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VUCA relates to threats that people and enterprises often encounter. The acronym reflects the constant, dramatically-transforming, and unpredictable world. The concept originated in 1987, based on the theories of Warren Bennis and Burt Nanus. The term was first used by U.S. Army War College to describe the volatile, uncertain, complex, and ambiguous general conditions globally.
The acronym found traction after 2002, when it was considered an emerging idea to be discussed among the strategic leadership. The term VUCA stands for:
- Volatility
- Uncertainty
- Complexity
- Ambiguity
The 4 VUCA challenges reflect the unpredictable forces of change that affect organizations, necessitating new skills, approaches, and behaviors to mitigate them. The 4 elements of VUCA relate to how people view the situations where they make decisions, formulate plans, respond to challenges, cultivate change, and solve issues.
VUCA is a practical code for anticipation, understanding, preparedness, and intervention in the wake of uncertainty and confusion. One of the biggest challenges of managing in a VUCA world involves team members who resist change. Simply training the leaders on key capabilities isn’t adequate to avoid failures resulting due to not handling the VUCA issues properly. What differentiates sound Leadership from mediocre management is the leaders’ ability to ascertain key elements that prevent them from adopting resilience and flexibility.
In this age of disruption, Volatility, Uncertainty, Complexity, and Ambiguity are widespread. These elements will be more prevalent across industries and enterprises in future, and if not managed properly can sap an organization’s and its employees’ strengths.
Let’s discuss these VUCA elements individually.
Volatility
The Volatility element of VUCA talks about the distinct situational categorization of people due to their specific traits or their reactions in particular situations. People react differently in specific settings due to social cues. Volatility describes the influence of situations on stereotypes and social categorization, which is the reason why people perceive others differently.
Two factors connect people to their social identities: Normative fit and Comparative Fit. Normative fit is the degree that a person relates to the stereotypes and norms that others associate with their specific identity. For example, a Hispanic woman cleaning a house does not get gender stereotypes from others in this situation, but when she eats an enchilada ethnic stereotypes emerge and the gender is forgotten. Comparative fit relates to specific traits of a person that are prominent in certain states compared to others, which are obvious as others around a person do not have those traits. For example, a woman in a room full of men stands out, whereas all the men are grouped together.
Uncertainty
The Uncertainty element of VUCA pertains to the unpredictability of information in events, which often occurs in the intention to indicate correlation between events. Uncertainty is often counteracted by using social categorization (stereotypes), as people tend to engage in social categorization when there isn’t much data about an event.
For instance, when there isn’t enough information to clearly appreciate someone’s gender—as in case of an author’s name when discussing written information—majority of people presume the author is a male. Social categorization also occurs in case of a race, when people stereotype a certain race to a particular trait. For example, basketball players are most of the time assumed as black people while golfers are expected to be white.
Complexity
The Complexity element of VUCA relates to the inter-relatedness of several factors in a system. Complexities due to interactions and dependencies within groups and categories bring unexpected results even in a controlled environment. There are certain identities in individuals that are more dominant than others. Other people distinguish these identities, make their assumptions about them, and create stereotypes. However, complexity in a person’s personality makes it difficult to socially categorize that individual accurately.
Different categories trigger in the mind of the observer, creating positive and negative perception. It is that positive perception that the observer is more open-minded despite stereotypes and think past the target’s dominant social trait. Complexities in social identities cause some identities to lessen the noticeability of other identities, making the targets unnoticeable and overlooked.
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Supply Chain Management is getting more and more complex. The pressure on the Supply Chain information to be made public is also increasing day by day. With the popularity and widespread use of social media, it has become more and more difficult for organizations to hide information pertaining to supply chain practices, employees’ treatment, suppliers’ processes, or waste materials generated that could affect the environment. Social media often publicizes negative reports on companies’ supply chain practices—its best to have a robust information disclosure strategy before anything like that ever happens.
