To Recognize Risks Earlier, Invest in Analytics

You’ve probably heard business leaders justify their flat-footedness in a crisis by claiming that every organization is flying blind in times of deep uncertainty. But in fact some leaders know precisely where they’re going. They understand what’s required to chart a course through market turbulence, and they’ve built organizations with keen situational awareness.

When it comes to developing the ability to figure out where things are heading and respond nimbly to a changing environment, nothing is more important than analytics. Unfortunately, in recent years analytics (also known as data mining or business intelligence) has become the unloved stepchild of data sciences, overshadowed by machine learning and statistics. Those two disciplines layer mathematical sophistication on top of a foundation of human intuition, creating an appealing illusion of objectivity and deft steering. Ironically, of the three, analytics is the most essential competency for navigating crises.

Solutions based on AI and machine learning hum along well during stable times but fall apart when disaster strikes. These technologies automate tasks by extracting patterns from data and turning them into instructions. Such models can quickly become obsolete when the inputs to the system change. Analytics, in contrast, alerts you when the rules of the game are changing. Without that kind of a warning, automation solutions can quickly go off the rails, leaving you exposed to exogenous shocks.

Statistics has a similar shortcoming during a crisis. Statisticians help decision-makers get rigorous answers. But what if they’re asking the wrong questions? While statistical skills are required to test hypotheses, analysts have the acumen to come up with the right hypotheses in the first place. To attempt statistics without analytics, you’d need great confidence in your assumptions—the kind of confidence that’s foolhardy when a crisis pulls the rug out from under you.

Analysts thrive in ambiguity. Their talent is exploration, which makes them particularly good at foreseeing and responding to crises. By searching internal and external data sources for critical information, analysts keep a finger on the pulse of what’s going on. They scan the horizon for trends and formulate questions about what’s behind them. Their job is to inspire executives with thought-provoking yet qualified possibilities. Once the highest-priority hypotheses have been short-listed by leaders, then it’s time to call in a statistician to pressure-test them and separate true insights from red herrings.

During good times, leading organizations build analytics capabilities to strengthen their ability to innovate. Analysts’ ability to find clues to such things as shifting consumer tastes can help firms take advantage of opportunities before less-savvy competitors do. When the going gets tough, however, what looked like a nice-to-have innovation booster turns into a must-have safety net. To be sure, some events are impossible to see in advance—the true black swans—but addressing their fallout is a game best played with open eyes.

Unfortunately, it’s very hard to cobble together a mature analytics department on short notice. The technical skills that allow analysts to guzzle data with lightning speed merely increase the mass of information they encounter. Spotting a gem in it takes something more. Without domain knowledge, business acumen, and strong intuition about the practical value of discoveries—as well as the communication skills to convey them to decision-makers effectively—analysts will struggle to be useful. It takes time for them to learn to judge what’s important in addition to what’s interesting. You can’t expect them to be an instant solution to charting a course through your latest crisis. Instead, see them as an investment in your future nimbleness.

It also takes time to secure access to the promising data sources analysts need. Ideally, business leaders won’t wait for a big disruption to begin building relationships with data vendors, industry partners, and data collection specialists. Bear in mind that in the face of an extreme shock, your historical data sources may become obsolete. If your understanding of the past fails to give you a useful window on tomorrow’s world—perhaps because a pandemic has changed everything—it doesn’t matter how good your information was yesterday. You need new information. After the 2008 financial crash, for example, banks around the world recognized that there might be an advantage to analyzing nontraditional signals of creditworthiness, such as data from supermarket loyalty cards, but not all players were equally positioned to get access to them.

Additionally, your internal data stores may require special processing before analysts can mine them, so it’s worth thinking about hiring supporting data engineers. If analytics is the discipline of making data useful, then data engineering is the discipline of making data usable; it provides behind-the-scenes infrastructure that makes machine logs and colossal data stores compatible with analytics tool kits.

