Marina Gorbis's Blog, page 798

How Mount Sinai Health System Fosters Collaboration to Fight Cancer

Alice Mollon/Getty Images

Precision cancer medicine — sequencing a patient’s DNA in order to customize cancer treatments — shows promise, but is very much in its infancy. It’s still not nearly precise enough to launch a winning battle against many forms of cancer. To dramatically advance in this field, clinicians, medical researchers, and computer scientists must substantially deepen their collaboration.

This is a challenge for most academic medical centers, which are typically hierarchical, segmented organizations. The hospital stands apart from the medical school, and for employees of each to join forces, the chains of command must approve. Granting researchers access to extraordinary computational brainpower, essential for some of today’s medical research, often requires even more authorization.

The Mount Sinai Health System is organized differently from most, as one integrated institution. Doctors from the seven Mount Sinai hospitals work side by side with researchers from the Icahn School of Medicine at Mount Sinai. Indeed, many clinicians also have Sinai research labs. If a clinician and a researcher devise a viable idea to solve a medical problem, they are free to join forces and pursue the project. This makes it possible to rapidly bring a finding from the lab bench to the patient bedside.

Insight Center



The Future of Health Care
Sponsored by Medtronic

Creating better outcomes at reduced cost.

By taking advantage of Mount Sinai’s collaborative freedom, we are using advanced computer analytics to effectively treat some of the most challenging cancers, those that affect the blood and bone marrow. Cells from these cancers are highly heterogeneous, arising from different genetic drivers, each of which may or may not respond to a particular medicine. While solid tumors, like lung cancers, often respond well to treatments selected based on an analysis of the tumor’s DNA, such analysis cannot provide the information needed to effectively target blood cancers such as multiple myeloma. These kinds of liquid cancers are so complex and difficult to treat — virtually all patients relapse — that DNA analysis has yet to make a dent in treatment.

To unmask the genetic anomalies that are specific to multiple myeloma and that could guide treatment, our teams at the Icahn School of Medicine at Mount Sinai collaborated to map both DNA and RNA signatures of multiple myeloma tumors. RNA is the ultimate messenger of the genetic instructions a cell needs to manufacture proteins. Only information transcribed from DNA into RNA will ultimately impact the structure of proteins, including the mutations that lie behind cancers. So it is critical to understand the RNA of a complex cancer.

As we planned to crack and classify the RNA profile of multiple myeloma, it quickly became clear that the task would require a large amount of dedicated computing power. Our Institute for Next Generation Healthcare created a dedicated server for the multiple myeloma research, named CRUSHER, at an off-campus Mount Sinai computer lab, and a customized software program, named DAPHNE, to get the job done. With this high-power computing capability we were able not only to decipher the RNA of multiple myeloma cancer cells but also to link mutations affecting protein structure to disease patterns, and identify novel associations between clinical traits and genomic markers. Together, our myeloma specialists, genomics scientists, and drug repurposing experts used the DAPHNE software to integrate DNA and RNA sequencing, as well as clinical data, to identify non-myeloma drugs that might be repurposed to help patients whose disease had relapsed after receiving standard therapy approved for multiple myeloma.

Preliminary trials are highly encouraging. In one patient, the RNA analysis revealed abnormal activation of a molecular pathway that enables the transmission of a signal from a receptor on the surface of a cell to the DNA in the cell’s nucleus. After he was treated with a drug approved for other cancers that inhibits this pathway, his myeloma went into remission. In another case, RNA and DNA analysis identified oral drugs approved for breast cancer and chronic leukemia that should be effective against myeloma. A 70-year-old painter whose myeloma had relapsed after standard therapy went into remission following treatment with the new combination and has returned to painting.

RNA analysis turned out to be far more helpful than DNA sequencing in determining the most effective drugs for each patient. Of the 21 evaluable patients in our study, 11 received a personalized drug based upon RNA profiling, two received a drug based on both RNA and DNA, and eight received a drug based on DNA. This is remarkable because the vast majority of diagnostic companies and oncologists using genetic analysis are studying only patient DNA, not RNA.

The merging of high technology with medical research is still in its early stages while we strive to build our understanding of disease. As we embrace a new paradigm — treating cancers based on multiple genetic drivers rather than histology (cell structure) — academic medical centers should loosen their hierarchies and clear the way for computer scientists to deepen their collaborative efforts with oncologists, pathologists, and geneticists to look beyond DNA sequencing. This is how we will generate the knowledge that will achieve major progress in the war against the most difficult cancers.

How Mount Sinai Heath System Fosters Collaboration to Fight Cancer

Alice Mollon/Getty Images

Precision cancer medicine — sequencing a patient’s DNA in order to customize cancer treatments — shows promise, but is very much in its infancy. It’s still not nearly precise enough to launch a winning battle against many forms of cancer. To dramatically advance in this field, clinicians, medical researchers, and computer scientists must substantially deepen their collaboration.

This is a challenge for most academic medical centers, which are typically hierarchical, segmented organizations. The hospital stands apart from the medical school, and for employees of each to join forces, the chains of command must approve. Granting researchers access to extraordinary computational brainpower, essential for some of today’s medical research, often requires even more authorization.

The Mount Sinai Health System is organized differently from most, as one integrated institution. Doctors from the seven Mount Sinai hospitals work side by side with researchers from the Icahn School of Medicine at Mount Sinai. Indeed, many clinicians also have Sinai research labs. If a clinician and a researcher devise a viable idea to solve a medical problem, they are free to join forces and pursue the project. This makes it possible to rapidly bring a finding from the lab bench to the patient bedside.

Insight Center



The Future of Health Care
Sponsored by Medtronic

Creating better outcomes at reduced cost.

By taking advantage of Mount Sinai’s collaborative freedom, we are using advanced computer analytics to effectively treat some of the most challenging cancers, those that affect the blood and bone marrow. Cells from these cancers are highly heterogeneous, arising from different genetic drivers, each of which may or may not respond to a particular medicine. While solid tumors, like lung cancers, often respond well to treatments selected based on an analysis of the tumor’s DNA, such analysis cannot provide the information needed to effectively target blood cancers such as multiple myeloma. These kinds of liquid cancers are so complex and difficult to treat — virtually all patients relapse — that DNA analysis has yet to make a dent in treatment.

To unmask the genetic anomalies that are specific to multiple myeloma and that could guide treatment, our teams at the Icahn School of Medicine at Mount Sinai collaborated to map both DNA and RNA signatures of multiple myeloma tumors. RNA is the ultimate messenger of the genetic instructions a cell needs to manufacture proteins. Only information transcribed from DNA into RNA will ultimately impact the structure of proteins, including the mutations that lie behind cancers. So it is critical to understand the RNA of a complex cancer.

As we planned to crack and classify the RNA profile of multiple myeloma, it quickly became clear that the task would require a large amount of dedicated computing power. Our Institute for Next Generation Healthcare created a dedicated server for the multiple myeloma research, named CRUSHER, at an off-campus Mount Sinai computer lab, and a customized software program, named DAPHNE, to get the job done. With this high-power computing capability we were able not only to decipher the RNA of multiple myeloma cancer cells but also to link mutations affecting protein structure to disease patterns, and identify novel associations between clinical traits and genomic markers. Together, our myeloma specialists, genomics scientists, and drug repurposing experts used the DAPHNE software to integrate DNA and RNA sequencing, as well as clinical data, to identify non-myeloma drugs that might be repurposed to help patients whose disease had relapsed after receiving standard therapy approved for multiple myeloma.