Executives must appreciate these external forces and information transparency demands, and react proactively to build and maintain competitive advantage for their organization. They need to be able to, first, accurately predict the data requirements of various stakeholders and then unanimously decide on the type and frequency of the information to be shared. A reactive information disclosure strategy is less time and planning intensive, but it does limit the chances of first-mover advantage over competition.
Supply Chain information can be classified into 4 categories:
- Critical
- Strategic
- Non-critical
- Optional
Critical Information
Organizations using this information category know that they have certain glitches in their Supply Chains that could potentially be a source of criticism from NGOs and the media and may bear adverse effects on their reputation. This includes information concerning unhygienic or inferior quality products; unfair supply chain practices; or environmental problems.
Strategic Information
Even though stakeholders do not ask for this information, this information category is considered strategic as disclosing this data can boost brand value and product differentiation. The strategic information category is high value to the organization but is low on risks for the supply chain. For example, in the beauty, fashion or food products industry, sharing information about organic ingredients may be instrumental in achieving product differentiation and brand reputation.
Noncritical Information
Disclosure of this information category is typically un-called for and has negligible effects on brand value. This information category has low value for the company and has low risks for the Supply Chain. For instance, needlessly sharing child labor data in regions with actively enforced child welfare laws.
Optional Information
This information category is a matter of internal supply chain consideration and has no bearing on the customer. The optional information category is low value to the organization and is actually highly risky for the Supply Chain. For instance, potential quality issues and defects in the supply chain that are identified and resolved during quality control, and do not affect the finished product.
There isn’t a one-size-fits-all strategy that organizations can adopt to ensure a viable and high-quality Supply Chain Information Disclosure. However, the approach needs to be evolving based on individual circumstances. Senior executives should promptly respond to public inquiries, ensure fair treatment of employees, and guarantee compliance with basic human rights to protect their organizations’ reputation. Experts suggest the following 8-phase approach to address and improve Supply Chain Information Disclosure.
Appreciate the criticality of Supply Chain information disclosure
The first step is to analyze the forces that demand increased supply chain transparency and ascertain the importance and priority of information for the stakeholders. Once it is established, the leadership must take actions to address the information requirements of key stakeholders.
Appraise Supply Chain data collection abilities and resource requirements
The next step is to assess the competence of the organization—and that of the suppliers—to gather quality supply chain data. The executives should also evaluate the costs and resource requirements to enable improved information disclosure.
Determine the existing and desired levels of Supply Chain information
The third step is to ascertain the existing knowledge of supply chain information among the executives and suppliers. The leadership needs to identify the desired levels of supply chain data collection and sharing capabilities, and invest to fill any gaps between the existing and desired supply chain data collection and sharing competencies.
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Transformation of an organization into a Next-generation Learning Organization (NLO) is a challenging endeavor. The main hurdles include convoluted hierarchies, bureaucratic red tape, delayed decision making, and complicated organizational systems and processes.
To develop a learning organization, leadership needs to trim down bureaucracy and complexities. They should make the best use of technology to gather holistic real-time data, deploy Artificial Intelligence at scale, and develop data-driven decision-making systems.
Five Core Pillars of Learning are essential for the creation of a Next-generation Learning Organization, including:
- Digital Transformation
- Human Cognition Improvement
- Man and Machine Relationship
- Expanded Ecosystems
- Management Innovation
Let’s take a deep dive into the first 3 Core Pillars.
1. Digital Transformation
The first pillar is Digital Transformation. Next-generation Learning Organizations (NLOs) are characterized by their speed of learning and their adeptness to take action based on new insights. They use emerging technologies to automate as well as “autonomize” their businesses, without relying too much on human intervention and decision-making.
By autonomizing, the NLOs enable machines to learn, take action, and evolve on their own based on continuous feedback. They create integrated learning loops where information flows automatically from digital platforms into AI algorithms where it is mined in run-time to gather new insights. The insights are passed to action systems for necessary action that create more data, which is again mined by AI, and the cycle continues, facilitating learning at fast pace.
