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When an Educated Guess Beats Data Analysis



Research on data provided by 122 companies in the advertising, digital, publishing, and software sectors (industries characterized by uncertainty over outcomes) suggests that data driven decision-making could be counter-productive under conditions of uncertainty. Heuristics and gut feelings often offered a better tradeoff in terms of decision-making speed and accuracy; the inclusion of analysis in the decision-making process did not bring about any meaningful improvement in accuracy while significantly reducing speed.

Data-driven decision making is often viewed as the gold standard in modern management. And this is for good reason. The explosion of available data and rapid advances in data science enable managers to know substantially more about their business. This knowledge, if used well, should bring about better decision-making on about every aspect of the business.

This is perhaps why most companies are in a horse race in building analytical capabilities to make the most of this unprecedented abundance of data. For example, a recent survey of Fortune 1000 companies shows that 91.9% of firms report increasing investment in data initiatives.

While the potential of big data is irrefutable, is it the panacea for all decision-making situations? Put differently, could a strong emphasis on data and analysis backfire under some circumstances? We explored this in our recent research.

Our intuition was that data-driven decision making could be counterproductive under extreme uncertainty. In such cases, it will be highly challenging and sometimes impossible to collect reliable data. This could explain why 12 publishers were unable to see the potential of Harry Potter and the Philosopher Stone before Bloomsbury Publishing accepted to publish an initial print run of 500 copies. The book was so innovative that there was by definition no prior data available to accurately assess its potential.

To test our intuition, we collected data from 122 companies in creative industries (in advertising, digital, publishing, and software sectors) about their latest innovation projects. We chose creative industries due to high levels of uncertainty about customer reactions and an infinite variety of potential new products and product modifications. For the same reason, we focused on innovation screening decisions — the decision to select what innovation projects to pursue for development. These decisions are characterized by high uncertainty; managers often lack sufficient past data that would enable them to predict customer reactions accurately, market potential, feasibility, and risks. Even if they had such data, it would often be extremely difficult and sometimes even misleading to extrapolate.

We asked managers in these companies to think about their most recent innovation project for which they needed to make a screening decision and included questions to understand how they made this decision. Specifically, the questions addressed the extent to which they relied on analysis (i.e., choosing the option that proved best based upon analyzing the data), instinct (i.e., choosing the option following their instincts), and a range of well-known heuristics (i.e., practical strategies to make decisions faster and more frugally). These heuristics included “tallying” (choosing the option with highest number of favorable points), “experience” (choosing the option most experienced person in team wanted) and “majority” (choosing the option most people wanted) amongst several others. Next, we asked managers to indicate whether they think they got the decision right (perceived decision-making accuracy) and how fast they were in making the decision (perceived decision-making speed).

The results first showed, to our surprise, despite the huge interest in big data, that the managers in our sample did not rely on analysis any more than on their instincts or some of the simple heuristics. The most commonly used heuristic, more than both analysis and instinct, was tallying.

We also find that relying on analysis is not necessarily the ideal way to choose between innovation projects. While the decisions based on data analysis brought about a good level of decision-making accuracy, the process was slow. Managers who relied on their instincts together with some simple heuristics made decisions that were just as accurate but were undertaken much more quickly. That is, heuristics and gut feelings offered a better tradeoff in terms of decision-making speed and accuracy; the inclusion of analysis in the decision-making process did not bring about any meaningful improvement in accuracy while significantly reducing speed.

One note of caution for managers who consider embarking on gut-based innovation decisions: the effectiveness of their intuition might rely on prior experience. Prior research suggests that the effectiveness of intuition compared to analysis is contingent upon domain knowledge; experts in a domain are more likely to make better gut decisions. Managers with limited domain expertise might therefore be better off by refraining from extensive reliance on intuition. Our results suggest relying mainly on heuristic also presents a viable alternative.