Preliminary trials are highly encouraging. In one patient, the RNA analysis revealed abnormal activation of a molecular pathway that enables the transmission of a signal from a receptor on the surface of a cell to the DNA in the cell’s nucleus. After he was treated with a drug approved for other cancers that inhibits this pathway, his myeloma went into remission. In another case, RNA and DNA analysis identified oral drugs approved for breast cancer and chronic leukemia that should be effective against myeloma. A 70-year-old painter whose myeloma had relapsed after standard therapy went into remission following treatment with the new combination and has returned to painting.

RNA analysis turned out to be far more helpful than DNA sequencing in determining the most effective drugs for each patient. Of the 21 evaluable patients in our study, 11 received a personalized drug based upon RNA profiling, two received a drug based on both RNA and DNA, and eight received a drug based on DNA. This is remarkable because the vast majority of diagnostic companies and oncologists using genetic analysis are studying only patient DNA, not RNA.

The merging of high technology with medical research is still in its early stages while we strive to build our understanding of disease. As we embrace a new paradigm — treating cancers based on multiple genetic drivers rather than histology (cell structure) — academic medical centers should loosen their hierarchies and clear the way for computer scientists to deepen their collaborative efforts with oncologists, pathologists, and geneticists to look beyond DNA sequencing. This is how we will generate the knowledge that will achieve major progress in the war against the most difficult cancers.

One Reason Mergers Fail: The Two Cultures Aren’t Compatible

Yongyuan Dai/Getty Images

Amazon’s 2017 acquisition of Whole Foods was met with a lot of fanfare. The deal would allow Amazon to grow beyond e-commerce and sell groceries in hundreds of stores while collecting significant shopper data. Meanwhile, Whole Foods could lower its prices (organic avocados for just $1.69!) and scale up after its recent declines in sales and market share. In the words of Whole Foods CEO John Mackey, the partnership was “love at first sight.”

A year later, such optimism seems hard to find at Whole Foods. Stories of employees literally crying on the job over Amazon’s changes have begun circulating. Scorecards measuring compliance with a new inventory system are used to punish and sometimes terminate workers. A group of Whole Foods employees have recently taken steps to explore unionizing. Even customers — the stakeholders that Amazon values the most — have been angry over poorly stocked stores.

So where did the love go?

Amazon and Whole Foods’ relationship problems were completely predictable. The two companies may have seen value in capitalizing on each other’s strengths, but they failed to investigate their cultural compatibility beforehand. They now stand on a fault line where tensions often erupt in mergers. This fault line is what we call tightness versus looseness. When tight and loose cultures merge, there is a good chance that they will clash.

Tight company cultures value consistency and routine. They have little tolerance for rebellious behavior, and use strict rules and processes to uphold cultural traditions. Loose cultures are much more fluid. They generally eschew rules, encourage new ideas, and value discretion. Tight cultures have an efficient orderliness and reassuring predictability, but are less adaptable. Loose cultures tend to be open and creative, but are more disorganized. People in loose cultures prefer visionary, collaborative leaders: those who advocate for change and empower their workers, like Whole Foods’ Mackey. People in tight cultures desire leaders who embody independence, extreme confidence, and top-down decision making. Amazon CEO Jeff Bezos, who is known to expect unwavering discipline from his workers, personifies this leadership style.

Amazon’s culture is a tight one, characterized by structure and precision. Rooted firmly in the manufacturing industry, Amazon has defined processes to maximize its efficiency. Employees operate within a hierarchy and are well aware of the guidelines that dictate their behavior. According to Amazon’s leadership principles, leaders are instructed to “hire and develop the best” and “insist on the highest standards.” Performance is subject to constant measurement and review — employees can anonymously report each other to higher-ups through an internal phone system. Behavior is even more tightly regulated at Amazon’s warehouses, where target goals and surveillance keep production on schedule. This rule-bound culture ensures that all employees understand the company’s objectives and are consistently working to achieve them.

Whole Foods, on the other hand, has a much looser culture. The unique blend of idealism, high profit margins, and rapid growth that came with operating the first certified organic national supermarket in the U.S. provided the founders with considerable latitude in introducing innovative and unorthodox management methods. Prior to the Amazon merger, the company had an egalitarian structure organized around self-managed teams. This structure granted individual employees significant decision-making power. Face-to-face interactions between workers, vendors, and customers were the norm. Managers could operate their stores with autonomy and tailor products to customer preferences. “Empowerment must be much, much more than a mere slogan,” Mackey wrote in a 2010 blog post. “It should be within the very DNA of the organization.” Such decentralization and lack of structure, however, might have ultimately contributed to company-wide inefficiencies that drove up prices.

To understand more about how mergers between tight and loose cultures work, we collected data on over 4,500 international mergers from 32 different countries between 1989 and 2013. The study took into consideration factors such as deal size, monetary stakes, industry, geographic distance, and cultural compatibility. We found that mergers with more-pronounced tight-loose divides performed worse overall. On average, the acquiring companies in mergers with tight-loose differences saw their return on assets decrease by 0.6 percentage points three years after the merger, or $200 million in net income per year. Those with especially large cultural mismatches saw their yearly net income drop by over $600 million.

Fortunately, when diagnosed early, the tight-loose clashes that crop up in mergers can be handled productively. To increase their chances of achieving cultural harmony, companies should do a few things.

Prepare to negotiate culture. In addition to negotiating price and other financial terms, organizations discussing a merger need to negotiate culture. Leaders should start by conducting a cultural assessment to understand how people, practices, and management reflect tightness or looseness in both companies. They should determine the pros and cons of their current levels of tight-loose, as well as the opportunities and threats posed by merging cultures. How might sacrificing some discretion for structure, or vice versa, enhance or harm each organization? Above all, they should identify areas for compromise: Tighter organizations need to identify domains where they can embrace greater looseness, and looser organizations need to think about how they can welcome some tight features. We call these flexible tightness and structured looseness, respectively.

Construct a prenup. Once merging organizations better understand the strengths and weaknesses of their company cultures, they should develop a cultural integration plan that articulates which domains will be loose and which will be tight. Mutual input about how each company will change — and a formal contract documenting those changes — can help ensure long-term success. When Disney bought Pixar in 2006, Disney CEO Robert Iger agreed to a set of ground rules for safeguarding Pixar’s looser culture. For example, Pixar employees weren’t required to sign employment contracts with Disney, were free to choose the titles on their business cards, could decorate their cubicles and offices as they wished, and could continue their annual paper airplane contest. 

Get buy-in. Everyone across both organizations needs to be informed about the integration plan. Simply explaining what the changes will be is not enough; people need to know why they will be implemented. Communicating openly and gaining broad acceptance for changes will help minimize the threat people feel from new ways of doing business. People in tight organizations might feel their control is being threatened. People in loose organizations might feel their autonomy is being threatened. Leaders need to be culturally ambidextrous — or demonstrate the value of being both tight and loose, and work to address employees’ underlying fear of change.