2. Human Cognition Improvement
Next-generation Learning Organizations (NLOs) schedule time for their people to have unstructured reflection on their work. While most organizations fear disruption of human work in future by AI and machines, NLOs assign unique roles to their people based on human cognition strengths—e.g., understanding relationships, drawing causal judgment, counterfactual thinking, and creativity. These organizations are aware of AI’s advantage—in analyzing correlations in complex data promptly—as well as its shortcomings in terms of reasoning abilities and interpretation of social / economic trends. NLOs make design the center of their attention and utilize human creativity and imagination to generate new ideas and produce novel products. They assign roles accordingly, inspire imagination in people by exposing them to unfamiliar information, and inculcate dynamic collaboration.
3. Man and Machine Relationship
NLOs foster innovative ways to promote collaboration between people and machines. They recognize that this helps them in better utilization of resources, maximize synergies, and learn dynamically.
To create effective collaboration between people and machines, NLOs develop robust human-machine interfaces. The existing AI systems lack the ability to decipher everything, which is an area where humans excel. NLOs supplement these shortcomings by setting up human-machine interfaces, where humans assist the AI by corroborating its actions and suggesting sound recommendations. These learning organizations bifurcate responsibilities based on the risks involved, assign humans and machines appropriately against each job, and select a suitable level of generalization and sophistication between humans and machines.
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Gordon Moore, Intel co-founder, observed that the number of transistors in a dense integrated circuit doubles about every two years. He projected that this rate of growth would continue for at least another decade.
His observation, termed the “Moore’s Law,” has correctly predicted the pace of innovation for several decades and guided strategic planning and research and development in the semiconductor industry. Moore’s law is based on observation and projection of historical trends.
In 2015, Gordon Moore foresaw that the rate of progress would reach saturation. In fact, semiconductor advancement has declined industry-wide since 2010, much lower than the pace predicted by Moore’s law. The doubling time and semi-conductor performance has changed, but it has not impacted the nature of the law much.
Although many people predict the demise of Moore’s law, exponential growth in computing power persists with the emergence of innovative technologies. Moore’s law is only part of the equation for effective Digital Transformation—there are other contributing factors including the role of leadership.
First Law of Digital Transformation
George Westerman—a senior lecturer at the MIT Sloan School of Management—proposes a new law, which states that, “Technology changes quickly, but organizations change much more slowly.” The law known as the “First Law of Digital Transformation” or “George’s Law” is a pretty straightforward observation, but is often ignored by the senior leadership. This is why Digital Transformation is considered more of a leadership—than technical—issue.
Just announcing an organization-wide Transformation program does not change the enterprise. According to George’s Law, successful Digital Transformation hinges on the abilities of senior leadership to effectively manage the so many contrasting mindsets of its workforce, identify and take care of the idiosyncrasies associated with these mindsets, interpret their desires, and focus attention on encouraging people to change.
Above all, the leadership should focus on converting Digital Transformation from a project to a critical capability. This can be done by shifting emphasis from making a limited investment to establishing a sustainable culture of Digital Innovation Factory that concentrates on 3 core elements:
- Provide People with a Clear and Compelling Vision
- Invest in Upgrading or Replacing Legacy Technology Infrastructure
- Change the Way the Organization Collaborates
Let’s now discuss the first 2 elements of the First Law of Digital Transformation.
Provide People with a Clear and Compelling Vision
Without a clear and compelling transformative vision, organizations cannot gather people to support the change agenda. People can be either change resisters, bystanders, or change enablers. However, most people typically tend to like maintaining the status quo, ignore change, or choose to openly or covertly engage in a battle against it.
For the employees to embrace change, leadership needs to make them understand what’s in it for them during the transition and the future organizational state. This necessitates the leaders to develop and share a compelling vision to help the people understand the rationale for change, make people visualize the positive outcomes they can achieve through Transformation, and what they can do to enable change. A compelling vision even urges the people to recommend methods to turn the vision into reality.