The next time when you face a managerial decision that is ambiguous, bear in mind that data might not be the only basis for a choice. Following your instincts, together with some simple heuristics, can lead to quicker and potentially as accurate decisions especially for those with the requisite expertise.


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Managing people

Organizations Need a Dynamic Approach to Teaching People New Skills



As employees and organizations adapt to hybrid work norms, emerging technologies, and general business disruptions, the skills needed to succeed in today’s work environment are shifting rapidly. According to a Gartner analysis of more than 7.5 million job postings, in 2018, U.S. job postings in IT, finance, and sales roles required an average of 17 skills. The same types of roles now require an average of 21 skills, including at least eight that weren’t previously required. At the same time, 29% of the skills from an average job posting in 2018 may not be needed next year.

This poses a major challenge for organizations, particularly in today’s war for talent. Organizations are struggling to find a way to keep up with changing skills, but they can’t rely solely on hiring strategies to meet their needs. Instead, organizations must find or develop the skills they need within their existing workforces.

To better understand how organizations are managing their shifting skills needs, we surveyed 6,500 employees, as well as 75 HR leaders. Except where indicated, our findings come from these 2020 surveys. Our analysis revealed that most organizations used one of two approaches to ensure employees have the skills the business needs when it needs them:

  • Reactive — Unfortunately, many organizations find themselves taking a reactive approach, scrambling to build new skills as needs arise. One HR leader from a large manufacturing organization shared the challenge of trying to keep up with requests from the business to develop new skills: “When we put together a learning solution, the business has already moved on.” In organizations with a reactive approach, employees apply only 54% of the new skills they learn after 12 months. These organizations are simply too slow to get the skills to employees at the times they’re needed most.
  • Predictive — On the other side, more than 50% of HR leaders think the solution is to get ahead by predicting the business’ future skills needs. Without a crystal ball, attempts at predicting future skills are more likely to lead to misplaced investments in wasted training or outdated skills. Our research finds that trying to predict skills is worse than reacting: Employees apply only 37% of the new skills they learn at organizations with a predictive approach — significantly less than the reactive approach.

Rather than making big investments in predictive approaches that may not work or resorting to a reactive approach, our research reveals a third option: the dynamic approach. This strategy casts skills management as a dynamic exercise that embraces ambiguity, makes peace with imperfection, and frees up HR, managers, and employees to move fast in responding to the things they know and can anticipate. In our current work environment, where employees are constantly seeking increased transparency, personalization, and choice, the dynamic approach empowers them with more information so that they can make the right choices to build the skills they need to stay current in their desired roles. Employees at organizations that use a dynamic skills approach apply 75% of the new skills they learn — double the new skills application realized with the predictive approach.

Here are three steps organizations can take to adopt a dynamic approach to skilling and reskilling employees.

Identify Changing Skills Needs

Most organizations today rely on managers and leaders to identify skills needs and HR to implement solutions. When leaders recognize that employees are missing essential skills, the assumption is that HR can help them develop them. More specifically, over 75% of HR leaders report that leaders within the learning and development subfunction are primarily responsible for skills at their organizations. But leaders outside of HR don’t always know the talent implications of business goals, which can result in identifying the wrong skills gaps or overlooking important needs.

To spot and close skills gaps as they arise, regularly bring together input from employees, leaders, and customers by facilitating a network of stakeholders who can report on the specific skills needs in their areas. Together, these skills-sensing networks are able to monitor changing needs and ensure employees are prepared.

For example, Lloyds Banking Group, a financial services company headquartered in London and a Gartner client, takes an iterative approach to mapping skills needs. HR facilitates collaboration among a network of skills stakeholders that include business leaders, partners from each business unit, and HR specialists. This collaboration helps them quickly identify not only skills gaps, but also local and enterprise-wide actions to close them. The stakeholders meet regularly to review a skills dashboard that contains information about employees’ existing skills and the talent interventions planned to meet the skills needs of the business. They check for progress against the agreed-on interventions and escalate any changes that are likely to impact the enterprise-wide skills strategy. Through this approach, Lloyds is able to make data-backed decisions that ensure local and enterprise-wide skills needs are met.