Embrace trial and error. Finally, organizations need to be prepared to reevaluate their original integration strategy. No matter how foolproof the plan may seem, issues are bound to arise. Amazon’s increased standardization and employee surveillance at Whole Foods had positive business outcomes — prices dropped as much as 40% on certain items — but it was also hard on the company culture. Amazon now has an opportunity to learn from these results, and possibly incorporate some of the looser cultural elements that Whole Foods employees value. For example, Amazon could create a better balance between the time people spend on logging inventory and organizing store shelves and the time they spend interacting with customers. Likewise, there may be more domains where Whole Foods can relinquish some of its unstructured business practices. For example, using Amazon’s expertise in data science and logistics, Whole Foods has an opportunity to gain better customer insights and provide its clientele with services that are not only personal but also customized and consistent.

Negotiating tight and loose in organizations takes work, but patience and a willingness to make sacrifices can help merging organizations overcome some of the most difficult challenges. How will the Amazon–Whole Foods partnership pan out? It’s too soon to say, but spending more time on integrating their cultures could help.

6 Ways to Build a Customer-Centric Culture

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Companies have been trying to adopt customer centricity for nearly 20 years now. But the CMO Council reports that “only 14 percent of marketers say that customer centricity is a hallmark of their companies, and only 11 percent believe their customers would agree with that characterization.”

Why do so many companies struggle to get customer centricity right? The volume, velocity, and variety of customer data that now exists overwhelms many organizations. Some companies don’t have the systems and technology to segment and profile customers. Others lack the processes and operational capabilities to target them with personalized communications and experiences.

But the most common, and perhaps the greatest, barrier to customer centricity is the lack of a customer-centric organizational culture. At most companies the culture remains product-focused or sales-driven, or customer centricity is considered a priority only for certain functions such as marketing. To successfully implement a customer-centric strategy and operating model, a company must have a culture that aligns with them — and leaders who deliberately cultivate the necessary mindset and values in their employees.

To build a customer-centric culture, business leaders should take six actions:

Operationalize customer empathy. Empathy is one of those buzzwords that sound really good, but very few companies actually understand what it means, much less practice it. Essentially, customer empathy is the ability to identify a customer’s emotional need, understand the reasons behind that need, and respond to it effectively and appropriately. And it’s pretty rare. According to PwC, only 38% of U.S. consumers say the employees they interact with understand their needs.

To instill empathy as a universal value, one that informs everything their organization does, leaders must do more than give it lip service. Slack, the business communication software company, operationalizes empathy. Employees spend a lot of time reading customer messages and observing customers to try to intuit what they want and need. Customer support specialists are encouraged to research the people they’re helping and create mini personas for them to better understand how the customers are using Slack. The company screens for support people who know how to express empathy through the written word, and the company doesn’t allow them to cut and paste canned responses. And for partners who build apps on the Slack platform, the company promotes nine best practices to help them practice empathy, including “outline your use cases” and “storyboard each interaction.”

Hire for customer orientation. From the very first interaction with prospective employees, organizations should make thinking about customers and their needs a clear priority. At Hootsuite, the social media management platform, marketing and human resources executives collaborate to do this.

During the interview process, hiring managers are required to ask every candidate, regardless of role, a question to gauge their customer orientation. Kirsty Traill, the company’s VP Customer, explains that this practice not only assesses candidates and ensures that every new employee is aligned to customer-centric thinking, but also sends a clear message to everyone — recruits and hiring managers alike — about the importance of customer experience at the company.

Democratize customer insights. For every employee to adopt a customer-centric mindset, every employee must understand the organization’s customers. Adobe Systems has opened up access to customer insights for all employees. It doesn’t store up customer understanding in the sales and marketing groups and then expect other departments to focus solely on their functions.

The company created a new department, a combined customer and employee experience team, to facilitate customer understanding. It set up listening stations where employees can go, either online or in an Adobe office, to listen to customer calls. And at every all-employee meeting, leaders give an update on the company’s customer experience delivery.

Facilitate direct interaction with customers. Companies need to develop ways for employees to interact with customers directly, even in “back office” functions. After all, every employee impacts the customer experience in some way, even if indirectly, so every employee can benefit from interacting with customers to better understand them and learn about their successes and challenges.

Airbnb considers hosts, the people who rent out their homes, to be customers, so it facilitates employee-host interactions by requiring employees to stay in Airbnb rentals whenever they travel for business. The company also asks employees to let hosts stay with them when they attend meetings at the Airbnb offices. What’s more, employees participate in an annual event alongside hosts so that together they discuss learnings from the past year and plans for the next.

Most organizations’ business models probably don’t allow for direct employee-customer contact as organically as Airbnb’s does, but leaders can still facilitate interactions by letting employees observe focus group, sales and support calls, customer visits and ride-alongs, and co-creation labs, and participate in customer events like advisory board meetings and industry conferences.

Link employee culture to customer outcomes. The adage “You can’t manage what you don’t measure” applies to customer centricity, too. Managers will be motivated and equipped to cultivate a customer-centric culture if they know if and how it impacts results, so organizations should ensure they establish and track the link between culture and customer impact. According to Diane Gherson, head of HR at IBM, employee engagement drives two-thirds of her company’s client experience scores. That proves what Gherson and her team knew intuitively: If employees feel good about IBM, clients do, too.

Temkin Group, a customer experience consulting firm, has developed a model that estimates the impact of customer experience improvements on revenue in different industries. On average, Temkin calculates, a typical $1 billion company can gain $775 million over three years through modest improvements such as reducing customer wait times or making a transaction easier for the customer.

Tie compensation to the customer. Organizations should reinforce a customer-centric culture through their compensation program. Donna Morris at Adobe calls this “giving every employee skin in the game.” She says that for employees to know that customer-oriented attitudes and behaviors are expected from them, there has to be “an element of risk” to it.

So Adobe implemented a compensation program tying every employee to the customer. The short-term cash incentive plan reflects the company’s revenue performance as well as customer success measures such as retention. The program not only makes tangible the contributions to the customer that every employee makes but also produces organization-wide alignment because everyone is working toward the same goals.

Company leaders are starting to recognize that culture and strategy go hand in hand. Only when customer-centric strategies are supported and advanced by culture will a company realize its customer-centric vision.

Making Great Decisions

From the Women at Work podcast:

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There’s a lot that goes into making a good decision at work: figuring out priorities, coming up with options, analyzing those — and several steps later, planning for what to do if you’re wrong. If you’re a woman, you are also factoring in how your colleagues expect you to ask for their opinions so you can create consensus. And if you do, they’re still likely to see you as indecisive and lacking vision.

We talk with Therese Huston, author of the book How Women Decide, about our strengths as decision makers and how to work around double standards when we’re making decisions and communicating them to our team.

Guest:

Therese Huston is the author of How Women Decide: What’s True, What’s Not, and What Strategies Spark the Best Choices.

