Tag Archives: organization

A Word With Shefi: Micro Insurance

This is part of a series of interviews by Shefi Ben Hutta with insurance practitioners who bring an interesting perspective to their work and to the industry as a whole. Here, she speaks with David Dror at Micro Insurance Academy.

To see more of the “A Word With Shefi” series, visit her thought leader profile. To subscribe to her free newsletter, Insurance Entertainment, click here.

Describe what you do in 50 words or less:

I lead a team that brings the poor in rural informal contexts into the fold of insurance. We address this challenge by acting as change agents. We do not sell a product; instead, we take communities from having no risk-management solution to adopting a mutual-aid insurance model that enables them to establish both the demand for and supply of insurance, specific to their context.

And when you are not working, what do you like to do?

I like to read, write, walk, socialize and rest.

How did you become engaged in microinsurance?

I have been involved with social insurance since the 1970s, mostly at the macro level; in India, I work with grassroots communities. My experience in India teaches me one overriding lesson, that top-down interventions, without full funding, offer very little opportunity to affect social change, and “localism” that taps into invisible resources offers some unexplored opportunities to reach results.

What is the main challenge the Micro Insurance Academy sets out to address?

The social challenge we address is the uninsured exposure to risks that condemns the poor in the “informal sector” to poverty, ill health and uncertainty. Insurance is broadly recognized as an indispensable tool to improve access to healthcare, agricultural production (thus food security and livelihoods) and to mitigate climate-change-related crises. However, the challenge to roll out solutions in the informal sector has proved difficult largely because the multifaceted aspects of poverty are often anchored in families and extended families, and not the individual as in the formal sector. Dealing with those social units requires innovation in business models and social engagements. This is what MIA focuses on.

In a recent paper termed The Demand for (Micro) Health Insurance in the Informal Sector, you write about the importance of group consensus in driving individuals’ buy-in to microinsurance. Do you see insurers account for this lifestyle in their selling proposition?

Our solution, which is to assist the community to establish its own insurance schemes that leverage existing relationships of trust and obligation, is based on developing associations for the purpose of efficient sharing that enable the community to be consumers, creators, collaborators, suppliers and distributors of insurance. This is P2P “sharing economy.” Success means that each member becomes both co-owner and customer, with a role in business decisions of the supply chain, organization and development. Traditional selling is simply not effective in this setting, and mobilizing entire communities, not merely community leaders, is the novel paradigm.

What does success look like five years from now for Micro Insurance Academy?

Many insurers work with us to adopt risk-management solutions to be demand-driven and needs-based. Success in business results would mean outreach to millions of uninsured people, and success in business process adaptation would mean that we mobilize resource pools from resources that are today invisible and inaccessible.

Is the talent gap within insurance an issue in India as it is in North America?

Our model relies on a three-pronged approach (capacity building, governance and insurance), each of which leverages local function, purpose and culture. Developing capacity is a challenge mainly because such capacity must be available at the community level, not just in a few remote back offices. Better local capacity is the backbone that supports good governance.

Best life lesson:

“The greatness of humanity is not in being human but in being humane” – Mahatma Gandhi.

How to Choose a Great Coach

The Institute of Leadership & Management (ILM) published a report titled “Coaching for Success: The key ingredients for coaching delivery and coach recruitment.” There’s plenty of interesting snippets of research findings and practical advice.

If you have time, it is well worth a read, but the points that caught my eye were a three-stage process for coach selection. I agree with the ILM that the selection of coaches often still lacks a robust structured process and so am going to share their recommended process as a good example.

This process can be used by individuals for themselves or by someone selecting on behalf of an organization. It assumes that a long list of possible coaches has already been found. To achieve that, you could go as Wild West as a general Google search on “coach”/”leadership coach”/”executive coach.” However, I’d recommend starting with a pre-qualified list like the Association for Coaching (AfC) directory of coaches or equivalents from other coaching bodies.

