64% of consumers believe that companies have a responsibility to solve climate and environmental issues.¹ These commitments align with broader international efforts, such as the United Nations’ Sustainable Development Goals (SDGs), which call for urgent action to create a more sustainable world.

Casting a company in a green light can be profitable: Products making ESG-related claims averaged 28% cumulative growth over a five-year period, compared to 20% for products without such claims, according to a 2023 McKinsey study.²

But what happens when sustainability claims are just for show?

Companies that try to reap the benefits of seeming sustainable without making actual change are greenwashing, or misleading consumers about environmental practices to benefit their public image.

When companies exploit consumers’ desire to make environmentally responsible choices, they challenge trust and undermine genuine sustainability efforts.

What is greenwashing?

Greenwashing, also known as green marketing or green sheen, is the act of communicating misleading or false claims to make a company appear more sustainable than they are in practice.³ 

For example, a company might tout that their clothing is “sustainably produced and shipped,” but still use synthetic fibers and non-recyclable packaging, among other unsustainable choices. In this case, there is a gap between symbolic gestures, like green logos or eco-labels, and substantive, day-to-day actions.

Companies achieve this misrepresentation through methods such as press releases about green projects or sustainability task forces, rebranding products or services, and advertising materials.

Dr. Victoria Hurth, fellow at the University of Cambridge Institute for Sustainability Leadership, says greenwashing can be deliberate or come from a place of ignorance. “In either case the idea of being ‘green’ is washed out of its meaning for those receiving the message,” Hurth explained.

Examples of greenwashing

Volkswagen’s “Clean Diesel” engine

One greenwashing example is the Volkswagen “Clean Diesel” engine scandal. VW heavily marketed new low-emissions diesel technology as more environmentally friendly than other gasoline cars.

In reality, Volkswagen was fitting their vehicles with a “defeat device” that reduced emissions during emissions tests. On the road, their engines emitted nitrogen oxide pollutants up to 50 times the legal limit in the United States.⁴ 

This led to a host of regulatory fines and several false advertising lawsuits being filed against VW, which cost the company $35 billion and resulted in millions of vehicles being recalled.⁵ Five years after the scandal, the company’s stock was still valued at 35% below its previous levels.⁶

In 2025, ten years later, courts are still ruling Volkswagen liable for the defeat devices and convicting former employees of fraud.^{7, 8}

H&M conscious clothing

Clothing brand H&M faced criticism from European watchdog organisations over its “Conscious Choice” collection – marketed using environmental scorecards and claims that products were made with more sustainable materials.

A 2022 Quartz investigation found that among the scorecards claiming an item of clothing was better for the environment, more than half were no more sustainable than comparable items made by the company and its competitors.⁹

The data for the scorecards comes from an industry-metric called the Higg Index. In a notice to H&M, the Norwegian Consumer Authority labelled the data as misleading and a breach of Norway’s marketing laws.¹⁰

That same year, H&M made commitments to the Netherlands Authority for Consumers and Markets (ACM) to adjust or remove sustainability claims from their website “in order to minimise the risk of misleading practices involving sustainability claims.”¹¹

How to spot greenwashing

It might feel easier for consumers to take sustainability claims at face value. As Hurth notes, “There is an incentive not to look beyond the surface of a green message – it can be like a silent agreement that buyer and seller have to enable actions they would otherwise feel bad about.”

Exercising due diligence can help shoppers spot deception and make an informed choice. Consumers can look out for vague terms and explore the company’s mission and supply chain to find out more information. There are also certifications from trusted organisations that can help verify a company or product’s sustainability.¹²

Why should companies care about greenwashing?

As the demand for green practices increases, many companies might opt for the easy way out by using greenwashing to appear environmentally responsible. However, appearances will only get businesses so far. Governments, regulators, and stock markets are pushing forward mandatory disclosures on environmental impact.

When companies engage in greenwashing, the consequences extend beyond the PR department:

• Erodes trust: When consumers realise they’ve been misled, their trust in the company can decline. 54% of consumers say that they would stop buying from a company if they were found to have been misleading in their sustainability claims, according to KPMG research.¹³

• Legal and financial liabilities: When companies deceive consumers with false or misleading claims, they open themselves up to regulatory punishment. Fines for breaking consumer protection laws and even criminal sentencing for fraud are potential outcomes for companies.

• Undermines genuine ESG efforts: Without clear and substantiated claims, the validity of other sustainability efforts can also diminish in the eyes of consumers. For example, 76% of consumers express skepticism about “green” labels on products.¹⁴ False claims water down the validity of genuine ones.

How to avoid greenwashing at your company

2 out of 3 consumers doubt that companies are genuinely committed to sustainability.¹⁵ How can you help change that in your own organisation?

• Use clear, specific language. Use precise language when making environmental claims and set realistic goals for future progress.

• Act first, share later. Prioritise progress over marketing those ambitions to customers. When companies make progress towards meaningful ESG goals, the PR can be more specific, data-driven, and confident.