Resources:

“Research: We Are Way Harder on Female Leaders Who Make Bad Calls,” by Therese Huston
“Women and the Vision Thing,” by Herminia Ibarra and Otilia Obodaru
“Why Do So Many Incompetent Men Become Leaders?” by Tomas Chamorro-Premuzic
“Get Excited: Reappraising Pre-Performance Anxiety as Excitement,” by Alison Wood Brooks

Email us here: womenatwork@hbr.org

Our theme music is Matt Hill’s “City In Motion,” provided by Audio Network.

Fixing the Gender Imbalance in Health Care Leadership

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Female physicians continue to face myriad challenges in medicine ranging from implicit bias to gaps in payment and promotion to sexual harassment. So it is not surprising (though it’s still appalling) that although equal numbers of men and women now graduate from medical school, only a small fraction of female physicians become medical leaders. Currently in the US, only 3% of healthcare CEOs are women, 6% are department chairs, 9% are division chiefs, and 3% are serving as chief medical officers. This is despite women comprising 80% of the healthcare workforce and evidence that having women in upper management and on corporate boards is associated with improved financial performance and enhanced accountability.

These numbers point to a clear need for better representation of female physicians in leadership. How exactly to achieve this given the many barriers they face is less clear. Yet bright spots have emerged, both in healthcare and in other industries asking themselves a similar question. They highlight four priority areas for organizations seeking to systematically improve the promotion of women.

1. Quantification

Before they can make progress, healthcare organizations need to see how well (or poorly) women are represented among their leadership. They’ll also benefit from understanding female physicians’ experiences in the workplace, and how those compare to those of their male counterparts. Quantification is a key facilitator of change in addressing gender imbalance. A powerful example of this can be seen in the United Kingdom’s Athena Swan Charter and Awards. The Charter recognizes commitment to advancement of women in higher education and research. Depending on how well they meet the Charter’s requirements, institutions are eligible for Bronze, Silver, or Gold Awards. As of 2011, organizations must have received at least Silver Awards to qualify for National Institute for Health Research Funding. Evaluation thus far suggests that the Charter has increased awareness of gender and other diversity issues, created numerical and financial incentives for change, and catalyzed structural and cultural changes, such as increased career support for female researchers.

2. Re-thinking awards and promotions

Women physicians lag their male colleagues in the rates at which they receive major awards or recognitions. This obviously has an impact on promotions. Systematization can ensure that male and female faculty’s achievements are equitably recognized. Recent work from Brigham and Women’s Hospital highlights that gender gaps in recognition emerge early in female physicians’ careers, but that systematic identification and publicity of their accomplishments can narrow gender-based gaps. This lesson can be applied more broadly, including to systematizing search processes, appointment of physicians to committees, and nomination for leadership roles and increased responsibility.

Insight Center



The Future of Health Care
Sponsored by Medtronic

Creating better outcomes at reduced cost.

For many decades, medicine has valued and preferentially promoted clinicians who also conducted biomedical research. As the career paths available in medicine have broadened, the career profiles of those who get promoted have not commensurately expanded. Continuing to prioritize clinician-researchers for promotion can disadvantage certain groups (among them female physicians, who are more likely to choose careers as clinician-educators) and doesn’t necessarily align with the skills needed for modern healthcare system leadership. Several institutions have begun promoting for accomplishment in less traditional career paths in which women may be over-represented. For example, Duke has promotion tracks specifically for faculty with clinical service and educational focuses to their careers, providing tenure-track guidelines for advancement from assistant all the way to full professor. Similarly, the Dana Farber Cancer Institute each year names those among its most accomplished clinical faculty as Senior and Institute Physicians, recognizing clinical prowess that is often not acknowledged in a traditional, academics-focused institution.

3. Engaging broadly

Men and women alike should work to enhance gender diversity in leadership. There is substantial data on the pervasiveness of implicit bias and gender-based microaggressions in STEM fields in general, and medicine in particular. Implicit bias training has been shown to decrease negative, implicitly held beliefs and attitudes about women’s capabilities in STEM. Engaging men alongside women in efforts to reduce bias has proven powerful. At Dell, for example, the Men Advocating Real Change program engages men as key allies in driving gender equity. Targeted at the largely-male executive leadership, the program is run by the nonprofit Catalyst and covers topics such as privilege, unconscious bias, dominant culture, and gender role conditioning and its link to leadership. Anecdotal feedback suggests the program is having a positive effect on Dell’s ability to recruit, retain, and promote women and on the gender balance in male dominated divisions such as sales, for example, although the gender imbalance in leadership generally still persists.

4. Creating opportunities for development and sponsorship

A final lesson from the technology industry suggests that support for women’s advancement must go beyond networking and forums towards true sponsorship and career advancement opportunities. Both male and female leaders should take on sponsorship roles to promote high-potential women’s access to diverse opportunities, and to avoid the common problem of female leaders becoming overburdened with mentee requests. IBM’s Technical Women Pipeline Program is a good example. Established in 2010, it engages mid and senior-level women identified as strong leadership candidates in a two-day program aimed at boosting their careers. The women are paired with executive advocates with whom they work on development plans and check in on a quarterly basis after initial face-to-face meetings. Women also join quarterly, international calls with others in the Pipeline Program community. The program has improved retention rates for mid- and senior-level technical women and increased the number of women considered distinguished engineers.

Given the value placed on data and evidence in medicine, the impact of these interventions will be further increased by rigorous study of their effects. In the meantime, they provide valuable starting points for a problem affecting not just female physicians, but the health and performance of the systems they work in.

How Blockchain Can Help Marketers Build Better Relationships with Their Customers

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Blockchain has important implications for marketing and advertising. But according to The CMO Survey, only 8% of firms rate the use of blockchain in marketing as moderately or very important.

Blockchain technology is not well understood and subject to a lot of hype. This combination creates a natural barrier to entry and has likely caused marketers to take a “wait and see” approach. However, there are many reasons to invest the time now to understand the technology and begin exploring specific marketing applications for your industry. Like digital platforms, social media, martech, fintech, and numerous other innovations, the spoils of blockchain may go to early adopters who commit to ruthless innovation.

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Blockchain’s properties — transparency, immutability, and security — make it reliable and trustworthy for applications such as supply chain management, smart contracts, financial reporting, the Internet of Things, the management of private (e.g., medical) information, and, even, electrical grid management. Meanwhile, its transmission model reduces the costs of transactions, enables verification and efficient exchange of ownership, and opens the door to real-time micropayments. It may make it possible for payment frictions to shrink, intermediaries to fade away, and consumers to own and control their personal information. Here, we see the disruptive potential of blockchain on marketing.

The Marketing Impact of Near-Zero Transaction Costs

Today, financial transactions have considerable costs. Retailers routinely pay credit card companies 3% payment processing fees, while gas stations pay even more. Vendors using eBay and Shopify pay listing and sales fees, and consumers pay transaction fees on payment portals like PayPal. All of these fees increase the cost of goods and are typically passed on to consumers. With the pervasive use of credit cards and debit cards, many merchants have set minimum purchases for their use to avoid having their profitability destroyed by fees.