Jumpstart Skills Development

Many organizations respond to today’s rapidly evolving skills needs by providing more formal training. Unfortunately, according to Gartner’s 2018 Shifting Skills Survey of more than 7,000 employees worldwide, there is no significant relationship between the time employees spend in formal virtual or classroom training and the percentage of skills they use. While thoughtful, formal training still has its place, for many in-demand skills, it’s just too slow. All too often, by the time the training is created and delivered, the need has changed.

These quickly evolving skills needs require new, faster solutions — what Gartner calls “skills accelerators.” Skills accelerators leverage existing resources and expertise to enable upskilling support that’s “good enough” to meet skills needs in a timely way. Enacting a sufficient solution in time is better than implementing a perfected training solution too late. In practice, this can look like:

  • Identifying skills adjacencies — Building shortcuts to in-demand skills by identifying adjacent, stepping-stone skills from skills employees already have.
  • Training “skills disseminators” to coach peers — Upskilling a select cohort of motivated and influential employees and then having them coach their peers on new skills as the need arises.
  • Delivering learning to employees when they need it most — Using data to identify and tailor learning delivery to the moments when skills needs arise in the business.

Identifying skills adjacencies can help business leaders tap into a broader and more diverse pool of employees and candidates who can get up to speed quickly. For instance, your organization may need an employee skilled in Python, a general-purpose programming language. Instead of limiting recruitment or internal searches to employees with knowledge of Python, a hiring manager should also consider candidates with closely related skills, such as Linux, Java, or Perl. Having one of these adjacent skills generally makes it easier for an employee to upskill — even through self-directed or on-the-job learning — in the desired area.

The figure below shows the skills adjacencies for Python. Closely related skills like Java are part of an overall network of complementary skills that people with the Python skill usually have or can develop quickly. Tertiary skills, like other scripting languages, are related to Python but one more step removed.

One large manufacturing organization we interviewed took this approach by thinking broadly about the backgrounds of current employees most likely to be able to develop data science skills. Instead of competing to hire experienced data scientists, they invested in developing these skills among employees with backgrounds in adjacent areas like mathematics, statistics, and business analysis.

Delivering learning to employees at the right times is another skills accelerator. Recognizing that time of learning and application were disconnected, one of Gartner’s clients, CVS Health, a healthcare company that owns the CVS retail chain, focused on aligning learning delivery with moments of employee and business need. HR leaders realized that inputs from business leaders aren’t always sufficient or timely enough to identify when new skills and learning are needed most. They use data from a variety of sources to identify:

  • Moments in which employees need to apply new skills and can benefit most from learning (such as tenure milestones and promotions).
  • Opportunities to build skills to support the business during high-demand moments (such as flu season).
  • Real-time productivity or on-the-job performance data that HR accesses directly from the various business systems to trigger training, reskilling, or upskilling on a regular basis.

Foster Transparency Between Employees and the Organization

Ensuring both the organization and employees are moving in the same direction is key to developing skills dynamically. While many leaders and managers try to motivate employees to engage in continuous learning by fostering a learning mindset, most employees are already motivated. In fact, 97% of employees report that they would learn a new skill if given the opportunity. Yet only 39% percent believe their organization is effective at helping them understand how information about skills needs applies to their own context.

To help employees make informed decisions about their development, leaders need to share evolving skills needs — even when plans are uncertain — and how these changes are likely to impact specific roles. Employees should also share their skills and career goals with the business. Exchanging this information empowers employees and leaders with the information they need to match and pursue mutually beneficial and flexible development opportunities.

Connector managers” — those who can connect employees to the right people and resources at the right time — are particularly effective at diagnosing their employees’ strengths, development areas, motivations, and career aspirations. They’re also more transparent with employees about skill needs and opportunities.