When I began speaking at conferences about the importance of analytics, I found that convincing an audience of its value was the easy part. The mood changed when I explained the catch: Analytics is a time investment. You can’t count on getting something useful out of every foray into a data set. To succeed at exploration, your organization needs a culture of no-strings-attached analytics. As the leader, you are responsible for setting the scope (which data sources should be looked at) and the time frame (“You have two weeks to explore this database”). Then you must ensure that analysts aren’t punished for coming back empty-handed.

During an extreme shock, your historical data sources may become obsolete. Then it doesn’t matter how good your information was yesterday. You need new information.

Once business leaders accept that analytics represents an investment that may not immediately pay off, I hit the next stumbling block: the perception that only a large and technologically sophisticated company such as Alphabet can afford it. This is nonsense. In my experience you’re more likely to find analytics thriving in start-ups than at well-established behemoths.

Start-ups naturally invest in analytics as they try to navigate a new market, with several generalists taking on a share of the exploratory work. Then as the venture grows, the culture changes. Workers are trusted less and made more accountable for return on their efforts, and overzealous management stifles opportunities for analytics to thrive. Analysts hired into this culture rarely get to enjoy the most interesting part of their work—exploration—and instead serve as human search engines and dashboard janitors. Many quit out of frustration as their potential is squandered.

Creating a culture where analytics flourishes takes thoughtful leadership. As organizations grow toward incumbency, only the most visionary will have the courage to nurture a true analytics department and make sure that business leaders have access to it and are influenced by it. Industries that have been burned by a previous crisis — banking is a good example — are especially likely to invest in analytics and apply it to risk management.

Becoming a leader in analytics takes a commitment to trust your analysts and give them space to do their work. Their job, after all, will be to reveal threats that you never even imagined should be on your radar. That sort of work can’t be managed with a stopwatch and a checklist.

Crises such as a pandemic—when no one has the answers, and uncertainty is high—remind us of the importance of asking the right questions. Analytics gives firms an edge in learning and adapting. When the world is suddenly upended, those who can learn the fastest are best positioned to succeed. Smart companies will invest in analytics today to get ahead of whatever is coming tomorrow.

By: Cassie Kozyrkov

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RedRisks

👀 OVERVIEW: On the 3rd June 2020, I presented a live event on Risk Management Fundamentals. This video is an extract of the “Risk Identification” presentation. Due to demand, a future live event rerun is planned and if this appeals to you, please subscribe to the weekly newsletter on the website and I can keep you posted. 🖥 WEBSITE / POST: https://www.redrisks.com/risk-managem… 📧 SUBSCRIBE to my free WEEKLY newsletter: https://www.redrisks.com 🙏 ABOUT THIS YOUTUBE CHANNEL (“RedRisks”): https://youtu.be/AsXUaIACQrA 🔔 PLEASE SUBSCRIBE AND SUPPORT THIS YOUTUBE CHANNEL: If you liked this video, please give me a thumbs up (or a thumbs down – they’re all important). 👪 CONNECT WITH ME: Linkedin: https://www.linkedin.com/in/sonnigopal/

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How People Analytics Can Help You Change Process, Culture, and Strategy

It seems like every business is struggling with the concept of transformation. Large incumbents are trying to keep pace with digital upstarts., and even digital native companies born as disruptors know that they need to transform. Take Uber: at only eight years old, it’s already upended the business model of taxis. Now it’s trying to move from a software platform to a robotics lab to build self-driving cars.

And while the number of initiatives that fall under the umbrella of “transformation” is so broad that it can seem meaningless, this breadth is actually one of the defining characteristic that differentiates transformation from ordinary change. A transformation is a whole portfolio of change initiatives that together form an integrated program.

And so a transformation is a system of systems, all made up of the most complex system of all — people. For this reason, organizational transformation is uniquely suited to the analysis, prediction, and experimental research approach of the people analytics field.

People analytics — defined as the use of data about human behavior, relationships and traits to make business decisions — helps to replace decision making based on anecdotal experience, hierarchy and risk avoidance with higher-quality decisions based on data analysis, prediction, and experimental research. In working with several dozen Fortune 500 companies with Microsoft’s Workplace Analytics division, we’ve observed companies using people analytics in three main ways to help understand and drive their transformation efforts.