• Track goals publicly. Commit to keeping your customers updated on your progress over time. One example is Microsoft’s Environmental Sustainability Report — detailed transparency can boost trust in your organisation.¹⁶

“As executives and citizens, we all have a role to play in directing, overseeing and accounting for investment that works for the challenges we face in reality,” Hurth said.

Professionals of all levels – not only those in leadership positions – need to take on the challenge of driving meaningful, sustainable change. To achieve this, workers can upskill with online sustainability courses.

The Business Sustainability Management online short course from the University of Cambridge Institute for Sustainability Leadership is geared towards working professionals who want to strengthen corporate social responsibility efforts and implement sustainability in their organisation. Over eight weeks, you’ll learn to develop and motivate an action plan for sustainable business practices and consider corporate sustainability in your organisation – affecting real change, not just greenwashing.

Deepen your knowledge of organisational sustainability with an online course.

CAMBRIDGE CISL
Business Sustainability Management online short course

FAQs

What is greenwashing in simple terms?

Greenwashing is when companies, either intentionally or unintentionally, make misleading or false marketing claims about their sustainability efforts or the environmental impact of a product.

Is greenwashing illegal?

Greenwashing tends to fall under consumer protection laws around unfair or deceptive marketing, which vary by country. For example, in the U.K., the Competition and Markets Authority oversees the “Green Claims Code” — guidelines that help businesses meet legal obligations when making environmental claims.¹⁷ In the United States, the Federal Trade Commission (FTC) has a similar perspective, called “Green Guides.”¹⁸

What is an example of greenwashing?

One example of greenwashing is when companies advertise a product as “100% natural” or “made from eco-friendly materials” without providing specific details or evidence that support these claims.

Why is greenwashing bad?

When companies engage in greenwashing, they can damage their reputation and relationship with customers, experience legal and financial punishments for breaking consumer protection laws, and undermine genuine sustainability efforts around the world.

The post Greenwashing: How to spot and stop false sustainability claims at your organisation appeared first on GetSmarter Blog.

Being a chief operating officer (COO) is a highly influential role, often second-in-command to the CEO. The COO is typically responsible for overseeing the company’s daily operations, turning the CEO’s long-term vision into actionable, efficient reality.

Given the strategic nature of the position, there are many legitimate paths to the C-suite. Success hinges less on following a rigid checklist and more on gaining the right blend of experience, educational depth, and proven executive capabilities.

What does a chief operating officer do?

The COO is the chief execution executive of a company, translating the high-level business strategy into operational excellence. This executive’s responsibilities are inherently fluid, changing based on the size of the organization, the industry, and the CEO’s style.

The COO’s job is to manage the resources, personnel, and logistics of the organization to ensure all business functions run efficiently and effectively. This often involves:¹

• Collaborating with the CEO to drive organizational vision and hiring
• Translating business strategy into actionable steps and implementing organization-wide processes
• Supervising daily operations to drive productivity and cost-effectiveness
• Overseeing financial management efforts like budgeting, cost management, and resource allocation
• Driving change management, and guiding the organization through transitions

In some larger organizations, the COO position is strategically used as a training and testing ground for the next CEO. However, the role is always a pivotal one, requiring extensive experience, critical thinking, and a sharp focus on continuous improvement.

Education to become a COO

There is no single required degree to become a chief operating officer, but a solid educational foundation is a consistent prerequisite. Many COOs hold degrees in business-related fields, which suggests that what matters most is acquiring a deep understanding of business administration, management, and strategic thinking.²

Undergraduate degrees for chief operating officers

A bachelor’s degree in a field like business administration or management can provide foundational knowledge in key areas like finance, marketing, strategic planning, and project management.

For those with an early interest, a major in a field like operations management can offer a specialized base in process optimization, resource management, and supply chain logistics, which are core to the COO role.

Graduate degrees for chief operating officers

Many COOs pursue an advanced degree to deepen their knowledge, which often contributes to the strategic mindset needed at the executive level.

• Master of Business Administration (MBA): An MBA provides a broad, analytical toolkit covering finance, data analysis, strategy, and leadership. This breadth is especially valuable because a COO must oversee various departments, from human resources to manufacturing.

• Specialized master’s degrees: Programs in finance or computer science can also set a strong foundation, but offer a more focused speciality.
  • A finance background equips a leader with the knowledge to make strategic financial decisions, understand cash flow, and manage cost and risk.
  • A technical degree may be beneficial in a tech-focused or manufacturing industry, offering deep expertise in the intricacies of that sector and positioning the executive to leverage technologies.

The decision often comes down to the individual’s existing career background and the type of company they aspire to lead. A specialized master’s may build on an existing strength, while an MBA often rounds out a professional’s expertise to prepare them for an organization-wide leadership role.

The best educational route is the one that complements your existing career trajectory and builds the skills needed for the specific type of organization you aim to lead.