In our interviews with HR leaders about their approaches to more transparently sharing skills information among leaders and employees, we found that a few leading organizations have started to ask employees to document skills as part of a portfolio or profile throughout their careers. At these organizations, employees use an HR-supplied portal to track current skills, knowledge, and experiences alongside their career goals and development aspirations. Leaders can also access this information to fill critical roles and direct employees to development opportunities based on their profiles. Helping employees understand the connection between tracking skills information and future career opportunities makes them more likely to commit to maintaining their profiles.

As industries, organizations, customer needs, and work norms continue to shift and evolve, the need for rapid reskilling and upskilling will only intensify. These challenges require organizations to rethink the boundaries of current solutions to skills gaps. Rather than trying to read a crystal ball to identify the skills of the future or waiting for requests from business leaders for new skills, taking a dynamic skills approach leads to the highest likelihood of employees actually applying the skills they learn in their current roles.


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Today’s CEOs Need Hands-On Digital Skills



Because digital transformations change every process — from strategy to execution — and alter every function, they’re often challenging to pull off. CEOs have to be digitally literate and get personally involved if they wish to succeed. Yet, it seems that many companies don’t have the kind of CEOs, top management teams, and boards of directors they need to tackle digital transformations. Not only do CEOs have to be digitally literate, but they also need to play the pivotal role of the change agent. Digital transformation is about so much more than adopting new technologies and processes. At its core, it’s about overcoming inertia and resistance to changing the way people think and work. The CEO needs to lead from the front, inspire confidence in her vision, and rally the company to believe in what might appear to be a distant destination.

As business increasingly becomes digital and data-driven, many companies that once appeared to be built for success suddenly seem structured to fail. That’s evident in the lackluster results that recent digital transformations have delivered; according to a recent BCG study, over 80% of companies accelerated their transformation projects last year, but 70% fell far short of their objectives.

Because digital transformations change every process — from strategy to execution — and alter every function, they’re often challenging. To successfully pull one off, CEOs have to be digitally literate and get personally involved. This means understanding the nuances of the digital world and helping to shape product design, user experiences, and technology direction.

As Tom Siebel, founder of Siebel Systems, recently wrote in McKinsey Quarterly, “What I’m seeing now is that, almost invariably, global corporate transformations are initiated and propelled by the CEO. Visionary CEOs, individually, are the engines of massive change that is unprecedented in the history of IT — possibly unprecedented in the history of commerce.”

Yet, it seems that many companies don’t have the kind of CEOs, top management teams, and boards of directors they need to tackle digital transformations. According to a study of about 2,000 companies that was published in Sloan Management Review in March, only 7% were led by digitally competent teams; that is, a team where over half of the members are digitally savvy, with a firm understanding of how emerging tech will shape their company’s success. Unsurprisingly, those companies outperformed the rest by 48% in terms of revenue growth and market valuation.

Fewer than 25% of CEOs and about 12.5% of CFOs in the sample could be regarded as digitally proficient, which comes as no surprise to me. Even among those leading the technology function, just 47% of CTOs and 45% of CIOs made the cut; the rest focus on IT infrastructure and back-office operations more than capturing value from digital technologies. Clearly, companies everywhere need to rethink the composition of their top management teams.

Company boards aren’t that different either; another MIT study of around 3,000 companies with over $1 billion in annual revenues showed that 76% of boards weren’t digitally savvy — be it in terms of directors’ backgrounds, the number with digital experience, or the manner in which boards interacted with executives on technology-related issues. Interestingly, companies with three or more digitally savvy directors on their boards reported 17% higher profit margins and 38% higher revenue growth than those with two or fewer directors.