Here are the stages that the ILM recommends, to be used like a checklist of questions to ask (I’ve added what I’d say if asked):

Stage 1: Long-list to Short-list

  • What experience of coaching does the coach have? (I could evidence my number of coaching hours and cite previous mentoring experience within a large corporation)
  • Can the coach demonstrate an understanding of the leadership challenges in your industry? (I’ve found some clients value my experience in customer insight leadership or within the insurance industry)
  • What training do they have? (I could evidence my ILM Level 7 qualification in Executive Coaching and Mentoring)
  • What ethical standards do they work to? (I share with clients a copy of the AfC code of ethics and explain that I abide by that)
  • What supervision does the coach have in place? (I use AfC/University of South Wales co-coaching forums)

Stage 2: Getting down to the last few

  • What coaching methodologies does the coach use, when and why? (my primary tools are active listening, Socratic questioning, goal-oriented models and, where relevant, positive psychology tools like Strength Finders)
  • What price do they charge? (average fees can vary around the country, but between £100-250 per hour is typical; I normally charge £150 per hour)

Stage 3: Final selection

  • What does the coach he can achieve for the individual coachee/client? (this is where a free introductory meeting can help me clarify where I may be able to help or if another intervention other than coaching might help more)
  • What do they believe they can achieve for the organization? (it’s always worth doing your homework on an organization and discussing context with a client, before you can offer a view on this)
  • Will the coach and the coachee/client get on? (at the end of the day, a lot comes down to personal chemistry, so I will meet up for a chat over a coffee and let us both assess if we feel it can work)

I hope you find that helpful, especially if you are facing this challenge. The ILM also suggests that competency frameworks from leading global coaching bodies can help, but I like the clear simplicity of the above list.

Has anyone found another approach to selecting a coach worked for them? Please share your experience.

innovation

Does Your Culture Embrace Innovation?

Why does it matter whether your organization embraces innovation by design? We are at the beginning of an era where the confluence of increasingly powerful computing capability, ease of starting a tech-intensive firm and massive data in a deeply networked world will drive more innovation more broadly than ever before. The rate of change and, indeed, the speed with which new incumbents enter markets and existing players fail will only increase. This means innovation must become part of a company’s fabric and its culture to ensure success.

Looking over the past 20 years to gain a better view of the next 20 years, there are three things that stand out, are surprising and are instructive.

  1. Science, geo-politics, sports, weather, information technology and cyber are all areas full of events that, a year or two before the “event,” prominent insiders would have said were not in the realm of possibility—they were not just unlikely but impossible, if not loony.
  2. While impressive, the huge growth and acceleration we have seen in information technology, social media, mobile, big data, several areas of science and cyber all exhibit patterns of the beginning of something—not a pattern of stability, maturation or, even, peaking. The amount of data, the amount of IP-enabled nodes and the throughput cost of computing could all scale 100 – 500 times in the next decade, making today just the beginning of a hockey-stick-like curve.
  3. The simple truth, threat and opportunity is that the rate of change is increasing across all areas of life while the scale of change is expanding.

What does all that mean? One thing is certain: Being agile is not enough. Those who effectively embrace innovation at an organizational (if not cultural) level will fare better than those who do not. Indeed, if this is the beginning of accelerating rates of change with massive outlier impacts, then driving innovation pragmatically across an organization is imperative.

See Also: Innovation Trends in 2016

If, from the top, the mission for everyone in an organization includes being innovative, this can become part of the fabric, the culture of the organization. Businesses that effectively embrace innovation at a cultural level will fare better than those that do not.

Still, there is a massive amount of fog surrounding the word “culture.” I often hear it is the insurmountable obstacle to innovation at scale and pace.

One Fortune 500 Example: Motorola

In the early 2000s, I was an officer with tech and business responsibilities at Motorola. The culture was largely internally focused, obsessed with continuous (often marginal) improvements, in love with engineering and intellectual property (IP) filings and not necessarily the monetization of IP. It was a family-oriented culture with, literally, generations of the family working at the firm. But the firm was failing.