Blockchain technology allows for near-zero transaction costs—even on microtransactions. Financial corporations like Mastercard and Visa already offer the ability to send money in any local currency over a blockchain rather than by swiping a credit card, taking advantage of the technology’s additional layers of security and transparency. On top of that, being able to cut intermediaries and connect directly the banks of both ends of each transaction can avoid most cross-border fees.

There are implications for marketers and advertisers as well. Today, marketers often try to get access to customer data by paying third-parties (like Facebook) to share information. But blockchain could allow merchants to use micropayments to motivate consumers to share personal information — directly, without going through an intermediary. For example, a grocery store chain with a mobile app can pay users $1 for installing the app in their phones, plus an extra $1 if they allow it to enable location tracking. Every time they open the app and spend at least a minute on it, the retailer can pay them a few cents or loyalty points’ worth of store credit, up to a maximum per day. During that time, they push deals and special offers to the user. Indeed, user-tailored deals open a legitimate mechanism to deliver personalized prices that are a function of the consumer’s profile. This approach has the potential to reduce fraud and minimize inaccurate or incomplete information from customers that currently plague these programs.

In the same way, marketers can enable “smart contracts” (virtual agreements that remove the need for validation, review, or authentication by intermediaries) that users can activate when they subscribe to email newsletters or sign up for a rewards program. Micropayments are deposited directly to the users’ wallets whenever they interact with commercial emails — or with ads, which brings us to our next point.

Ending the Google-Facebook Advertising Duopoly

A similar model could be used with website ads by compensating consumers for each page view. In 2016, HubSpot published a research study showing that a majority of Internet users dislike most forms of pop-ups and mobile ads and see online advertisement as intrusive and negatively disruptive. An increasingly common response is to install ad blockers, a trend that is having a major punitive effect on the industry. By 2020, it is estimated that ad-blocking adoption will cost publishers $35 billion.

Blockchain-enabled technology potentially allows marketers to recapture some of that revenue with a different type of model: marketers pay consumers directly for their attention—and cut out the Google-Facebook layer.

We believe that the Google-Facebook duopoly in digital advertising will soon be threatened by blockchain technology. While keyword-based search will not disappear completely, it will become much less prominent. Eventually, individuals could control their own online profiles and social graphs.

With blockchain technology, companies can bypass today’s social media powerhouses by directly interacting with consumers and can share the reward of ad exposure directly with them. In 2016, Google is reported to have generated an average of $73 per active user via ads. Of course, the $73 is just an average over nearly one billion active users. It is reasonable to expect that Google brings in much more than $1,000 for certain highly-valued demographics. Imagine the marketing possibilities when companies can efficiently transfer these values to consumers via “willingly-consumed” advertising enabled via blockchain technology.

Blockchain technology can also verify ad delivery and consumer engagement; avoid ad or email overserving, which angers consumers and demotivates them from buying; and prevent follow-me ads that are no longer relevant (such as when consumers have already made a purchase of the company’s or competitor’s products).

Ending Marketing Fraud and Spam

Fraud verification via blockchain will also help verify the origin and methodology of marketers. Micropayments will also effectively destroy the current concept of mass phishing spam that dilutes the effectiveness of marketing for everyone.

Some 135 billion spam emails are sent every day, currently accounting for 48% of all emails sent. Spammers receive only one reply for every 12.5 million emails sent. A very small blockchain-enabled payment to the recipient of the email will discourage the spammer by increasing the cost of this activity. It should also help companies identify consumers who are interested in the transaction by their willingness to make this exchange.

Similarly, for the internet, every time a user clicks on a link, there could be a micropayment. In most cases, the user will make a small micropayment (for example, one cent to read a news article). This would defeat the denial of service attacks — a type of cyber-attack that involves recruiting bots to hit a website with millions of requests that causes the website to go down or to provide poor response time.

Blockchain could also make it difficult for bots to set up fake social media accounts, flood users with deceptive messages, and steal online advertising dollars from big brands. Online authenticity is literally baked into the blockchain technology. One company that is tackling the problem of social media fraud is Keybase.io, which enables individuals to use blockchain to demonstrate that they are the rightful owners of their various social media accounts. This will make the impact of marketing easier to track and marketing expenditures easier to justify — both are big wins for the profession.

As of 2016, $7.6B (or 56% of total display ad dollars) were lost to fraudulent or deceptive activity, a number that is expected to grow to $10.9B in the next years. By using blockchain technology to track their ads, marketing teams can retain control over all their automation practices, ensure that marketing spend is focused on ROI-generating activities, and directly measure the impact of marketing down to a per-user, per-mail metric. By tying user behavior and micropayments together, blockchain could solve the attribution problem that has bedeviled marketers for decades.

Remonetizing Media Consumption

Blockchain-enabled editorial content will likely allow companies to enhance quality control and copyright protection. For instance, (the reinvented) Kodak has created KODAKOne, which will feature a digital ledger documenting who owns the rights to individual images, allowing photographers to assert control over their work. Currently, the theft of online content is a pervasive problem and creators have little recourse to recoup lost monies other than expensive lawsuits. In the future, they will automatically and easily receive payments for content usage.

In addition, the average person who creates viral content, such as much-watched videos or social posts, could receive compensation for every click. (Currently, they receive little or no money unless their work is shown on online channels with subscribers.)

In all of these scenarios, content creators are empowered to produce relevant work that is valued proportionally to its success.

Companies like Coupit are getting ready to maximize the impact of that improved content. Its blockchain-based technology allows marketers to become part of loyalty and affiliate programs for opted-in consumers who can trade rewards with each other. Marketers gain visibility and transparency to differentiate between dormant and loyal customers, thereby expanding their strategies to send targeted offers to each group.

Even when a data aggregator or analytics intermediary is necessary, micropayments will allow companies to bypass ad blocking. Individuals will control the amount of personal information they share, will be directly rewarded for ad exposure, and many privacy concerns will be legitimately appeased.

One example of this is Brave, a new web browser created by Brendan Eich, co-founder of the Mozilla project and creator of the JavaScript language. Besides offering new levels of privacy and security, Brave is enabling a blockchain-based system aimed at transforming the relationship between users, advertisers, and content creators. Basic Attention Tokens (BATs) will allow publishers to monetize value-added services and capture some of the growth related to advertising, 73% of which is dominated by Facebook and Google.

Better Results for Companies and for Consumers

As blockchain goes mainstream, all intermediaries will need to adapt their business models. The decision chain will be structurally altered: Individuals will have more control over how they share personal information and how they spend their time interacting with advertisers. Spam and phishing scams will be stopped by their own nature—the more spammers spam, the more unsustainable they become from an economic standpoint. For companies, this could mean higher levels of control over the quality of inbound traffic for all their marketing efforts, as well as a much-needed improved understanding of customers’ behavior.

On the other hand, exposure to advertisement will not be imposed without a transactional payment to each affected individual. Consumers will also have an incentive to post an accurate social profile online – detailing what they are interested in – because they will get paid for it. Marketers will be paying consumers directly – not the social media middle layer. When targeting high value customers, the incentives will be accordingly higher.