Don’t forget, boards exercise more control over legacy companies than they do over digital firms. The board of a Silicon Valley firm usually consists of tech company founders, venture capitalists, and seasoned executives from digital companies, who understand technology as well as the odds of success. That’s why Amazon’s Jeff Bezos could say, back in 1997, that Amazon would make bold, rather than timid, investment decisions; some would pay off while others would not; and “we will have learned another valuable lesson in either case.” Unfortunately, that isn’t something CEOs of legacy companies dare tell their boards or shareholders.

Not every CEO is born digital, by the way; most successful ones learn to understand technology on the job. Brian Chesky (Airbnb), Tim Westergren (Pandora), Sean Rad (Tinder), and Evan Sharp (Pinterest) are all non-tech entrepreneurs who set up digital giants. They focused on learning about their respective industries by looking at their technology strategy and some have even learned to program along the way.

Tech companies succeed when they are led by a digital holy trinity: A world-class Product Head, User Design Chief, and Chief Technology Officer. While each of these areas may be led by experts in those fields, the CEO in a digital firm plays an active role in determining product requirements, designing user experiences, and making technology choices. But, these roles are often buried deep in the corporate hierarchy in legacy companies. When they’re located more than three layers deep in the organization (as they often are), the CEO loses sight of, and involvement in, those decisions. The managerial bureaucracy takes over, and product, technology, and user experience decisions will demand lengthy peer reviews and inter-departmental clearances. The result: consensus — which is the enemy of speed and uniqueness.

Not only do CEOs have to be digitally literate, but they also need to play the pivotal role of the change agent. Digital transformation is about so much more than adopting new technologies and processes. At its core, it’s about overcoming inertia and resistance to changing the way people think and work. The CEO needs to lead from the front, inspire confidence in her vision, and rally the company to believe in what might appear to be a distant destination.

I can imagine legacy CEOs arguing that they can’t afford to be hands-on, that they hire great people (often from tech companies), and that their role is to facilitate work. But that’s the old world. The most successful digital leaders obsessively focus on products, user experiences, and technology. An obsession with detail characterizes Amazon’s Jeff Bezos, Apple’s Steve Jobs, Google’s Sergey Brin and Larry Page and Tesla’s Elon Musk. It’s the same with non-tech companies led by digital leaders such as Nike’s John Donahoe and Starbucks’ Kevin Johnson. They all understand that focusing on change management, great products, and user experience isn’t exactly living in the weeds; they’re the seeds of the future.

As a CTO of a tech company based in Silicon Valley, I’ve met with the CEOs of some of the world’s largest incumbents to help them modernize their digital and data infrastructure. At most of my meetings, I ask them how important digital technologies are to their business, and they assure me that no other priority comes anywhere close. But when I ask their CIOs or CDTOs (Chief Digital Transformation Officers) how much time the CEO spends focusing on technology and digital innovation, their voices drop to a whisper: “Less than they should.”

If the CEOs of the world’s most valuable companies can afford to spend time on product requirements, user experience, and technology, CEOs of legacy companies that are playing digital catch-up can hardly afford not to do the same.

With every business turning into a digital and data business, every CEO needs to lead his or her company’s digital transformation personally. Nothing could hurt a company more in the future than the mistaken notion that becoming a digital business is simply the CTO or CIO’s problem.


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Running a Business

3 Tactics to Accelerate a Digital Transformation



Nothing changes unless people’s behavior changes. Sure, digital transformation requires that companies upgrade systems and make sure people have the right tools and know how to use them. But those investments only lead to transformation if they are coupled with serious work helping people adopt and use that technology in meaningfully different ways. Otherwise, you replace fax machines with email, email with Slack, Slack with neurologically transmitted messages (someday!), but still find past problems perpetuating. As Oracle CEO Safra Catz notes, “The hard thing about these transformations isn’t the technology. It’s the sociology.”

How do you encourage and enable distributed groups of people to get the most out of new digital technologies? Let’s consider a case study of how DBS Bank in Singapore managed the transition to more distributed, remote work over the past two years. [Disclosure: Scott’s firm, Innosight, has provided advisory services to DBS in the past. And Paul is currently an Advisor to DBS.] This case suggests three key tactics to enable successful digital transformation: use technology to make technology disappear, actively shape day-to-day behavior, and systematically reinforce desired behavior changes.