Invest in Upgrading or Replacing Legacy Technology Infrastructure
Problems and shortcomings in the legacy platforms is an important area to focus on during Digital Transformation. The legacy technology infrastructure, outdated systems, unorganized processes, and messy data are the main reasons for organizational lethargy. These issues hinder the availability of a unified view of the customer, implementing data analytics, and add to significant costs in the way of executing Digital Transformation.
Successful Digital Innovation necessitates the organizations to invest in streamlining the legacy systems and setting up new technology platforms that are able to enable digital and link the legacy systems. Fixing legacy platforms engenders leaner and faster business processes and helps in maintaining a steady momentum of Innovation.
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Technology, Internet, growth, and globalization have metamorphosed the way we work, play, and live. They have even changed the fundamental laws of economics. We are living in an economy that is quite different from the old manufacturing-based economy of the 1980s. Fewer people are now employed in the manufacturing sector, who are anxious about the prospects of being replaced by machines soon.
The “New Economy” is a term economists started using in the 1990s to describe new, high-tech, high-growth industries that have been the driving force of economic growth since that period. The new economy is also heralded as the Digital Economy, the Knowledge Economy, the Data Economy, or the eCommerce Economy. Top technology enterprises—including Google, Facebook and Apple—have outpaced traditional firms around the globe by taking advantage of the new economy.
Leadership Development in this age of Digital Economy is a key challenge for most organizations. More and more organizations, today, are revisiting what they are about and the meaning of leadership for them. It’s not about one person or even those residing at the top anymore.
MIT Sloan Management Review conducted a study of 4,000 executives from 120 geographies around the world to understand what defines a great leader in this changing world. The study revealed striking results with most executives believed that their leaders lacked the mindset needed to produce the strategic changes essential for leading in the Digital Economy. Enterprise-level transformation is what majority of leaders feared to embark on.
Mindsets are established set of attitudes held by someone that shape how a person interprets and responds to experiences. A mindset arises out of a person’s view of the world or philosophy of life. To know about the Digital Economy leadership mindsets (i.e. leadership mindsets critical to survive in this new economy), the MIT Sloan Management Review’s global study identifies 4 critical mindsets—based on in-depth interviews from executives worldwide and detailed analysis of data:
- The Producer
- The Investor
- The Connector
- The Explorer
Let’s define these first 2 leadership mindsets.
The Producer
Leaders with a producer mindset evaluate each of their customer touch points painstakingly. These leaders exhibit a passion for producing customer value. Producers concentrate on analytics, digital know-how, implementation, results, and customer satisfaction. They focus on analytics to fast-track creativity. The resulting innovation helps them tackle shifting customer preferences and enhance customer experiences. The Producers strive to create all the customer journeys enjoyable.
The Investor
The leaders with an investor mindset make people appreciate the higher purpose they serve by their work. They constantly struggle to instill motivation and teamwork among their teams in order to achieve their overall organizational goals. The leaders with an investor mindset are concerned about the communities that surround them. They look after the well-being and constant advancement of their employees, and devote their efforts to improve value for their customers.
Fostering these types of mindsets is critical to building the right Organizational Culture for an organization to be successful in the Digital Economy.
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Disruptive technologies are helping companies automate work. Robotic Process Automation and Artificial Intelligence are taking up jobs which were in the past earmarked only for smart humans. Driver-less cars, automated check-in kiosks at airports, and autopilots steering the aircrafts are just few instances of how automation is transforming our world.
However, automation presents unique challenges that organizations need to identify and mitigate appropriately. These include costs associated with job losses; confidentiality of data; quality and safety risks stemming from automated processes; and regulatory implications.
Other critical factors to consider before investing in automation are adoption, pace of development of automation, and readiness of organizational leadership in redefining processes and roles to support automation.
The key question is how automation will impact our work in future. Should we anticipate benefits — e.g., efficiency gains and quality of life improvements — or dread further disruption of established business and job cuts?