The board brought in a new CEO from Silicon Valley, and we changed the company culture radically in 18 months. We did six simple things, instigated and championed by the new CEO:

  1. Clearly communicated a broad new mission about being externally focused, fast-paced, innovative and customer-centric
  2. Set out the behaviors that we expected and that the company would reward, as well as behaviors we would punish
  3. Continually “sold” (over-communicated) the rationale of why we were changing
  4. Made sure rewards and punishments were publicly meted out to support the new direction
  5. Matched structure to mission and talent to task; (when the game changes from soccer to rugby, not all team members have a role despite prior excellent performance)
  6. Eliminated active objectors and passive resistors who simulated support but were not rowing the boat (a third of the top 120 executives changed in about 12 months, mostly for this reason)

Motorola changed its culture and performance radically in 18 months. We released the breakthrough RAZR phone, which became the best-selling phone of all time. IT, for example, became a platform for tech breakthroughs and even had a venture arm for emerging tech.

Unfortunately, shortly after that, Apple made a thing called the iPhone, we made some very bad leadership talent decisions and we backed hardware over software in our largest business unit.

No amount of motivation or positive innovation culture will save you from a bad strategy that is married to poor talent decisions in key posts, compounded by groundbreaking, world-class competition.

Cultural obstacles

A well-communicated mission, backed up by clarity on what garners rewards and punishments, is key. The rewards and punishments must be broadly, consistently and continuously meted out for the behaviors that merit them. This will drive the behaviors in the organization. Lots of organizations get the reward part generally right, but they fail miserably on the punishment side, then wonder why they have cultural obstacles.

Done properly, rewards and punishments drive the behaviors inside your organization. The sum of those behaviors is your culture. 

Tips for building an innovation culture

Innovation must be about both big and small innovation, not just breakthroughs. Almost all organizations have an untapped wealth of innovation they can access by just eliminating the longstanding negativity that confront the rank and file daily. The front-line person in accounts payable and customer service or the distribution center in Managua may have process ideas that are innovative and high-impact for the whole organization.

See Also: Tech Innovation Is No Longer Optional

The simple question, “What really dumb stuff do we do around here?” in the right penalty-free environment usually unleashes a torrent. But without a culture of innovation, small, incremental, continuous improvements lie dormant.

Idea platforms and innovation/suggestion processes are all well and fine, but they should live inside an innovation culture where everyone thinks it’s part of their individual mission, with the underpinning or institutional agility and continuous improvement that goes with it. Again, you are not asking each person to reinvent Google, Facebook or the low-cost Fusion; you are rewarding them for innovative improvements.

To keep up with the changing external environment, an organization must be adaptable, agile, great at managing change and effective at the necessary but mundane underlying program management. An organization must also be deeply externally aware and manage emerging potential challenges, opportunities and threat profiles as far in advance as possible. No culture can remain innovative if it is internally focused and not connected purposefully to the outside world.

One simple approach to help instantiate innovation is to use “HLI” and that modern cultural artifact PowerPoint to drive innovation into the bedrock of the culture. I did this at several firms where PowerPoint was closer to an addiction than a facet of the culture. Quite simply, I insisted every program update, every group or function presentation, start with HLI.

  • H = Highlights: Show highlights of what the team did well. The real objective is to say “thanks” and acknowledge a mini win. Over time, teams start to think in terms of what they can put under ‘H’ on the front page. Accomplishment and recognition of accomplishment are necessary for a motivated environment.
  • L = Lowlights: Here you want to see some stretch, some failure. But, most of all, you want to see some learning and experimenting. By reviewing this without beating anyone up—maybe even praising the effort—you eliminate the fear. The message quickly goes through the organization that no one got killed for stretching or trying harder and occasionally dropping the ball. This also helps kill one of the most anti-innovation elements in business, the “under promise, over deliver” malaise.
  • I = Innovation: This is simply asking what you tried that was new, what you grabbed from phase two and did in phase one, what serial process you made parallel, what new method or tool you used, what you borrowed from prior efforts, etc.

If anyone shows up with a presentation that doesn’t lead with HLI, you politely cancel the meeting and get them to come back later. Over time, this creates activity inside teams so they can fill in the three sections. Teams start to have early conversations about how they are going to innovate, stretch and learn.

Innovation at scale requires change management 

There are many stories about the initial excitement of going big on innovation that are then followed by failure and disillusionment because the leadership attention waned as the novelty of the program passed and the hard work of change management, scaling and maintaining ensued.