In core functional or process transformation initiatives — which are often driven by digitization — we’ve seen examples of people analytics being used to measure activities and find embedded expertise. In one example, a people analytics team at a global CPG company was enlisted to help optimize a financial process that took place monthly in every country subsidiary around the world. The diversity of local accounting rules precluded perfect standardization, and the geographic dispersion of the teams made it hard for the transformation group to gather information the way they normally would — in conversation.

In core functional or process transformation initiatives — which are often driven by digitization — we’ve seen examples of people analytics being used to measure activities and find embedded expertise. In one example, a people analytics team at a global CPG company was enlisted to help optimize a financial process that took place monthly in every country subsidiary around the world. The diversity of local accounting rules precluded perfect standardization, and the geographic dispersion of the teams made it hard for the transformation group to gather information the way they normally would — in conversation.

So instead of starting with discovery conversations, people analytics data was used to baseline the time spent on the process in every country, and to map the networks of the people involved. They discovered that one country was 16% percent more efficient than the average of the rest of the countries: they got the same results in 71 fewer person-hours per month and with 40 fewer people involved each month.

The people analytics team was surprised — as was finance team in that country, which had no reason to benchmark themselves against other countries and had no idea that they were such a bright spot. The transformation office approached the country finance leaders with their findings and made them partners in process improvement for the rest of the subsidiaries.

It’s unlikely the CPG company would have been able to recognize and replicate these bright spots if they had undertaken transformation with a top-down approach. And, perhaps more importantly, it involved and engaged the people on the ground who had unwittingly discovered a better way of doing things.

In bottoms-up cultural transformation initiatives, the how things are done is equally or more important than what is done. Feedback loops and other methods of data-driven storytelling are our favorite way that people analytics makes culture transformation happen. Often times, facts can change the conversation from tired head-nodding to curiosity. One people analytics team in an engineering company was struggling to help develop the company’s managers, for example. Managers often perpetuated a “sink or swim” culture that didn’t fit the company’s aspirations to be an inclusive, humane workplace.

The data analysis found that teams whose managers spent at least 16 minutes of one-on-one time with each direct per week had 30% percent more engaged direct reports than the average manager, who spent just 9 minutes per week with directs. When they brought that data-driven story to the front lines, suddenly a platitude was transformed into a useful benchmark that got the attention of managers. In this way, data storytelling is a lightweight way to build trust among stakeholders and bring behavioral science to culture transformation.

Top-down strategic transformation is often made necessary by market and technology factors outside the company, but here people analytics is a critical factor for execution. A people analytics team can serve as an instrument panel of sorts to track resources, boundaries, capacity, time use, networks, skill sets, performance, and mindsets that can help pinpoint where change is possible and can measure what happens when you try it.

One people analytics team at a financial services company was trying to help the CEO manage growth while he worked to instill a new culture in which departments would be asked to run leaner and more competitive in the market – “scrappy” and “hungry” were terms that often came up. As the transformation accelerated, teams were asked to do more with less, generate more data, and make decisions faster. Amid this, department leaders began to hear anecdotes about burnout and change fatigue and questioned whether the pace was sustainable.

To address this, the people analytics team provided their CEO with a dashboard showing the number of hours that knowledge workers were active for in different teams. When an entire team is over-utilized, he knows they can’t handle more change, while under- or unevenly utilized teams might be more receptive. He can also slice the dashboard by tenure, to learn whether recent hires have been effectively onboarded before approving new hire requests to absorb extra work.

As organizations increasingly look to data to help them in their transformation efforts, it’s important to remember that this doesn’t just mean having more data or better charts. It’s about mastering the organizational muscle of using data to make better decisions; to hypothesize, experiment, measure and adapt. It’s not easy. But through careful collection and analysis of the right data, a major transformation can be a little less daunting – and hopefully a little more successful.