Research by McKinsey suggests that Robotic Process Automation will impact 4 workplace areas the most:
- Workplace Activities
- (Re)definition of Work
- High-wage Jobs
- Creativity and Meaning
Now, let’s discuss the first two key areas in further detail.
Workplace Activities
Research findings (based on the US labor market data) reveal that the future does not likely hold complete automation of individual jobs, but rather automation of certain activities within specific occupations. The assumption that only routine, codifiable activities can be easily automated — and those that necessitate implicit knowledge will be unaffected — is misleading. Automation has already reached (or surpassed) the median level of human performance in some cases.
Capital or hardware-intensive industries — under stringent regulatory control — are slow and expensive to automate and need more time to reap return on investments. Whereas, the sectors where automation is mostly software based (e.g., financial services) may create value at a far lower cost and within rather shorter span of time.
(Re)definition of Work
The current level of automation can potentially transform a number of occupations to a certain level, but it requires redefinition of job roles and activities. Research reveals that only about 5% of occupations can be completely automated with the current level of technology.
In spite of this, automation can boost human productivity even in the highest paid occupations by taking care of repetitive daily tasks — e.g., analyzing paperwork, reports, data and evaluating applications based on criteria — and freeing up time for people to focus more on high value work that involves human emotions and creativity.
For instance, Automation and Machine Learning can automate diagnosis of common ailments, thereby enabling the doctors to concentrate more on acute or complicated problems. Likewise, lawyers can employ data mining tools to sift through piles of documentation to isolate the most relevant cases for their review.
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Digital-savvy startups are disrupting markets and threatening conventional businesses. They are doing this by utilizing technology to offer new products and services and providing tailored yet uncomplicated experiences for their customers.
Likewise, large traditionally-run firms will have to keep evolving their Customer Experience approaches to secure additional avenues of revenue and to stay competitive. To accomplish this, they will need to develop capabilities to effectively utilize insights on customer preferences and design offerings as per the customers’ preferences.
Many organizations, today, are undertaking Digital Transformation programs to improve their Customer Experiences. However, a majority of these Digital Transformation initiatives fall short of securing their maximum value potential due to focusing only on improving specific touchpoints instead of confronting the entire customer journeys—spanning across several departments and channels.
To make their Customer Experience sustainable and to become Customer-centric Organizations need to clearly transform their ways of doing business, operations, and employee behaviors. It is critical to improve these fundamental support processes before embarking on initiating any Customer Experience optimization initiatives.
Customer Experience optimization facilitates in gaining more satisfied/paying customers, additional value, and better retention rates. Research reveals that the companies that have higher Customer Satisfaction levels can achieve four times growth in value compare to those that rank lower in Customer Satisfaction.
Customer Experience (CX) Approach to Value Creation
The following pragmatic 5-phase approach to Customer Experience Management and Value Creation is of great benefit to organizations aspiring to enrich their Customer Experience, achieve clear-cut differentiation, and capture the most potential value:
- Understand What Customers Value
- Simplify and Streamline Offerings
- Link Customer Value to Operational Drivers
- Focus on Most Important Customer Journeys
- Adopt Continuous Improvement (CI) Thinking
Let’s now delve deeper into the first 3 phases of the approach.
Understand What Customers Value
Ascertaining the key drivers of Customer Satisfaction is the foremost step in improving Customer Experience. A flawed approach—that many companies still employ—at the onset of a Customer Experience optimization initiative is to reduce costs associated with internal processes and exploring customer pain points. This doesn’t assist in maximizing Value Creation.
Customer-centric organizations, on the other hand, devote their time in developing a clear understanding of what really matters to their customers. This helps in deciding where to focus, rationalizing their processes, and creating new experiences for the customers to generate additional value.
Great Customer Experience necessitates much more than just satisfactory interactions. Customer Satisfaction should be mapped along the entire customer journey—spanning multiple functions and channels—as customers use various channels to communicate with companies before making a transaction.