1) Use technology to make technology disappear.

Paul served as the Chief Data and Transformation Officer for DBS Bank in Singapore for more than a decade. He led a team called “Future of Work” that helps to accelerate innovation and drive technology adoption across the workforce.

The team seeks to use technology to create friction-free, human experiences, where the technology itself disappears into the background. Like most banks, DBS is very security-conscious. The rise of people working from home in the wake of the Covid-19 pandemic has brought new security risks, such as the possibility of bad actors more easily taking photos of screens, to use one example. Due to these concerns, DBS did not allow most employees to access sensitive systems from home prior to the pandemic. But with the increased need for remote work, DBS now uses new techniques — some of which were originally created to combat credit card fraud — to enhance the security of remote work, without compromising the user experience. For example, DBS now places a “digital watermark,” or a unique pattern, on each user’s screen. It uses sophisticated artificial intelligence to detect unusual employee behavior and has dramatically simplified the two-factor authentication experience required to access internal systems. These largely invisible background technologies allow employees to enjoy the same access to enabling tools and sensitive information, wherever they happen to be.

Another challenge brought about by the increase in remote work is getting a handle on employee sentiment without as much face-to-face interaction. To address this issue, the Future of Work team has built a model using natural language processing algorithms to spot weak signals of employee dissatisfaction in qualitative comments in regular experience surveys. The model assesses employee sentiment and categorizes and highlights patterns in qualitative comments. It features a dashboard so that any department or team can view sentiment analysis and trends across categories or drill down into word-for-word comments. This approach enables leaders to have a fine-grain view on what needs the most attention.

A final example involves using technology to pinpoint internal tools that aren’t delivering against employee expectations. As employees work in a more hybrid fashion, they need a wider range of digital tools to help do basic work tasks. DBS has more than 200 applications that employees can use to do common tasks ranging from processing credit card applications to completing online performance reviews. Just as consumers rate games and productivity tools in Apple’s popular App Store, DBS employees rate their internal applications. For any application that has more than 100 users and less than a four-star rating (out of five stars), the app owner must address the identified challenges. For example, one app tracks the number of times employees open official corporate communications to measure their effectiveness. A low app store rating surfaced significant usability issues, such as frequent crashes and a confusing interface. The team upgraded the app and introduced training, boosting the score well above 4 stars.

2) Actively shape day-to-day behavior.

In our book Eat, Sleep, Innovate (also co-authored by Scott’s Innosight colleagues Natalie Painchaud and Andy Parker), we noted that a significant barrier to behavior change in organizations is the inertia of old ways of doing things. Past processes designed for an analog world can conflict with digital technologies, leading to duplication of effort and significant employee frustration.

DBS has a mechanism to deal with this problem called the Kiasu Committee. Kiasu is local slang in Singapore, akin to the idea of the fear of missing out (when people stormed supermarkets early on in the pandemic to hoard toiler papers, locals would say, “Why so kiasu?”). The head of Legal and Compliance chairs the Kiasu Committee, which takes the form of a mock courtroom where any employee can “sue” the owner of a policy or process that they feel is getting in the way of getting work done. A mix of employees from a range of levels serve as the “jury,” collectively deliberating over whether a change should be made. One of the first decisions was to remove the need for physical signatures to approve a proposal. The approach caused quite a ripple through the company and gave DBS employees confidence that their issues would be heard and addressed.

The Future of Work team has also focused on addressing new problems that arose with the rise in remote work, such as the “cultural decay” that comes when connectivity and community fray due to factors ranging from obvious ones (the lack of the ability to hold informal gatherings) to more subtle ones (the lack of buffers between meetings inhibiting informal human connection).