By: Chantrelle Nielsen & Natalie McCullough

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AIHR – Academy to Innovate HR

What is People Analytics and how is it different from HR Analytics, Workforce Analytics, or Talent Analytics? What has made it so popular all of a sudden and why should you be excited about it? What is the ROI of People Analytics? These are the questions that will be answered in this video!

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The Robot Will See You Now: Could Computers Take Over Medicine Entirely – Tim Adams

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Like all everyday miracles of technology, the longer you watch a robot perform surgery on a human being, the more it begins to look like an inevitable natural wonder.

Earlier this month I was in an operating theatre at University College Hospital in central London watching a 59-year-old man from Potters Bar having his cancerous prostate gland removed by the four dexterous metal arms of an American-made machine, in what is likely a glimpse of the future of most surgical procedures.

The robot was being controlled by Greg Shaw, a consultant urologist and surgeon sitting in the far corner of the room with his head under the black hood of a 3D monitor, like a Victorian wedding photographer. Shaw was directing the arms of the remote surgical tool with a fluid mixture of joystick control and foot-pedal pressure and amplified instruction to his theatre team standing at the patient’s side. The surgeon, 43, has performed 500 such procedures, which are particularly useful for pelvic operations; those, he says, in which you are otherwise “looking down a deep, dark hole with a flashlight”.

The first part of the process has been to “dock the cart on to the human”. After that, three surgical tools and a video camera, each on the end of a 30cm probe, have been inserted through small incisions in the patient’s abdomen. Over the course of an hour or more Shaw then talks me through his actions.

“I’m just going to clip his vas deferens now,” he says, and I involuntarily wince a little as a tiny robot pincer hand, magnified 10 times on screens around the operating theatre, comes into view to permanently cut off sperm supply. “Now I’m trying to find that sweet spot where the bladder joins the prostate,” Shaw says, as a blunt probe gently strokes aside blood vessels and finds its way across the surface of the plump organ on the screen, with very human delicacy.

After that, a mesmerising rhythm develops of clip and cauterise and cut as the velociraptor pairing of “monopolar curved scissors” and “fenestrated bipolar forceps” is worked in tandem – the surprisingly exaggerated movements of Shaw’s hands and arms separating and sealing tiny blood vessels and crimson connective tissue deep within the patient’s pelvis 10ft away. In this fashion, slowly, the opaque walnut of the prostate emerges on screen through tiny plumes of smoke from the cauterising process.

This operation is part of a clinical trial of a procedure pioneered in German hospitals that aims to preserve the fine architecture of microscopic nerves around the prostate – and with them the patient’s sexual function. With the patient still under anaesthetic, the prostate, bagged up internally and removed, will be frozen and couriered to a lab at the main hospital site a mile away to determine if cancer exists at its edges. If it does, it may be necessary for Shaw to cut away some of these critical nerves to make sure all trace of malignancy is removed. If no cancer is found at the prostate’s margins the nerves can be saved. While the prostate is dispatched across town, Shaw uses a minuscule fish hook on a robot arm to deftly sew bladder to urethra.

 
‘The technique itself feels like driving and the 3D vision is very immersive’: Greg Shaw controls
the robot as it operates on a patient Photograph: Jude Edginton for the Observer

The Da Vinci robot that Shaw is using for this operation, made by the American firm Intuitive Surgical, is about as “cutting edge” as robotic health currently gets. The £1.5m machine enables the UCH team to do 600 prostate operations a year, a four-fold increase on previous, less precise, manual laparoscopic techniques.

Mostly, Shaw does three operations one or two days a week, but there have been times, with colleagues absent, when he has done five or six days straight. “If you tried to do that with old-fashioned pelvic surgery, craning over the patient, you would be really hurting, your shoulders and your back would seize up,” he says.

There are other collateral advantages of the technology. It lends itself to accelerated and effective training both because it retains a 3D film of all the operations conducted, and enables a virtual-reality suite to be plugged in – like learning to fly a plane using a simulator. The most important benefit however is the greater safety and fewer complications the robot delivers.

I wonder if it changes the psychological relationship between surgeon and patient, that palpable intimacy.