Simplify and Streamline Offerings
Alongside rationalizing the processes, it is equally important to carry out a detailed analysis of the brands, offerings, and price structures is essential to tap value from Customer Experience. After all, even the most pleasing Customer Experience cannot offset an unpredictable or exorbitantly expensive product.
Once these fundamentals are in order, organizations should investigate which interactions and Customer Journeys carry the most significance in a Customer Experience; evaluate how the organization is rated in each journey; identify and focus on the operations that need to be overhauled to improve the overall Customer Experience.
Link Customer Value to Operational Drivers
Technology and customer input provides the stimulus to streamline offerings and Customer Experience. However, the real value comes from linking the Customer Experience to core operational processes. Seeing journeys from the customer perspective aids in focusing on what they need and linking internal processes, structures, and KPIs to customer facilitation.
This necessitates deeper insights on elements that are of most value to the customer across a journey, pinpointing drivers of business costs and revenues, and—most importantly—inculcating the right mindsets across the organization. This detailed evaluation of customer journeys facilitates in determining operational improvements that bear the most positive effect on Customer Experience.
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Organizations need to persistently improve the way they do business to stay ahead of the curve. New ideas trigger organizational improvement and build the foundation of a Learning Organization.
Scholars have defined a Learning Organization in many different ways. Some suggest it as an organization skilled at creating, acquiring, and transferring knowledge, and at modifying its behavior to reflect new knowledge and insights. Marlene Fiol and Marjorie A. Lyles describe organizational learning as “the process of improving actions through better knowledge and understanding.” Barbara Levitt and James G. March define organizations as “Learning Organizations when they encode inferences from history into routines that guide behavior. Chris Argyris categorizes organizational learning as “a process of detecting and correcting error.” According to Peter Senge, “a Learning Organization is a group of people working together collectively to enhance their capacities to create results they care about.”
Being a Learning Organization offers several advantages. A perpetual influx of insights and new experience keeps the organization dynamic and ready for transformation; assists in better management of investments, improves efficiency; and helps in developing cost leadership and differentiation strategies. Learning Organizations tend to be more innovative by encouraging people to learn, develop, and by generating a more innovative environment. Shared learning builds the corporate image of the organization and increases the pace of change within the organization. Learning Organizations provide their people the ability to think insightfully about complex problems, take coordinated action, improve decision making, and instill a sense of community in them.
Despite efforts to improve continuously and creating new knowledge, organizations cannot simply become Learning Organizations. They employ various approaches but what they actually need is to become proficient in translating new knowledge into new ways of doing things, and actively managing the learning process so that it gets ingrained into the organizational culture.
Becoming a Learning Organization necessitates mastering 5 key activities. These 5 activities form the building blocks of a Learning Organization and should be integrated into the organizational core to transform your company into a Learning Organization.
- Systematic Problem Solving
- Experimentation
- Learning from Experience
- Learning from Others
- Knowledge Transfer
Applying these practices to some degree or in isolated cases isn’t enough. To ensure continued success, these practices should be complemented by distinct mindsets, support systems, and processes.
Let’s now discuss the first 3 building blocks in detail.
1. Systematic Problem Solving
Systematic problem solving is based on scientific methods for diagnosing problems, e.g., the Plan, Do, Check, Act (PDCA) cycle or “hypothesis-generating, hypothesis-testing.” The technique employs fact-based management, relying on concrete data instead of assumptions for making decisions and utilizes statistical tools—such as Pareto charts, histograms, correlation, and cause and effect diagrams—to consolidate data and draw conclusions.
For a real Learning Organization, people need to become more disciplined, pay more attention to detail, assess underlying causes, and analyze data before reaching decisions.
2. Experimentation
Experimentation involves systematic exploration and testing of new knowledge. Experimentation has 2 fundamental configurations; both forms transfer knowledge and yield new insights, capabilities, tools, techniques, and processes:
- Ongoing programs
- Demonstration Projects
Ongoing Programs
Ongoing programs entails a chain of small experiments aimed at yielding incremental gains in knowledge. These programs maintain a steady flow of new ideas by sending workforce on sabbaticals at different places to learn new work practices and tools from industry and academia, and applying that knowledge to their daily routines. Such programs foster risk taking and a feeling of “benefits of experimentation far outweigh the costs.”