Blockchain technology holds the potential for societies to become more trustworthy and empowered, increasing visibility, connecting parties, and rewarding individuals for their contributions to transactions. Marketing and advertising are fundamentally impacted by these changes. Finding ways to design and implement measures to make blockchain-related transformations should be a priority not only for CMOs, but also for all strategic, financial, and technological decision makers. Operationally, companies may be able to build new levels of trust with individuals, and ultimately connect their products and services with consumers in a manner and scale impossible to achieve without blockchain.

Marketing and technology leaders have the potential to leverage blockchain to reinvent their customer relationships. Early action on this far-reaching technology will put companies in the best position to benefit from what we think will be widespread adoption.

Two Powerful Ways Managers Can Curb Implicit Biases

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Many managers want to be more inclusive.  They recognize the value of inclusion and diversity and believe it’s the right thing to aspire to. But they don’t know how to get there.

For the most part, managers are not given the right tools to overcome the challenges posed by implicit biases. The workshops companies invest in typically teach them to constantly check their thoughts for bias. But this demands a lot of cognitive energy, so over time, managers go back to their old habits.

Based on our work at the Stanford Women’s Leadership Lab, helping organizations across many industries become more diverse and inclusive, our research shows there are two, small — but more powerful — ways managers can block bias: First, by closely examining and broadening their definitions of success, and second, by asking what each person adds to their teams, what we call their “additive contribution.”

The problem is that, when hiring, evaluating, or promoting employees, we often measure people against our implicit assumptions of what talent looks like — our hidden “template of success.”  These templates potentially favor one group over others, even if members of each group were equally likely to be successful.

Take, for example, the hiring process. While interviewing a candidate, we might ask her where she went to school or to share her experiences. We genuinely believe we are gathering relevant information that will help us decide objectively whether the person is a good fit for the job. But, in fact, we are likely measuring that person against our hidden “template.” Did the person go to the “right” school? Are her experiences similar to ours?  Is her personality a close match with that of the other employees on the team?

Not surprisingly, most managers end up hiring people who match their implicit template of success. Now, this approach may seem like a recipe for sound decision-making. Wouldn’t those people work best with the hiring manager and fit in with the rest of the team? Perhaps.

But this approach can pose a serious problem: Even if we want to be inclusive, the template itself may inadvertently invite bias by giving preference to more traditional candidates or “the safe bet.” In finance, for example, that might mean believing — based on no evidence — that only MBA graduates from an elite university are likely to succeed at their jobs. Even if we apply that criteria fairly to every candidate, it can lead to an implicit preference for hiring white males. After all, 60 to 70% of graduates of elite MBA programs are male — and very few are people of color.

Take another example: In positions that demand skills for working in an open-source context, our hidden template of success might lead us to believe, again with no evidence, that only someone who is already part of the open-source community can do the job well. This narrow definition, however, will result in the same kind of candidate being picked over and over. Those who volunteer in the open-source community often do so outside and beyond their paid “day” job hours, which pretty much excludes people with care-giving roles and other responsibilities outside of work. As a result, open-source communities are typically 3 to 5% women and mostly younger men. You can see how replicating the template of success can quickly translate into sameness.  And sameness blocks performance and innovation.

Diversity, on the other hand, spurs innovation. In research spanning decades, Columbia professor Katherine Phillips has repeatedly found that, when tasked to innovate, teams that include diverse members and that value the contributions of all their members outperform homogenous teams. When working across difference, Phillips finds that team members work harder. They have to in order to communicate and to reach consensus with others who may not share the same experiences or perspectives. This makes all members of the team think more deeply and arrive at better decisions. Diversity, as Phillips writes, “makes us smarter.”

The Power of Additive Contribution

To block our implicit biases, we need to challenge the assumptions behind our templates for success. We need to ask if the criteria used to evaluate candidates will lead us to choose employees who will add to our team success or simply replicate the status quo. For example, is an MBA from a top business school really necessary to be successful in this position? It may be, or maybe we’re privileging some criteria without evidence that they are necessary for success. We need to ask questions that help us determine how a person adds to the portfolio of experiences and skills across our entire team.

Focusing on additive contribution, a term we developed in a collaboration with Alix Hughes, diversity program leader at Amazon, is a powerful way to avoid sameness in a team and to foster inclusion and innovation. When we consider other’s additive contributions, we open the door to people who might not traditionally match our implicit template of success, that are not like “us.” We make our teams more diverse and more successful.

So how can you ask questions that help you determine someone’s additive contribution?  Here are four ways:

Clarify ambiguous criteria for success. First ask, “What are my hidden ‘preferences?’” Then challenge your hidden preferences by asking what are the mindsets, skills, and diverse experiences that actually lead your team to success. This may make you more effective at hiring people who will thrive in your organization. Instead of asking about prior open-source experience, for example, you might seek someone who can discuss critical points effectively and respectfully in an environment of open debate.

Focus on a person’s value to your team. Ask, “How does this person’s approach help us get to better discussions and decisions?” or “Does this person help me see outside my ‘box’?” Professor Mary Murphy, an expert on growth mindsets in organizations, offered this question: “How can [or does] this person add to the total value (composition) of our team?” By asking questions like these, you are more likely to move beyond your hidden template of success and avoid any implicit bias that might come along with it.

Run a gap analysis. Ask, “What skills and experiences am I missing on my team that this person has?” Be careful not to focus on one-dimensional characteristics. For example, don’t determine you need “a woman to round out the team.” Diversity for diversity’s sake often leads others to make negative assumptions about your people decisions — and about those you hire or promote. Criteria still matter. Instead, look at how people can add to the total portfolio of mindsets, skills, and experiences on the team.

Consider their journey. Ask, “What has this person learned from her experiences? Can she take risks and persevere through difficulties?” We often perceive being quickly promoted as an indicator of someone’s talent. But using this criteria might lead you to overlook the value of grit and perseverance. If a person took a risk and it did not pay off, for example, they may have learned more than a person who took a safer path. The lessons people learn throughout their careers are often the key to uncovering their additive contribution.

Small Wins, Big Payoff

In 2016 Anton Hanebrink, Intuit’s Chief Corporate Strategy and Development Officer, took over a high-performing team known for its contributions to the direction of the company. The team’s historical approach to finding top talent had been simple — target graduates of top universities and MBA programs with experience at leading management consulting firms or investment banks. While these filters simplified the screening process, they also led to a relatively homogenous way of viewing the world.

Seeking to find a better way he pushed his team to broaden how they thought about top talent. The breakthrough for Anton and his team came during an offsite we facilitated for the company on implicit biases in criteria, such as only hiring people from elite universities. The company’s CFO asked a crowd of the company’s most accomplished finance leaders to raise their hand if they had attended an Ivy League school. Hardly anyone raised their hand.

Seizing on the moment, Anton pushed his team to examine this historical criterion more closely. His team discovered it was not an effective marker of how well the person would perform in the organization. It was, indeed, just a hidden preference. In reality, many of the top performers at Intuit, including the CEO and CFO, did not hold degrees from an Ivy League school.

Energized by Anton’s charge, the team worked together to define the skills, experiences, and mindsets that actually were necessary to succeed in the team. They identified the abilities to structure ambiguous problems, influence change at senior levels, and to effectively develop team members as the key contributions an incoming executive should add to the team. None of these abilities would be guaranteed by a credential earned sometimes decades ago.