Shaw does not believe so. “The technique itself feels like driving,” he says. “But that 3D vision is very immersive. You are getting lots of information and very little distraction and you are seeing inside the patient from 2cm away.”

There are, he says, still diehards doing prostatectomies as open surgery, but he finds it hard to believe that their patients are fully informed about the alternatives. “Most people come in these days asking for the robot.”

If a report published this month on the future of the NHS is anything to go by, it is likely that “asking for the robot” could increasingly be the norm in hospitals. The interim findings of the Institute for Public Policy Research’s long-term inquiry into the future of health – led by Lord Darzi, the distinguished surgeon and former minister in Gordon Brown’s government – projected that many functions traditionally performed by doctors and nurses could be supplanted by technology.

“Bedside robots,” the report suggested, may soon be employed to help feed patients and move them between wards, while “rehabilitation robots” would assist with physiotherapy after surgery. The centuries-old hands-on relationship between doctor and patient would inevitably change. “Telemedicine” would monitor vital signs and chronic conditions remotely; online consultations would be routine, and someone arriving at A&E “may begin by undergoing digital triage in an automated assessment suite”.

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Even the consultant’s accumulated wisdom will be superseded. Machine-learning algorithms fed with “big data” would soon be employed to “make more accurate diagnoses of diseases such as pneumonia, breast and skin cancers, eye diseases and heart conditions”. By embracing a process to achieve “full automation” Lord Darzi’s report projects that £12.5bn a year worth of NHS staff time (£250m a week) would be saved “for them to spend interacting with patients” – a belief that sounds like it would be best written on the side of a bus.

While some of these projections may sound far more than the imagined decade away, others are already a reality. Increasingly, the data from sensors and implants measuring blood sugars and heart rhythms is collected and fed directly to remote monitors; in London, the controversial pilot scheme GP@Hand has seen more than 40,000 people take the first steps toward a “digital health interface” by signing up for online consultations accessed through an app – and in the process, de-registering from their bricks-and-mortar GP surgery. Meanwhile, at the sharpest end of healthcare – in the operating theatre – robotic systems like the one used by Greg Shaw are already proving the report’s prediction that machines will carry out surgeries with greater dexterity than humans. As a pioneer of robotic surgical techniques, Lord Darzi knows this better than most.Bedside robots will feed patients while others would assist with physio

In a way, it is surprising that it has taken so long to reach this point. Hands-off surgery was first developed by the US military at the end of the last century. In the 1990s the Pentagon wanted to explore ways in which operations at M*A*S*H-style field hospitals might be performed by robots controlled by surgeons at a safe distance from the battlefield. Their investment in Intuitive Surgical and its Da Vinci prototype has given the Californian company – valued at $62bn – a virtual monopoly, fiercely guarded, with 4,000 robots now operating around the world.

Jaime Wong MD is the consultant lead on the R&D programme at Intuitive Surgical. He is also a urologist who has been using a Da Vinci robot for more than a decade and watched it evolve from original 2D displays that involved more spatial guesswork, to the current far more manoeuvrable and all-seeing version.

Wong still enjoys seeing traditional open surgeons witnessing a robotic operation for the first time and “watching the amazement on their faces at all the things they did not quite realise are located in that area”.

In the next stage of development, he sees artificial intelligence (AI) and machine learning playing a significant role in the techniques. “Surgery is becoming digitised, from imaging to movement to sensors,” he says, “and everything is translating into data. The systems have a tremendous amount of computational power and we have been looking at segmenting procedures. We believe, for example, we can use these processes to reduce or eliminate inadvertent injuries.”

Up until recently, Da Vinci, having stolen a march on any competition, has had this field virtually to itself. In the coming year, that is about to change. Google has, inevitably, developed a competitor (with Johnson & Johnson) called Verb. The digital surgery platform – which promises to “combine the power of robotics, advanced instrumentation, enhanced visualisation, connectivity and data analytics” – aims to “democratise surgery” by bringing the proportion of robot-assisted surgeries from the current 5% up to 75%. In Britain, meanwhile, a 200-strong company called CMR Surgical (formerly Cambridge Medical Robotics) is close to approval for its pioneering system, Versius, which it hopes to launch this year.