Demonstration Projects
Demonstration projects are one of a kind, large-scale initiatives that include holistic system-wide transformation targeted at a single site. These projects are executed with a goal of developing new organizational capabilities using a “clean slate” approach.
Self-managing, multi-departmental teams; high level of employee autonomy; considerable “learning by doing;” course corrections; implicit policy guidelines, precedents, and decision rules are the key characteristics of demonstration projects.
3. Learning from Experience
Learning Organizations gain valuable knowledge from their past experiences, by doing an exhaustive and systematic appraisal of past successes and failures. However, not too many managers pay attention to past experiences or reflect on those, eventually losing valuable insights. To inculcate a culture of learning, lessons learned should be recorded and made readily accessible to all employees.
A handful of companies have laid out processes for their managers to contemplate on their past actions and incorporate those in their learning. At the core of this approach lies the belief that distinguishes productive failure from unproductive success. Productive failure delivers knowledge and understanding whereas unproductive success goes unnoticed where nobody knows what went well and why. Learning from experience approach isn’t that expensive—case studies and project reviews can be compiled with little cost.
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Corporate Social Responsibility (CSR) is an organization’s commitment to produce an overall positive impact on society. CSR encompasses sustainability, social and economic impact, and business ethics. It makes a company socially accountable of its operations, stakeholders, and the public. Businesses undertake CSR programs to benefit society while boosting their own brands.
CSR affects every aspect of business operations and functions. Encouraging equal opportunities; partnering with organizations practicing ethical business methods; putting part of earnings back into environment, health, and safety initiatives; and taking care of communities and charity are all examples of CSR initiatives.
Communities, customers, employees, and media consider CSR vital and gauge companies based on these initiatives. Executives of leading companies consider CSR as an opportunity to deal with critical issues innovatively, reinforce their organizations, and serve the society simultaneously.
The Need for CSR Implementation
Organizations need to come up with a robust approach to unlock potential benefits and value from CSR for them and for the society. The organizations practicing Corporate Social Responsibility do that with one of the following 4 objectives in mind:
- Philanthropy: These initiatives (e.g. corporate donations) make the companies and society feel good, but produce low value for the business—questionable repute building benefits to companies, but offer much to society.
- Propaganda: These CSR initiatives are predominantly geared towards promoting a company’s standing, but offer little real value for the society. This form of CSR is more of advertisement and becomes risky if there are any gaps between the firm’s commitments and actions.
- Pet Projects: Some companies engage in CSR initiatives that support the personal interests of senior executives. These initiatives are much touted about, but are actually of little value to the business or community.
- Smart Partnering: These initiatives concentrate on common themes between the business and the community. Organizations, in this case, create innovative solutions by drawing synergies from partnerships to tackle major issues concerning all stakeholders.
Among these objectives, Smart Partnering offers maximum opportunities for shared value creation and finding solutions to crucial business and social challenges. Whereas for the society, smart partnering helps create more employment opportunities, improve livelihoods, and enhance the quality of life.
Guiding Principles for CSR Initiative Selection
An effective way for the companies to maximize benefits of their CSR efforts is to map the current initiatives; identify the objectives, benefits, and resources responsible for realizing value from those initiatives; and define the projects valuable for addressing key strategic challenges.
Pet projects, philanthropy, or propaganda are easy to plan and execute. However, the real issue is to implement CSR opportunities that bring value for the business as well as society (smart partnering). This goal can be achieved by applying these 3 guiding principles:
- Focus on the right segments
Real opportunities lie in the segments where the business collaborates with and influences the society the most. These segments help the business interpret mutual dependencies and uncover maximum mutual benefit.