Upgrading your skills to become a chief operating officer

The COO role demands a powerful hybrid of analytical competency and interpersonal leadership. Some examples of important skills include:³

• Strategic planning and thinking
• Data analysis
• Financial knowledge
• Project management expertise
• People management experience
• Problem solving and resilience

Online operations courses and online leadership courses can be one way to earn some of these skills on your own terms and timeline.

COO certifications

While there is no mandatory professional certification to hold the title, executive education programs and specialized credentials can signal a high level of expertise and commitment to executive operational leadership.

CAMBRIDGE CISL
Business Sustainability Management online short course

In an era where climate change, resource scarcity, and inequality are no longer fringe issues but central business concerns, the role of a COO must evolve to encompass sustainability. The Business Sustainability Management online short course offers the strategic and operational blueprint to highlight this fit and prepare for the C-suite.

CAMBRIDGE CISL
Communicating for Influence and Impact

COOs are translators, responsible for taking the C-suite’s strategy and articulating it into measurable, actionable steps across the entire organization. The Communicating for Influence and Impact online short course can help you become a master at this kind of strategic messaging.

THE LONDON SCHOOL OF ECONOMICS AND POLITICAL SCIENCE (LSE)
MBA Essentials online certificate course

A COO’s success rests on their ability to expertly manage strategy, finance, and people — the three pillars the MBA Essentials course dissects. Learn evidence-based approaches to using financial statements as diagnostic tools, managing the supply chain, and fostering a people-first work environment.

For COOs whose role is heavily focused on a specific operational domain, technical certifications can demonstrate a commitment to industry-recognized standards and expertise.

• Certified Supply Chain Professional (CSCP): Offered by the Association for Supply Chain Management (ASCM), this is a globally recognized credential for professionals managing end-to-end supply chain activities.⁴
• Six Sigma Green Belt or Black Belt: These credentials certify expertise in the Six Sigma methodology, which focuses on data-driven, problem-solving techniques to minimize defects and optimize business processes.⁵
• Program Management Professional (PgMP): Offered by the Project Management Institute (PMI), this certification is aimed at professionals who manage multiple, coordinated projects (a program) to achieve strategic objectives.⁶

A progressive career trajectory

The career path to COO is defined by a consistent, progressive accumulation of experience and a verifiable track record in operational and strategic leadership. Most successful COOs spend years rising through the ranks, demonstrating exceptional results at every management level, or are recruited for their deep history of operational excellence.

COOs come from diverse functional backgrounds, which only underscores the fluidity of the role:

• A traditional operations background provides a foundational understanding of process optimization and efficiency.
• A background in finance equips a leader with the crucial financial oversight and risk management skills needed for strategic decisions.
• A background in human resources provides deep expertise in organizational culture, talent management, and conflict resolution.

Seek out roles that provide cross-functional exposure and challenging, high-visibility projects. By consistently focusing on optimizing processes, driving execution, and cultivating the requisite leadership skills, you can strategically position yourself for this demanding executive role.

The post How to become a chief operating officer appeared first on GetSmarter Blog.

Recruitment or human resources (HR) managers know how difficult it is to find good employees; candidates either lack certain skills or they won’t fit in with the company culture. Business owners often focus on technical skills alone and don’t assess the qualities and characteristics that make up the ideal employee. This could end up adversely affecting culture, productivity, and may even protract training efforts.

Regardless of the industry or nature of the job, there are certain key qualities that hiring managers in all kinds of industries might look out for if they want their employees to succeed in the business world.

Key takeaways

• Both soft skills and hard skills are important for a good employee.
• The top core skills sought by employers in 2025 include analytical thinking, leadership, resilience, AI and big data, and talent management.
• Employee training and development can be a practical solution to address skills gaps in the current workforce.

What skills are employers looking for?

Both soft skills and technical skills, or hard skills, are equally important in an employee. Soft skills include the social expertise, personality and character makeup, communication skills, emotional intelligence, influence, and approach to work that an employee shows.

These serve to complement the hard skills — those abilities that have been learned and can be measured and quantified — and can make an employee more of an asset to a company.

The World Economic Forum’s 2025 Future of Jobs Report surveyed employers around the world to explore the exact skills and characteristics sought after. Some skills are seen as requirements for workers, deemed ‘core skills.’

In South Africa, core skills include analytical thinking, leadership, and resilience.

Top 5 Core Skills in 2025, South Africa¹

Globally, the top skills differ slightly. For example, 62% of employers in the UK identified creative thinking as a core skill in 2025. Other skills include motivation and self-awareness, technological literacy, and empathy and active listening.

Other skills were identified as ‘skills on the rise.’ These are skills employers expect to increase in importance over the next five years. In South Africa, top ‘skills on the rise’ include AI and big data, technological literacy, and resilience.