Wong says he welcomes the competition: “I tend to think it validates what we have been doing for two decades.”

The latest creators of robot surgeons see ways to move the technology into new areas. Martin Frost, CEO of the Cambridge company, tells me how the development of Versius has involved the input of hundreds of surgeons with different soft-tissue specialities, to create a portable and modular system that could operate not just in pelvic areas but in more inaccessible parts of the head, neck and chest.

“Every operating room in the world currently possesses one essential component, which is the surgeons’ arm and hand,” Frost says. “We have taken all of the advantages of that form to make something that is not only bio-mimicking but bio-enhancing.” The argument for the superiority of minimally invasive surgery is pretty much won, Frost suggests: “The robotic genie is out of the bottle.”

And what about that next stage – does Frost see a future in which AI-driven techniques are involved in the operation itself?

“We see it in small steps,” he says. “We think that it is possible, within a few years, that a robot may do part of certain procedures ‘itself’, but we are obviously a very long way from a machine doing diagnosis and cure, and there being no human involved.”A specialist mentor could be looking at different camera views, providing second opinions. It will be like ‘phone a friend’

The other holy grail of telesurgery – the possibility of remote “battlefield” operations – is closer to being a reality. In a celebrated instance, Dr Jacques Marescaux, a surgeon in Manhattan, used a protected high-speed connection and remote controls to successfully remove the gallbladder of a patient 3,800 miles away in Strasbourg in 2001. Since then there have been isolated instances of other remote operations but no regular programme.

In 2011, the US military funded a five-year research project to determine how feasible such a programme might be with existing technology. It was led by Dr Roger Smith at the Nicholson Center for advanced surgery in Florida.

Smith explained to me how his study was primarily to determine two things: first, latency – the tiny time lag of high-speed connections over large distances – and second, how that lag interfered with a surgeon’s movements. His studies found that if the lag rose above 250 milliseconds “the surgeon begins to see or sense that something is not quite right”. But also that using existing data connections, between major cities, or at least between major hospital systems, “the latency was always well below what a human surgeon could perceive”.

The problem lay in the risk of unreliability of the connection. “We all live on the internet,” Smith says. “Most of the time your internet connection is fantastic. Just occasionally your data slows to a crawl. The issue is you don’t know when that will happen. If it occurs during a surgery you are in trouble.” No surgeon – or patient – would like to see a buffering symbol on their screen.

The ways around that would involve dedicated networks – five lines of connectivity with a performance level at least two times what you would ever need, Smith says, “so that the chances of having an issue were like one in a million”.

Those kinds of connections are available, but the lack of investment is more one of regulation and liability than cost. Who would bear the risk of connection failure? The state in which the surgeon was located, or that in which the patient was anaesthetised – or the countries through which the cable passed? As a result, Smith says: “In the civilian world, there are few situations where you would say this is a must-have thing.”

He envisages three possible champions of telesurgery: the military, “If you could, say, create a connection where the surgeon could be in Italy and the patient in Iraq”; medical missionaries, “Where surgeons in the developed world worked through robots in places without advanced surgeons”; and Nasa, “At a point where you have enough people in space that you need to set up a way to do surgery.” For the time being the technology is not robust enough for any of these three.

For Jaime Wong the risks are likely to remain too great. Intuitive Surgical is pursuing the concepts of “telementoring” or “teleproctoring” rather than telesurgery. “The local surgeon would be performing the surgery, while our monitor would be remote,” he suggests, “and a specialist mentor could be looking at different camera views, providing second opinions. It will be like ‘phone a friend’.”

True telesurgery, Roger Smith suggests, also begs a further question, one which we may yet hear in the coming decade or so. “Would you have an operation without a surgeon in the room?” For the time being, the answer remains a no-brainer.

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How Predictive Analytics Can Help Your Business See the Future – Emily Conklin

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Your customers are supplying you with data that can help you predict the future. Now more than ever, predictive analytics are becoming available to small businesses looking to get ahead of the competition by mining their data and generating meaningful intelligence. From mapping customer purchase trends to optimizing product campaigns, predictive analytics can be the digital marketing solution your company needs.