After reconsidering their template of success, the team’s approach to hiring changed significantly. They especially improved how they interviewed candidates, engaging them more deeply and thoughtfully on the core skills of the job than they had in the past. They even went so far as redact the names of schools and prior employers during the interview process.

As a result, the team hired top talent whose diverse backgrounds have added to their total portfolio of skills. Anton’s team achieved more gender and racial diversity as well. By redefining success, a greater diversity of people were able to be seen for their leadership. The breadth of talent has led to a more rigorous debate of ideas and enabled the team to navigate new business opportunities and identify critical strategic insights they would have missed with their old approach to recruiting talent.

That’s the power of reexamining our assumptions and considering people’s additive contributions. They constitute small changes on our part, but the payoff is significant.

Why Agile Goes Awry — and How to Fix It

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In the spirit of becoming more adaptive, organizations have rushed to implement Agile software development. But many have done so in a way that actually makes them less agile. These companies have become agile in name only, as the process they’ve put in place often ends up hurting engineering motivation and productivity.

Agile software development

Frameworks for adaptive software development like Agile, have been around for a long time, and have manifested in many forms. But at the heart of most of these models are two things: forming hypotheses (e.g., what is a feature supposed to accomplish) and collaborating across domains of expertise on experiments, all in the spirit of driving learning and not careening down a path that proves to be incorrect.

When Agile software development was born in 2001, it articulated a set of four critical principles to elevate the craft of software development and improve engineering and product manager motivation.

Individuals and interactions over processes and tools
Working software over comprehensive documentation
Customer collaboration over contract negotiation
Responding to change over following a plan

Over the last three years, in our research on human motivation, we have analyzed the practices of engineers across over 500 different organizations using a combination of survey-based and experimental approaches. We’ve found that what happens in practice wildly departs from these stated principles.

For example, in common practice, processes and tools have become the driver of work, not individuals and interactions. In one large Fortune 100 company, the head of digital products said to us, “we’re not allowed to question the Agile process.” In another Fortune 500 organization, product managers and engineers communicate exclusively through their tools, which are used primarily for the former to issue commands to the latter.

Similarly, documentation often trumps working software. In one large tech company, their product team focused significant upfront time writing small requirements (called “user stories”). These requirements were put into a ticket queue as tasks for the next available engineer to start working on. The bar for documentation to keep the queue moving became high. Ultimately, this process became one of many small “waterfalls,” where work is passed from a product department to designers to engineering. This process is exactly what Agile was meant to eliminate. It is no wonder that the CTO of this company said, “my engineers feel like short order cooks in the back of a diner.”

When it comes to “responding to change over following a plan,” this often gets misinterpreted to mean “don’t have a plan.” For example, in one fast growing tech company, the Agile teams did not try to understand the broader strategy of the organization. As a result, their attempts to iterate often focused on low-value or strategically unimportant features.  Without a plan, teams won’t know how to prioritize actions, and how to invest in those actions responsibly. This principle has gone so far as to let engineers believe that it is not appropriate to have timeboxes or common milestones.

It would be one thing if these misapplications actually improved engineering motivation and performance, but we have found that in practice, the opposite happens. Agile, when practiced as described above, reduces the total motivation of engineers. Because they’re not allowed to experiment, manage their own work, and connect with customers, they feel little sense of play, potential, and purpose; instead they feel  emotional and economic pressure to succeed, or inertia. They stop adapting, learning, and putting their best efforts into their work.

For example, one venture capital partner shared with us a story of how a video game development company continued to build a product for a year, despite every engineer feeling like the game was not worth playing. The company realized they wasted a lot of time and money.

Agile processes go awry, because as companies strive for high performance, they either become too tactical (focusing too much on process and micromanagement) or too adaptive (avoiding long-term goals, timelines, or cross-functional collaboration).

The key is balancing both tactical and adaptive performance. Whether you’re an engineer or product manager, here are a few changes to consider to find this balance, so you can  improve your engineering (or any) team’s motivation and performance.

1. Software development should be a no-handoff, collaborative process.

Rather than a process where one person writes requirements (even small ones) while another executes them, all without a guiding strategic north-star, a team striving for true agility should have a no-handoff process versus a process where one person writes requirements while the other executes them. In a no-handoff process, the product manager and the engineers (and any other stakeholders) are collaborative partners from beginning to end in designing a feature.

First the team, including executives, should articulate the team’s strategic “challenges.” Challenges take the form of a question, always focused on improving some kind of customer outcome or impact. Think of them as a team’s detailed mission in question-form to trigger expansive thinking. The challenges themselves are developed and iterated by the whole team, including its executive sponsors (and customers). Every single person on the team (or any team for that matter) is asked to contribute ideas to each challenge whenever they want.

For example, in one bank, a challenge was, “how can we help customers be better prepared for possible financial shocks?”  Another was, “how can we make it more fun and less of a chore for customers to maintain healthy financial habits?” These challenges produced dozens of ideas from many different people.

Then, instead of someone writing requirements while another person executes, these teams develop and mature an idea collaboratively, from rough draft to testable hypothesis.

2. The team’s unit of delivery should be minimally viable experiments.

Teams often find they waste time by adapting too much. To avoid this, not only should ideas be formed for a strategic challenge, but they should also be executed with fast experiments aimed at learning just enough to know what works for customers. In other words, they should be maximizing their “speed to truth.”

In order to reduce wasted effort and increase the team’s decision rights, experiments should be short in nature. If possible, an experiment should be no longer than a week.

Sometimes this requires the team to minimize a feature to what is absolutely needed to test its weakest assumption. Sometimes it means that the team doesn’t code but instead completes an “offline” experiment through research.

3. The team’s approach should be customer-centric.

The process of building software (even internal-use software) should be squarely customer-centric.

At the simplest, these principles should hold:

“Challenges” are always framed around customer impact.
Problem solving meetings always start with a customer update, and representatives from the frontline are included frequently in these discussions.
Every experiment is built around a customer-centric hypothesis. That way, the team can hold themselves accountable to the outcome predicted by the experiment.

However, even more important is that engineers see with their own eyes how customers use their products. This requires the frontline and the engineers working together to see if the product is creating customer impact.

4. Use timeboxes to focus experimentation and avoid waste.

Interestingly, adaptive software development encourages timeboxes as a way to ensure an experiment is given the investment that is justified and to signal the acceptable quality level of given feature. On the other hand, typical Agile practitioners avoid timeboxes or deadlines, for fear that the deadline will be used to create emotional pressure. One of the worst feelings for a software developer is spending a few months working on something that ends up being not useful. This fills you with emotional pressure (“I let everyone down”) and a sense of inertia (“why am I even doing this?”).

To avoid this outcome, you want to be clear on how far an engineer should go before they check to see if the direction is still correct. The greater the uncertainty on a team’s hypothesis, and the greater the risk, the shorter that runway should be. With that in mind, the timebox isn’t a deadline. It is a constraint that should guide the level of depth and quality for an experiment before a real test. In this way, timeboxes can increase total motivation.