Top 5 Most Increasing Use Skills by 2030, South Africa²

8 skills and characteristics of good employees

Here are some of the top skills and characteristics of a good employee, combining today’s core skills and tomorrow’s sought-after skills in South Africa and around the world:

1. Analytical thinking

Analytical thinkers can break down complex problems and emerge with logical, data-driven decisions.³ These employees can find meaningful connections in data and help identify cause and effect relationships between data. Seven out of 10 companies consider it an essential skill in 2025, making it the most sought after quality in the World Economic Forum’s survey.⁴

Companies generate massive amounts of data, and employees who can analyze it effectively are invaluable. This skill leads to better strategies, more efficient processes, and a deeper understanding of business challenges.

Examples of analytical thinking in the workplace:

• Reviewing customer feedback to pinpoint areas for product improvement
• Using A/B testing results to optimize a website’s user experience
• Breaking down a complex project into smaller, manageable tasks

Economist Education
Critical Thinking: Problem-Solving and Decision-Making in a Complex World

2. Leadership and social influence

Leadership comprises a variety of skills that help create a sense of collective direction, confidence, and strategy. Good leaders can also wield their social influence to positively influence their team’s attitudes and behavior.⁵ Even without formal authority, these employees can build trust and push organizations towards a common goal.

Emotional intelligence plays an important role in these traits, too. Strong leaders are also compassionate and encouraging of others.

Examples of leadership and social influence in the workplace:

• Mentoring a new hire and helping them acclimate to the team
• Stepping up to resolve a team conflict constructively
• Leading a brainstorming session

Online leadership courses can help you develop specific management and interpersonal skills, such as conflict resolution and communicating for influence.

3. Resilience, flexibility, and agility

Resilience, flexibility, and agility include a variety of traits that center around bouncing back from setbacks, adapting to changing circumstances, and quickly navigating new challenges.⁶ Despite the stressors of the workplace, which could include anything from demanding economic conditions to rapidly shifting priorities, employees with these skills maintain their composure, efficiency, and problem-solving mentality.

Examples of resilience, flexibility, and agility in the workplace:

• Taking on a new role and responsibilities with a positive attitude
• Prioritizing tasks into a system based on what needs immediate attention
• Anticipating potential challenges and preparing contingency plans

4. AI and big data

Those who understand AI and big data know how to use technical tools to gain insights and automate tasks. It’s not just for data scientists; it’s about being literate in these technologies to improve your work.

Becoming comfortable with these tools will likely be necessary to keep up with shifting workflows and expectations: More than half of all LinkedIn members stand to see their jobs change in some way due to generative AI.⁷ Employees that have the technical know-how to engage with AI and big data tools deeply could be critical for companies that want custom solutions for their projects.

Examples of AI and big data knowledge in the workplace:

• Apply a machine learning model to predict customer churn
• Using a business intelligence dashboard to create a dashboard that tracks key metrics
• Writing an algorithm to automate a repetitive data entry task and save time

Online artificial intelligence courses can help you prepare for a changing workforce and expectations.

IBM
Generative AI Engineering

5. Talent management

Talent management is about attracting, developing, and retaining great employees.⁸ Workers with good talent management skills don’t need to work in HR to be positive forces in this area.

For managers, talent management could include the specific responsibilities that come with having direct reports — guiding professional development, onboarding new staff, and completing performance review, for example.

But even non-managers can exhibit talent management skills by helping cultivate an environment that rewards and supports talent.

Examples of talent management in the workplace:

• Helping to onboard a new employee and introducing them to the company culture
• Identifying an employee’s strengths and recommending them for a project where they can shine
• Establishing professional development goals with an employee and giving them time during the workday to pursue them

Yale School of Management Executive Education
Human Resources Leadership

6. Technological literacy

Technological literacy is the ability to effectively learn and leverage technology to solve problems and complete tasks. It extends beyond basic computer functionality to include things like new software, digital platforms, and online tools.⁹ Tech literate employees also demonstrate agility and speed when picking up new technical tools.

There are new technologies surfacing in the workplace constantly, but the most important tools in a few years may be things we don’t even know about yet. Businesses need employees who can not only adapt to rapidly developing tools, but help others do the same.

Examples of technological literacy in the workplace:

• Mastering a new project management software like Asana or Trello
• Troubleshooting a minor software issue on your own
• Discovering new technical tools that you can apply to your team’s workflow

7. Creative thinking

Creative thinking is the ability to come up with unique, innovative solutions to problems. In the workplace, a creative thinker can help challenge the status quo and improve products, processes, and services.¹⁰

Not all people are born creative, but creativity is a skill that can be learned through experimentation, imagination, questions, collaboration, and information processing.

Examples of creative thinking in the workplace:

• Proposing a new feature for a product to meet a customer need
• Discovering a new way to measure an initiative’s success
• Finding a low-cost solution to a budget constraint

8. Curiosity and lifelong learning

Curiosity and lifelong learning represent a desire to continuously seek out new knowledge, ask questions, and improve your skills.¹¹ These employees have a proactive mindset that drives their own professional growth.