While this is not a new concept, the widespread availability of predictive tools and the exploding arena of digital marketing has given these analytics renewed relevance. An investment in predictive analytics may give your business the competitive advantage it needs, helping you leave yesterday’s problems behind and focus on growth to come.

Check out the infographic below from Digital Marketing Philippines to find out more about how predictive analytics can work for you.

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How to Refocus Your Strategy and Reenergize Your Team – Stanley Meytin

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A person’s passion is the sincerest definition of who they are. Passion can manifest itself in a hobby, an aspiration, or if you’re really lucky, a career. Take two people, Joe and Jane, as an example. Joe has a passion outside of his career. He devotes a lot of his free time to this passion and naturally speaks about it to his peers.

When his peers think of him they probably define him as “person passionate about X.” Now take Jane, one of the lucky few who has made a career out of her passion. She devotes twice the amount of time, twice the amount of energy and twice the amount of conversation to her passion. How do you think her peers define her?

If you’ve read Simon Sinek’s bestseller Start With Why, then Jane will remind you of Herb Kelleher, co-founder of Southwest Airlines, or Steve Jobs, co-founder of Apple Inc. Joe will remind you of the Wright Brothers. Each of these individuals built empires by undyingly following their passion. Sure, you can claim that these individuals are used as examples because of winner’s bias. But they succeeded because not only were they extremely passionate. They succeeded because they were able to clearly communicate their visions.

I consider myself extremely lucky. Like Jane, I’ve built a career out of my passion. When I first launched my film production company, my team asked the same questions regarding our clients that our competition was asking:

  • What is this client doing that’s different?
  • What do they bring to the table?
  • What problems are they solving for their customers?

While these questions helped us understand our clients, we realized they weren’t getting to the core of what defined them. We were part of the same old convention of business. We were focusing on what our clients were doing and not why they were doing it in the first place. Once we realized this, we began asking ourselves different questions:

  • How can we harness the passion that defines the client’s company to create a story?
  • Are their employees inspired by that passion?
  • Does the story align with their core values?
  • How can we align the story with the company’s brand mission?
  • How is that story going to connect with their audience?
  • How are we going to make the story authentic and engaging?

The biggest takeaway, however, didn’t come in the form of one of our clients’ videos going viral. It came in-house. 2016 was the first year we set a quantitative benchmark for the number of videos we wanted to produce. Not only did we not hit the benchmark, but with all the energy we put into hitting a quota we lost focus on creating a better product. We produced more videos, but they were watered down compared to previous years. We lost our own purpose.

We got rid of all quantity benchmarks in 2017 and as a team, we held a meeting to refocus. In this meeting, we asked ourselves the same questions that we asked our clients. We ended the meeting with a mission to create a video channel to tell impactful and authentic stories that inspire others.

That channel has been a remarkably accurate reflection of the meeting where it was first conceptualized. We’re now using the same techniques that helped us define our purpose in our core business for our corporate clients. Not only has it righted our ship and produced success but it has also provided us with an entirely new set of questions to ask our clients:

  • Is their organization helping others?
  • Is their mission connecting with others?
  • Are their customers genuinely understanding their mission?
  • Are employees buying into their mission, do they believe their roles play an important part in promoting the mission?
  • Are they building a community?
  • Are they staying true to their core values and the values of their customers and employees?

The beauty of these questions is that you can propose them to your clients, to your employees and even to yourself. They’re not specific to video production or any industry for that matter. If you already have the answers, that’s incredible. If not, then use them to refocus your strategy or reenergize your team.

Just swap “their” and “they” for “your” and “you.” Connecting to people on a deeper level, nurturing a human connection, evoking emotion and inspiring are key ingredients to building loyalty and bringing the best out in people.

Note, however, that not all ingredients are created equal. Like apples grown on two separate farms, the ingredients that I listed — those that were seeded and cared for with passion — will always taste better.

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