Digital dislocation can drive cultural decay by limiting opportunities to teach norms to new members formally, or, even more importantly, to reinforce shared beliefs and assumptions in subtle ways. For example, newcomers can’t watch longstanding, unstated rituals, like how people array around tables during meetings, or observe which topics of conversation flow naturally in the hallway, and which are avoided.

DBS has developed specific rituals to address cultural decay. For example, it now offers a formal multimedia onboarding experience for new employees. The idea is to be very intentional about how DBS teaches key elements of its cultural transformation to new employees. The ritual builds off of a physical “wall of transformation” that DBS had in its headquarters providing a visual overview with year-by-year highlights of its transformation. The onboarding journey combines a digital version of this story with a set of curated discussions with DBS leaders. Not only does that provide a more complete picture of DBS’s transformation, it lets new employees quickly “meet” a range of leaders in the bank.

Another example is “meeting check-in.” Borrowing from agile development principles, at the start of meetings, DBS asks people to pick a number from 1 to 10 describing their state of mind. Anyone who doesn’t give a 7 or 8 has to explain why. Another approach is to ask people at the start of meetings what percent present they are in the meeting or to ask, “Is there anything that will prevent you being fully present at this meeting?” creating opportunities for people to share humanizing factors that build team empathy. Some departments augment the in-meeting ritual with simple apps to regularly track and calibrate data.

The Kiasu Committee, the virtual onboarding ceremony, and the meeting check-in are all examples of what we call BEANs, shorthand for behavior enablers, artifacts, and nudges. They combine a formal behavior enabler (like a checklist or a ritual) and informal artifacts and nudges (like a visual reminder) to drive behavior change. Our article “Breaking the Barriers to Innovation” provides a step-by-step guide for how to create BEANs.

3) Systematically reinforce desired behavior change.

Like any data-driven improvement program, the Future of Work team has faced its challenge. For example, it was natural for app owners to respond to low ratings by getting defensive, challenging the validity of the data, trying to hide bad news, or even gaming the system by submitting anonymous positive reviews.

Approaches that have the potential to give a louder voice to broader groups of employees only work if there are reinforcing mechanisms to hear those voices clearly and act based on what they are saying. More broadly, managing the human side of digital transformation requires work to systematically reinforce desired behavior change.

For the Future of Work effort, that starts with connecting to an overall effort at DBS to have a balanced scorecard that measures and manages its transformation efforts. DBS also modified incentives to support its overall digital transformation efforts. For example, the usage and rating of a particular digital app directly impacts the performance rating and bonus of the DBS leader responsible for that app.

Additionally, DBS created a new governance system specifically related to the employee experience. The “Employee Journey Council,” chaired by key senior executives, discusses issues identified by employees such as the responsiveness of the internal IT team and the burden of remote working. The council then intervenes to improve the employee experience. For applications that are missing their target threshold, for example, the council scrutinizes progress against an identified improvement plan. DBS plans to drive this governance mechanism lower in the organization to further increase accountability.

DBS carefully tracks and measures progress in its digital transformations. The percentage of employees who said that they strongly agreed with the statement that digital tools enhanced their productivity increased from 78% in 2019 to 84% in 2021. Positive sentiment measured with the dashboard mentioned above has increased by 35%. And, specific to hybrid work, a September 2021 dipstick survey found that 92% of employees said they were satisfied with the technology that helps them work remotely.

While the journey hasn’t been easy for DBS, rapid advances in artificial intelligence and the availability of open-source solutions have significantly simplified the ability to create models and back-end tools to reduce the barriers to digital transformation. Following the tactics in this article have smoothed DBS’s transition to hybrid work and helped DBS continue to win regular accolades. Leaders at other organizations can similarly accelerate their own digital transformation efforts by using technology to make technology disappear, actively shaping day-to-day behavior, and systematically reinforcing behavior change. The payoff in the forms of higher engagement and improved productivity is well worth it.


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