Curiosity is also fundamental to project success: asking questions early and often can help identify hurdles before they happen and opportunities for improvement. When employees ask ‘why?,’ they can form a deeper understanding of their work.

Examples of curiosity and lifelong learning in the workplace:

• Taking an online short course to learn a new skill relevant to your job
• Seeking out feedback from managers and peers to identify areas for professional development
• Reading industry reports to stay informed about the latest trends

Recruiting vs. training

All over the world, businesses are seeing skills gaps emerging. In South Africa alone, more than 60% of businesses identify skills gaps as a key barrier to business transformation by 2030.¹² 

One possible solution is training existing employees to become proficient in new skills – both hard and soft — and in turn creating ‘good employees.’ This also means that a new approach is needed when recruiting. Hiring employees who show potential to be further skilled and who display some of the qualities listed above may be an effective tactic. 

Given that top talent is likely to become more and more scarce and in demand, employee training and development might well be the best and most practical solution.

Knowing what skills and characteristics to look out for, in existing employees as well as when recruiting new employees, will ensure that these desired qualities are nurtured and developed throughout the business, regardless of the job title or function. The skills of a good employee reach beyond technical acumen and business experience. While these are important to get the job done, how these tasks are carried out, and the interactions with other team members, are indicative of the attitude, approach, mindset, and adaptability of a good employee.

GetSmarter can guide you as your learning partner, and help your business to create a tailored upskilling plan to meet your unique needs.

[Empower your team with the right skills]

The post What are the characteristics of a good employee? appeared first on GetSmarter Blog.

Alternatively, a macroeconomic perspective might reveal that the entire city is experiencing a recession, leading to a general decrease in consumer spending across the board. In this case, the business owner’s problem isn’t their individual strategy, but a larger economic trend that requires a different approach, like seeking government assistance or preparing for a prolonged downturn.

By exploring both microeconomics and macroeconomics, we can gain a more complete understanding of how our daily lives are shaped by economic forces, from the price of a single cup of coffee to the health of the entire global economy.

Key takeaways

• Microeconomics focuses on individual markets and a ‘bottom-up’ approach, while macroeconomics studies the economy as a whole, using a ‘top-down’ approach.
• Micro- and macroeconomics are interconnected, with actions at the individual level influencing larger economic trends.
• Both fields are important for businesses. Businesses use microeconomic principles to understand consumer behavior and set prices. At the same time, they must consider macroeconomic factors, such as government regulations or economic cycles, when making strategic decisions.

What is microeconomics?

Microeconomics is the study of individual markets, exploring how supply and demand interact to affect prices and the economy via a ‘bottom-up’ approach.¹

This subset of economics aims to discover what factors contribute to peoples’ decisions, and what impact these choices have on the general market as far as price, demand, and supply of goods and services.

Factors like wages, employment, and income are studied in tandem with behavioral trends and corporate policies to identify patterns and predictive indicators. When microeconomists understand decision-making and resource allocation at the individual level, they can help explain what will happen to the economy if certain conditions change.²

Microeconomics aims to answer the following questions:

• How do people and households spend their money?
• What causes people to spend more or less money?
• What is a product worth to consumers?
• How can businesses use resources efficiently?
• What should businesses produce and how much?

Examples of microeconomics in 2025

Some recent examples of microeconomic analysis include:

• AI-driven pricing: Dynamic pricing models already exist, such as surge pricing on ride-sharing apps, but the rise of AI could lead to even more automation. Businesses can use microeconomic principles to optimize their pricing models in real-time, responding to individual market trends or consumer behavior immediately.³ This also poses new questions for microeconomists: How will consumer behavior change in response to AI pricing models?

• The experience economy: People are looking to spend their money on how they spend their time, like travel, outdoor experiences, and food-related experiences. Two-thirds of European consumers say checking off a bucket-list item is a top financial priority in 2025, according to a Mastercard survey.⁴ These changes in demand and priority can affect some basic microeconomic questions: What kinds of products should businesses offer consumers? And how much will consumers pay for them?

What is macroeconomics?

Macroeconomics is the study of holistic economies, exploring how large-scale factors like GDP and policy influence national and global economic trends via a ‘top-down’ approach.

This branch of economics aims to discover what factors contribute to the overall health and performance of an economy. Macroeconomists analyze major economic indicators like national income, interest rates, government spending, and tax policy to predict entire industry or global economic shifts.⁵

Macroeconomics aims to answer the following questions:

• What causes inflation and how can it be controlled?
• Why do recessions occur and how can governments respond?
• What stimulates economic growth at the national level?
• What should the interest rate be?
• How does the balance of trade affect a country’s currency value?