I cannot talk about creating a culture of innovation without also teaching which change management models work best. It sounds obvious to say driving a culture of innovation is change-intensive, yet I almost never see a decent understanding of change management models and which one is most effective.

There are four basic management models:

  1. Edict
  2. Persuasion
  3. Participation (the communities of interest help define the change)
  4. Intervention (the sponsor justifies the need for change, monitors the process and communicates progress)

The change management model that has the highest frequency of success is intervention. It is at least twice as effective as the next-best model. It requires active leadership to continually “sell” the vision or plan, even while executing it. Understanding how that works and making sure everyone understands and follows the changed playbook are topics for a later article.

Suffice it to say, if you were to map the change processes at most firms, they often resemble spaghetti–an inefficient, unintended, sub-optimized maze. The majority of large tech-intensive programs are late, over budget, deliver less than promised or all of the above. Most companies have never mapped their processes and assume all is well.

Bottom line

Creating a culture of innovation inside a supporting ecosystem with a modicum of useful tools and the right leadership can lead to great success. Innovation is a pragmatic, broad-based journey, not a fad-centric exercise. Done well, innovation is the key to being effectively agile, and it is a concrete force multiplier. It very well may be the only sustainable competitive advantage over the next decade.

Do you have a culture that can innovate broadly, or do you have a silo-ed innovation team or champion or campaign?

Helping Data Scientists Through Storytelling

Good communication is always a two-way street. Insurers that employ data scientists or partner with data science consulting firms often look at those experts much like one-way suppliers. Data science supplies the analytics; the business consumes the analytics.

But as data science grows within the organization, most insurers find the relationship is less about one-sided data storytelling and more about the synergies that occur in data science and business conversations. We at Majesco don’t think it is overselling data science to say these conversations and relationships can have a monumental impact on the organization’s business direction. So, forward-thinking insurers will want to take some initiative in supporting both data scientists and business data users as they work to translate their efforts and needs for each other.

In my last two blog posts, we walked through why effective data science storytelling matters, and we looked at how data scientists can improve data science storytelling in ways that will have a meaningful impact.

In this last blog post of the series, we want to look more closely at the organization’s role in providing the personnel, tools and environment that will foster those conversations.

Hiring, supporting and partnering

Organizations should begin by attempting to hire and retain talented data scientists who are also strong communicators. They should be able to talk to their audience at different levels—very elementary levels for “newbies” and highly theoretical levels if their customers are other data scientists. Hiring a data scientist who only has a head for math or coding will not fulfill the business need for meaningful translation.

Even data scientists who are proven communicators could benefit from access to in-house designers and copywriters for presentation material. Depending on the size of the insurer, a small data communication support staff could be built to include a member of in-house marketing, a developer who understands reports and dashboards and the data scientist(s). Just creating this production support team, however, may not be enough. The team members must work together to gain their own understanding. Designers, for example, will need to work closely with the analyst to get the story right for presentation materials. This kind of scenario works well if an organization is mass-producing models of a similar type. Smooth development and effective data translation will happen with experience. The goal is to keep data scientists doing what they do best—using less time on tasks that are outside of their domain—and giving data’s story its best possibility to make an impact.

Many insurers aren’t yet large enough to employ or attract data scientists. A data science partner provides more than just added support. It supplies experience in marketing and risk modeling, experience in the details of analytic communications and a broad understanding of how many areas of the organization can be improved.

Investing in data visualization tools

Organizations will need to support their data scientists, not only with advanced statistical tools but with visualization tools. There are already many data mining tools on the market, but many of these are designed with outputs that serve a theoretical perspective, not necessarily a business perspective. For these, you’ll want to employ tools such as Tableau, Qlikview and YellowFin, which are all excellent data visualization tools that are key to business intelligence but are not central to advanced analytics. These tools are especially effective at showing how models can be used to improve the business using overlaid KPIs and statistical metrics. They can slice and dice the analytical populations of interest almost instantaneously.

