate talent through a better understanding of the data about their workforce that they can gather and analyze.

“People analytics,” as this emerging field is known, attempts to bridge the gap between HR and the rest of the organization by providing specific insights into an organization’s talent. “People analytics is all about connecting the value of your people to the strategic goals and objectives of the business,” Short says. “This approach represents a major opportunity for HR and finance leaders to take a road centered on the greatest asset that organizations have – their people – and start to shape the value-add they will create for the business over the next five to 10 years using predictive analytics.”

With skills shortages an increasingly pressing issue for many organizations around the world, gaining this kind of insight can help a business to identify and meet its future talent needs.

Aligning for Agility

As technology continues to disrupt, CEOs and the C-Suite in general must accept that there may not be a set playbook to follow to adapt and evolve. Flexibility is paramount, and often organizations must invent and reinvent as they move forward. Intelligently applying analytics tools to derive value from big data can help them navigate this new terrain.

“Today, CXOs want predictive insights,” Short says. “They want answers to the predictive ‘what could I do?’ questions as well as prescriptive – ‘what should I do?’ — questions.” Yet most tools and programs currently available are merely descriptive – to derive true insight needs additional interpretations from people who really understand the business.

This is where C-Suite collaboration becomes so vital. Organizations thrive when there are diverse and complementary personnel and systems working together. Sharing insights from the analysis of big data across the C-suite and across functions can position businesses to draw valuable insights from this data, harmonize planning around it, align their actions and understand the full value this brings both to their own divisions and the organization as a whole. And the more that data is shared, the more leading businesses discover that they can find answers to today’s – and tomorrow’s – questions.

With the measurable business benefits this data sharing can bring, the business case for breaking down silos within organizations is stronger than ever. Where this may have once been a C-Suite aspiration, the make-or-break implications of insights drawn from this data has made it a business imperative.

Talking Points

“In every industry, our analysis and our work with clients would suggest technology at a minimum is going to be a tremendous accelerant. So if you have a a business model, the opportunity to scale it more effectively, grow it more effectively gets… amplified.” – Greg Case, CEO, Aon

“The way that big data pervades most organizations today creates a dynamic environment for C-level executives to explore how it can and should be used strategically to add business value.” –  Economist Intelligence Unit

Further Reading