- Recognize challenges and benefits
After finalizing the opportunity segments, it is imperative to appreciate the potential for mutual benefit. The key is to find the right balance between the business and community and recognize the challenges that both sides face.
- Find the right partners
Collaboration with right partners—who benefit from business endeavors and capabilities of each other—creates a win–win situation for both sides and motivates them to achieve mutual value. Sustainable collaboration demands long-term alliances and deeper insights on the strengths of each other.
These principles are helpful in selecting appropriate CSR opportunities, identifying societal and business needs to be addressed, and the required resources and capabilities.
The Case for CSR Benefits
The goal of unlocking mutual benefits—associated with CSR (specifically Smart Partnering)—is critical for long-term success of the program. As required by any other strategic initiative, the mutual value creation objective needs to be carefully assessed based on the true value-creation potential, prioritized, designed, staffed, and audited.
The next step is to outline the list of potential benefits for the business and community. A well-defined business case and a compelling story immensely helps involve and gain commitment from the senior leadership, investors, and employees.
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Takeovers can turnaround companies in a short period of time, but there is a significant degree of risk to be anticipated and mitigated prior to undertaking such transactions. Lack of careful deliberation of the potential risks, insufficient planning, weak execution, and lack of focus on Post-merger Integration are the major reasons why many Merger & Acquisition deals fail to achieve their desired goals.
The course of an M&A transaction has to be set at an early stage, way before the actual deal closure. The period prior to the deal approval by the regulatory authorities and while due diligence is being done is most critical, and should be utilized by the leadership to clearly define the goals of integration, the potential risks, and a layout for the execution of the actual integration process. It is the right time to perform a structured evaluation of 3 core pre-merger considerations associated with such deals, i.e.:
- Strategic Objectives
- Organization & Culture
- Takeover Approach
Understanding these PMI Pre-merger considerations helps the stakeholders ascertain the unique challenges and constraints related to M&A transactions and make informed decisions. These considerations assist in developing a systematic approach to undertaking a Post-merger Integration (PMI) — which is devoid of any “gut decisions,” and ensures realization of synergies and value. These considerations set the direction and pace of the post-merger integration process.
Now, let’s discuss the 3 core considerations in detail.
Strategic Objectives
Organizations undertake Mergers and Acquisitions as a way to accelerate their growth rather than growing organically. The foremost core consideration associated with an M&A transaction is the strategic objectives that the organizational leadership wants to achieve out of it.
M&A deals take place to fulfill one or more of these 5 strategic objectives:
- Reinforcement of a segment
- Extension in new geographies
- Expansion of product range
- Acquisition of new capabilities
- Venturing into a new domain
The PMI approach needs to be tailored in accordance with the desired strategic objectives of the deal.
Organization & Culture
The senior management should be mindful of the significance of organizational and cultural differences in the two organizations that often become barriers to M&A deals. Small companies, typically, have an entrepreneurial outlook and culture where there aren’t any formal structure and the owner controls (and relays) all the information and decision making. Whereas, large corporations typically have formal structures and well-defined procedures.
A takeover of a small firm by a large entity is bound to stir criticism and disagreement. M&A process often faces long delays between the offer, deal signing, and closing — due to antitrust reviews or management’s indecisiveness — triggering suspicion among people. This should be mitigated during the PMI process by orienting the people of the small firm with the new culture and giving them time to transition effectively.
For M&A deals to be effective, leadership needs to carefully evaluate the behavioral elements of the organizational culture and contemplate the overriding principles guiding a company.
Takeover Approach
Integrating the operations of two companies proves to be a much more difficult task in practice than it seems theoretically. Organizations have the option of selecting the takeover approach most suitable for them from the following 4 methodologies — based on their organizational structures, people, management, processes, and culture:
- Direct Hit
- Hiatus
- Deferred Decisions
- Quick and Unsympathetic Disposal
Interesting in learning more about the takeover approach and the pre-merger considerations in detail? You can download an editable PowerPoint on Post-merger Integration: Pre-merger Considerations here on the Flevy documents marketplace.
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