When it comes to data science storytelling, one tool normally will not tell the whole story. Story telling will require a variety of tools, depending on the various ideas the data scientist is trying to convey. To implement the data and model algorithms into a system the insurer already uses, a number of additional tools may be required. (These normally aren’t major investments.)

In the near future, I think data mining/advanced analytics tools will morph into something able to contain more superior data visualization tools than are currently available. Insurers shouldn’t wait, however, to test and use the tools that are available today. Experience today will improve tomorrow’s business outcomes.

Constructing the best environment

Telling data’s story effectively may work best if the organization can foster a team management approach to data science. This kind of strategic team (different than the production team) would manage the traffic of coming and current data projects. It could include a data liaison from each department, a project manager assigned by IT to handle project flow and a business executive whose role is to make sure priority focus remains on areas of high business impact. Some of these ideas, and others, are dealt with in John Johansen’s recent blog series, Where’s the Real Home for Analytics?

To quickly reap the rewards of the data team’s knowledge, a feedback vehicle should be in place. A communication loop will allow the business to comment on what is helpful in communication; what is not helpful; which areas are ripe for current focus; and which products, services and processes could use (or provide) data streams in the future. With the digital realm in a consistent state of fresh ideas and upheaval, an energetic data science team will have the opportunity to grow together, get more creative and brainstorm more effectively on how to connect analytics to business strategies.

Equally important in these relationships is building adequate levels of trust. When the business not only understands the stories data scientists have translated for them but also trusts the sources and the scientists themselves, a vital shift has occurred. The value loop is complete, and the organization should become highly competitive.

Above all, in discussing the needs and hurdles, do not lose the excitement of what is transpiring. An insurer’s thirst for data science and data’s increased availability is a positive thing. It means complex decisions are being made with greater clarity and better opportunities for success. As business users see results that are tied to the stories supplied by data science, its value will continue to grow. It will become a fixed pillar of organizational support.

This article was written by Jane Turnbull, vice president – analytics for Majesco.

Leadership Coaching: Is It For You?

Have you experienced the benefits of leadership coaching? Years ago, U.K. business leaders appeared to just see it as an American business fad (for a culture that has also embraced the benefits of therapists and given us great TV like “In Treatment“). However, over the last decade, more and more U.K. businesses have embraced executive coaching, and the academic evidence for efficacy has grown substantially. Even in 2005, 88% of U.K. organizations reported using coaching and, by 2009, 93% of U.S. organizations.

The next revolution in coaching for businesses is the expansion of coaching to a wider leadership population. Once the preserve of CEOs or main board members, leadership coaching is now being expanded at progressive businesses to include all directors, talent pipeline candidates or, in some cases, the wider organization through team coaching. My personal interest is in the benefits of coaching for the rising stars who are today’s customer insight leaders.

There is a growing trend to create customer insight director or chief knowledge officer roles, often for individuals who have never held C-suite responsibilities. Such leaders are ideal candidates for coaching, not because of any deficits, but rather to ensure that they perform as well as possible and achieve the challenging goals for their new strategic focus.

So, what does coaching entail? Very briefly, the term covers a multitude of approaches and has many possible definitions. But experts now agree that executive coaching can be defined as: “a relationship-based intervention. Its focus is on the enhancement of personal performance at work through behavioral, cognitive and motivational interventions used by the coach, which provide change in the client.”

That more academic definition hints at the fact of multiple models or techniques that can be used, where helpful, to facilitate sessions. The qualification that I’m completing on executive coaching includes learning coaching models: goal-oriented; cognitive behavioral; positive psychology; and neurolinguistic programming. My own experience of coaching executives has taught me that different models can be appropriate at different times, with different clients, in different organizational contexts. The most important skill is still genuine active listening, but frameworks to help guide sessions and clear goals to be achieved do both help.

I’m encouraged by the positive messages being given by a number of organizations with regard to the importance of coaching (see “Coaching at Work” magazine). However, I have not yet seen this commitment applied to the customer insight leadership population. I hope that change will come, and I am focusing part of my business on helping to meet that need.

Have you seen the benefits of coaching or mentoring in your leadership role? I’d love to hear more about your experience of this emerging profession.