Examples of macroeconomics in 2025

Some recent examples of macroeconomic analysis include:

• Global supply chain resilience: Geopolitical tensions and changing trade dynamics can reshape supply chains, shifting production around the world and making entire industries reevaluate their processes.⁶ This is a study in macroeconomics: How does trade policy affect national economies?

• Sustainable development goals: The UN’s Sustainable Development Goals (SDGs) include massive global endeavors like ending hunger, ensuring clean water, and providing education for all by 2030.⁷ Reaching these SDG targets requires a macroeconomic mindset: How can governments deploy capital to achieve the greatest impact?

Comparing macroeconomics vs. microeconomics

Microeconomics and macroeconomics explore many of the same elements, but from different points of view. The main differences between them are:

• Macroeconomics studies holistic economies and microeconomics studies individual markets.

• Macroeconomics is concerned with the decision-making and policies of governments and global organizations. Microeconomics is concerned with the decision-making of individuals, households, and businesses.

• Macroeconomics studies high-level variables like GDP, inflation, and unemployment. Microeconomics studies lower-level variables such as supply, demand, and price.

How macroeconomics and microeconomics affect each other

Micro- and macroeconomics don’t exist in isolation from one another, but work in tandem to provide a complete understanding of economies at all levels. Choices based on microeconomic factors, whether from individuals or businesses, can impact macroeconomics when scaled up.

Some examples of how micro- and macroeconomics interplay include:⁸

Micro: The COVID-19 pandemic causes consumers to slow spending and save more money. Businesses lay off employees to cut costs and account for slower revenue streams.

Macro: The national unemployment rate rises.

Macro: Tariffs on global goods raise the price of importing manufactured products.

Micro: Businesses raise prices on goods to bridge the gap and consumer demand fluctuates.

How micro- and macroeconomics affect business

• The law of supply and demand
  Businesses use microeconomic principles to better understand the behavioral patterns of their consumers, in order to be successful and generate a profit.⁹
• Decision-making
  Large-scale external factors can be uncontrollable and still play a role in influencing a company’s performance and strategy. From microeconomic factors like a competitor’s choices and industry-specific cost changes, to larger macroeconomic factors like government regulations or climate change are all important to consider.
• Start-ups
  When starting a business, it is important to do extensive research into the industry in which you are interested. Know where customer demand is, to better provide and develop the products and services that would best match the needs of your target market. Investing in this microeconomic research can help you reach a competitive advantage to attract customers.
• Economic cycles
  Macroeconomics is cyclic; just as positive influences and changes promote prosperity, higher demand levels may trigger price increases, which may, in turn, dampen the economy, as households adopt leaner budgets. Then, when supply starts to outweigh demand, prices may go down again, leading to further prosperity, until the next cycle of economic supply and demand.¹⁰
• The cost of goods and services
  Regardless of what a business produces, the goal is usually to keep costs down in order to improve profits. In microeconomic theory, companies run at the highest level of efficiency, with production decisions based on how the maximum output can be achieved with minimal extra costs. So, for example, if production is ramped up, a need for extra labor may arise, resulting in the wage costs increasing, and a potential change in sales prices. In microeconomics, the cost of labor is typically the highest expense of a business.
• Pricing decisions
  In microeconomics, the price where quantity supplied meets the quantity demanded is known as the ‘equilibrium price’. The decided price of the product or service will impact on the number of people willing to buy it. For example, setting a price above the equilibrium doesn’t always mean greater profits, as fewer people may opt to buy your product, therefore, the price of the product should match your target market’s budget.¹¹

In order to make balanced, informed business decisions, it is important to take local and global economic trends into account, as well as relevant data and interactions with your customers. Look for opportunities that arise from economic trends, both on a micro- as well as a macroeconomic level.

Learn more about the effects of individual decision-making and larger economic systems with online economics courses on GetSmarter. Personal finance courses online can also help you understand how your individual choices interact with broader markets.

MIT Sloan School of Management
Economics for Business

THE LONDON SCHOOL OF ECONOMICS AND POLITICAL SCIENCE (LSE)
Economics for Public Policy

THE LONDON SCHOOL OF ECONOMICS AND POLITICAL SCIENCE (LSE)
Health Economics and Policy

THE LONDON SCHOOL OF ECONOMICS AND POLITICAL SCIENCE (LSE)
Real Estate Economics and Finance online certificate course

The post Microeconomics vs. macroeconomics: What’s the difference? appeared first on GetSmarter Blog.

The world is driven by data, and it’s being analyzed every second, whether it’s through your mobile GPS, your Netflix habits, or the items sitting in your online shopping cart. Every business sector looks to data for market insights and ultimately, to generate growth and revenue. 

Choosing the right type of data analysis for your task, and the techniques and tools to go with it, is an important step. Keep reading to learn more about how data analytics is used to take massive amounts of information and make predictions and decisions.