5. The team should be organized to emphasize collaboration.

To make sure you end up with a no-handoff process, the various stakeholders involved should function as a single cross-functional team, also known as a pod. The goal of the pod is to drive collaboration. Each pod should contain the full set of experts needed to deliver a great product. This may include senior executives. In one organization, for example product pods include a product manager, front-end engineer, back-end engineer, designer, a quality engineer, and part-time representation from customer service, and a senior executive from a control function.

In many organizations, there are tell-tale signs of “faux pods” — teams that call themselves pods but don’t actually operate that way. Signs of faux pods include:

Experts are in separate “aligned” teams, not the same team. For example, a product team has dedicated engineering “sprint teams.” These are not pods.
The team uses tools that prevent real collaboration. For example, while asking one engineering team why they chose the Agile software tools they are using, they said, “these tools will prevent executives from engaging in our work.” All this does is perpetuate a cycle of mistrust.
Engineering and Product functions actually have different goals from the top. Executives in both functions use their hierarchical power to get their people to prioritize the function’s goals above all others, including their pod’s goals. These conflicts ultimately result in clashes in the working teams that prevent true teamwork.
Rigidly hierarchical talent processes, like performance ratings, hierarchical titles, pressure to get promoted, and up-or-out systems destroy the teamwork required to make pods function well. These systems will either make team members more beholden to their boss than their team’s customer or they will put team members in competition with each other. Either way they will not function as a team.

Put differently, the stronger an organization’s silos, the more people will solve for the needs of their silo, versus the needs of their team. This makes collaboration and consensus very difficult to achieve without constant escalation.

6. The team should constantly question their process.

A famous maxim of engineering design is known as Conway’s Law. It states: any organization that designs a system will produce a design whose structure is a copy of the organization’s communication (i.e., process) structure. In other words, if you’re a monolithic organization, you’ll produce monolithic designs. If you’re organized by user segments, your product will optimize for that structure.

If you want to defeat Conway’s Law, the better practice is to constantly adjust your structure and processes to suit the problem at hand. This requires teams that have simple, lightweight processes and structures that they constantly question and tweak.

Thus, rather than building “Agile” as a religion that cannot be questioned, engineering teams should be in the habit of constantly diagnosing and iterating their own team’s operating model. In the best examples we’ve seen, on a monthly basis, teams diagnose their operating model and decide if it needs changing to produce a better product.

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The ability to attract, inspire, and retain digital product talent is becoming mission critical for organizations. Most organizations have fallen prey to a simple message — implement Agile as a series of ceremonies and everything gets better. Unfortunately, this is often not the case when the human-side of the equation is lost. By getting back to the basics of motivation and adaptive performance, you can build an organization that is truly agile.

To Get Employees to Empathize with Customers, Make Them Think Like Customers

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We all know how important it is for an organization’s leaders and employees to empathize with its customers. Evidence shows that when people understand and care about those they serve, they solve problems more creatively and provide better service.

What’s the best way to cultivate empathy? The standard answer is to spend more time with customers. For example, leaders at IBM, Medtronic, and Microsoft have sent their people out to meet customers and see their products in use. But recently at IDEO, we’ve been encouraging companies to go a step further. Instead of just getting to know the customer, we want employees to become the customer.

The idea is to create an embodied experience for employees, rather than just a conversation. People learn much more when they are physically engaged in an activity, not just talking about it. But you can’t just take employees through the actual customer experience. They already know it like the back of their hands; it’s too easy for them to get defensive and justify the way they already do things.

Instead, we bring people into different contexts — removed from typical day-to-day company operations — that can serve as a metaphor for what customers experience and therefore jolt employees into a more empathetic stance.

Take our work with Consumers Energy in Michigan. The company had noticed that low-income customers weren’t paying utility bills — even in the middle of the frigid Midwest winter. When they asked us to help them figure out why, we spent time with Consumers Energy users in Flint and quickly saw that the billing process was too opaque, with too many unexpected charges. We could have simply reported this to the company’s executive team, or brought them in to have the same discussions we’d had. But we decided our message would have more impact if we gave them a taste of the customer experience.

When they arrived for one milestone meeting, we greeted them in the lobby, gave each person a handful of Goldfish crackers and told them to make a simple choice: either take the stairs or the elevator to the seventh floor. Those who rode the elevator were charged three goldfish at the top, while those who took the stairs didn’t have to pay anything. Throughout the day, we laid on more choices with unexpected “charges.” By lunch time, one team member didn’t have enough Goldfish to “pay” for his food. And when we charged people to pay to sit down at a meeting, another team member had to borrow Goldfish to get a chair.

At the end of the day, the group had a richer understanding of how difficult it would be for people with limited resources to maneuver through their system. This empathy experience galvanized them to create an innovative pilot billing program called Clear Control, which features bi-weekly billing periods, daily text updates on usage and bill amounts, and personalized home audits for efficiency.

Another example comes from Carnival Cruise Line. The company wanted to reimagine its vacation planning and booking process, which had been especially painful for rookie cruise-goers and those managing group reservations. To bring the guest’s perspective on the problem to life, we brainstormed stories where we saw similar challenges and landed on a familiar but challenging journey with a group of characters, conflicts, and confusing rules: The Wizard of Oz. If her dream destination is to get home to Kansas, then Dorothy has to book it like a cruise.

We created a game with another token-based payment system, and employee characters as Dorothy had to advance through four stations aligned with stages of the Carnival booking process. About two dozen sales and service agents, managers, and execs participated — alternately laughing or complaining, shouting with impatience or cheering in victory. As in all our empathy exercises, we ended with a team debriefing. The team sat in a circle and talked about what had been fun and what had been frustrating. We then dove deeper into a discussion around the roles, rules, similarities to their work, and what they wanted to do to improve the guest experience. Doing this with cross-functional groups across different levels in the organization makes it easier for everyone to speak up, spot opportunities, and make collective change across silos. Carnival has since piloted a new team-based call center structure to create a more unified experience for guests and invested in a new digital dashboard for agents, which visually tracks each customer’s journey. Early signs have been positive, with increases in sales conversion and first call resolution.

It takes time and energy to design these experiences, and they can be messy in practice. But we’ve found them to be a powerful way to ensure that the people in your organization truly understand their customers. Here’s how to do it.

Step 1: Gather insights. What is broken, frustrating, surprising, or uncomfortable for your customer?

Step 2: Get outside. What industry, experience, or story has similar themes and problems? Generate a range of options and pick the one that resonates.

Step 3: Get creative. Make, build, simulate, act-out, and play through the overlapping moments of your real business problem and the analogous experience that you have identified. What is the minimum viable experience that connects the two for people? Design that.

Step 4: Invite a group of people to go through the exercise and to talk about it. Usually, the actual experience is no more than an hour or two — that’s long enough for people to go through a wide range of emotions — and then we leave at least half an hour to unpack how people felt and what they noticed. The goal is for everyone to walk away with new ideas and discrete actions to take, and a plan for communicating their insights to the rest of the organization.

It’s often said that necessity is the mother of invention. Sometimes we generate ideas to address our own needs. But in many cases, it’s the necessity of others that drives us to innovate. Empathy isn’t optional in problem-solving. It can drive creative breakthroughs.