Key takeaways

• The amount of data being generated is growing at an unprecedented rate, with 90% of the world’s data being created in just the last few years.
• There are four main types of data analysis — descriptive, diagnostic, predictive, and prescriptive — each serving a unique purpose, from understanding what happened in the past to recommending a course of action for the future.
• There are a variety of techniques to help you accomplish data analysis techniques, from data visualization and A/B testing, to machine learning tactics like NLP and decision trees.

What is data analysis?

Data analysis, or data analytics, is the process of applying logical and mathematical techniques to datasets in order to discover patterns and useful information, often to aid in decision-making.³ 

It’s often used on an industrial scale, helping organizations make calculated and informed business decisions. As the Internet of Things (IoT) expands and technology develops, new forms of data mining and analysis are constantly emerging.

Big data is characterized by the three V’s: Volume, the massive scale of data; velocity, the speed at which it’s generated and processed; and variety, the wide range of structured and unstructured data formats.⁴

Velocity is particularly important, as the need for real-time analysis has led to the integration of big data with advanced technologies like machine learning and artificial intelligence.

What are the types of data analysis?

The different types of data analysis provide a structured approach to gaining insights from data, moving from understanding what has happened to predicting what will happen and, finally, prescribing a course of action. The four main types of data analysis are:⁵

Descriptive analytics: Summarizes historical data to explain what happened. This could include generating reports, KPI dashboards, and summaries. It helps you understand the past and present state of data.

Diagnostic analytics: Focuses on historical data to determine why something happened. It involves techniques like regression analysis and A/B testing to find the variables that lead to a specific outcome.

Predictive analytics: Uses statistical models and machine learning to forecast what is likely to happen in the future. It can be used for tasks like sales forecasting, risk assessment, and identifying behavior trends.

Prescriptive analytics: Recommends what should be done to achieve a desired outcome. It leverages advanced techniques like simulation and natural language processing.

10 examples of big data analytics techniques

Big data analytics techniques function in a two-fold manner: processing data streams as they emerge and performing batch analysis on data as it accumulates to identify patterns and trends. As data generation accelerates, these techniques must evolve to handle the speed, scale, and depth of information.

1. Data mining

Data mining extracts patterns from large data sets by combining methods from statistics and machine learning, within database management. Today, it is increasingly automated and integrated with AI, allowing for more complex pattern detection.⁶

• Tools: Data-mining tools include programming languages like Python or R, and proprietary tools like KNIME and RapidMiner, which offer visual workflows and pre-built algorithms.

• Example: A retail company might use data mining to analyze customer purchasing histories and identify which segments are most likely to respond to a new product promotion.

2. Data visualization

Data visualization is the graphical representation of data and information. Through visual elements like charts, graphs, and dashboards, analysts communicate insights and help stakeholders make decisions. It can also make complex data understandable and accessible to non-technical users.⁷

• Tools: Data visualization softwares like Tableau and Power BI are powerful packages with built-in charting tools. There are also coding libraries that can power highly-customized visualizations, like D3.

• Example: A business dashboard can display real-time sales data using a line chart to show a trend over time or a heat map to show customer density.

3. Cluster analysis

Cluster analysis is a type of data mining that uses unsupervised machine learning in order to group data points into distinct clusters based on their similarities. The goal is to identify hidden groupings or structures within the data without any pre-existing labels.⁸

• Tools: Common tools and libraries for cluster analysis include Scikit-learn in Python and R.

• Example: A bank might use cluster analysis to segment customers’ behavior and detect fraudulent transactions by identifying groupings of unusual activity.

4. A/B testing

This data analysis technique involves comparing a control group with a variety of test groups to discern what changes will improve or change a given objective variable.⁹

• Tools: Software and platforms like Adobe Target, A/B Smartly, and VWO offer features for creating, monitoring, and analyzing a variety of web-based A/B tests.

• Example: A marketing team could use A/B testing to determine which website layout or ad copy leads to the highest number of conversions.

5. Regression analysis

Regression analysis is a statistical method for estimating the relationships among variables. It’s used to understand how the value of a dependent variable changes when one of the independent variables is varied.¹⁰

• Tools: Statistical software like SAS and SPSS, and programming languages like R and Python are used for regression analysis.

• Example: A real estate agent could use regression analysis to determine the relationship between house size and selling price.

6. T-tests

A t-test is a statistical hypothesis test used to determine if there is a significant difference between the averages of two groups. It helps to see if they are genuinely different or if the observed difference is due to chance.¹¹

• Tools: T-tests are available in statistical software like R and Python’s SciPy library.

• Example: A teacher could use a t-test to compare the average test scores of students who tried a new study method versus those who tried an old method, to see if there is a meaningful difference in their performance.

7. Machine learning

Machine learning automates model building for analytics. It enables computers to automatically learn from data without explicit programming to make inferences, predictions, and recommendations.¹²

• Tools: Popular tools and platforms for machine learning include Databricks, KNIME, and cloud-based services like Google Cloud AI and Amazon SageMaker.

• Example: Machine learning can be used by banks to detect fraud and identify suspicious credit card transactions automatically.

8. Time-series analysis

Time-series analysis is a statistical technique that analyzes data points collected over a period of time. The goal is to identify patterns, trends, and seasonal changes in the data.¹³

• Tools: Some tools for time-series analysis include Python libraries like Pandas, Statsmodels, and specialized platforms like Amazon Forecast.

• Example: Weather forecasters might use this kind of analysis to predict future weather conditions based on past temperature, pressure, and wind patterns.

9. Decision trees

Decision trees are a type of supervised machine learning algorithm that can be used for both classification and regression. It works like a flow chart, identifying optimal split points based on feature values to create pure subsets.¹⁴

• Tools: Decision-tree algorithms are implemented using various machine learning libraries, including Scikit-learn in Python and R.

• Example: A business could use a decision tree to predict whether or not a customer will buy a product, based on factors such as previous purchasing history, age, and location.

10. Natural language processing

Natural language processing (NLP) is a subset of AI and machine learning that uses algorithms to analyze, understand, and generate human language. Large language models (LLMs) and generative AI enable tools to process massive amounts of unstructured text data, such as emails, social media posts, and customer reviews.¹⁵

• Tools: Popular NLP tools include programming libraries like NLTK and spaCy, and the IBM Watson platform.

• Example: NLP is used for machine translation services, like Google Translate, to process input text and return that same information in a number of different languages.

Learn how to sort, analyze, and interpret data to inform business strategy with data analysis short courses on GetSmarter.

University of Cape Town (UCT)
Data Analysis online short course

THE LONDON SCHOOL OF ECONOMICS AND POLITICAL SCIENCE (LSE)
Data Analysis for Management online certificate course

Rice Glasscock
Data Analysis and Visualization online short course

THE LONDON SCHOOL OF ECONOMICS AND POLITICAL SCIENCE (LSE)
Applied Data Visualisation and Analysis for Business

The post Big data analytics techniques and types appeared first on GetSmarter Blog.

When implemented effectively, business process modeling can transform project management challenges into opportunities for shared understanding, innovation, and success.

Fundamentally, business process modeling involves identifying, defining, and representing a process in its entirety, in order to aid communication of that process. 

The visual references and diagrams used in modeling systems can help you:

• Identify tasks that are redundant and remove them
• Spot bottlenecks in the process and improve process efficiency by eliminating them
• Identically repeat processes and train new staff to do so

There are several techniques in business process modeling:

1. Business Process Modeling Notation (BPMN)

The Business Process Model and Notation (BPMN) is the global standard for modeling business processes. It is composed of a system of graphical notations used to visualize end-to-end tasks and workflows. Designed for stakeholders who manage and design business processes, BPMN emphasizes a combination of ease-of-use and specificity to meet the different needs of global organizations.¹

Strengths:²

• Individual organizations don’t need to invent their own visual system
• A standardized language helps close communication gaps between stakeholders
• Includes a library of process flows and rules to train new employees on
• Can be created using online tools like LucidChart and Visio

Limitations:³

• The highly rigid framework can make process innovation more complicated
• Challenging for first-time users to read
• May not be flexible for certain dynamic and non-sequential processes

BPMN symbols fall into the following basic categories:⁴

• Flow objects. The main elements that define a process are broken into three types of objects:
  
  • Events are displayed inside circles. These are things that “happen” during the course of a process and usually have a cause and impact.
  • Activities fit into rectangular boxes. This represents the work performed within a process.
  • Gateways are represented as diamond shapes. These are used to control how the process flows and either converges or diverges.

• Connecting objects. Show how tasks are connected and in what sequence they occur.
  
  • Sequence flows are displayed as solid lines. These depict the order of activities.
  • Message flows are displayed as dashed lines. These depict the transfer of information between participants.

• Swimlanes. Make provisions for partitioning a set of activities from others. They comprise “Pools” and “Lanes”.

• Artifacts. Provides additional information that isn’t captured in a sequence or message, but does not directly affect the process.⁵
• • Groups use dot-dash rectangles to logically relate components.
  • Text annotations are displayed inside square brackets.
  • Associations link text annotations to other elements via dotted lines.

2. Unified modeling language diagrams

Unified modeling language (UML) is a general-purpose approach to visually modeling and documenting processes. UML was initially developed by software developers, but has been successfully used in business process modeling.

It uses 14 types of diagrams to display an object-oriented approach to process visualization. This means that objects are modularized to include things like class, inheritance, and polymorphism. The types of diagrams are split into two categories: behavioral and structural, which display the dynamic and static aspects of a system, respectively.⁶

Strengths:⁷

• Popularity among software developers makes it highly recognized and interpretable for teams
• Versatile enough to model processes, applications, and software engineering projects
• Can use tools like LucidChart, Visio, and Draw.io

Limitations:

• Can have a steep learning curve to understand the different diagrams and object types
• Some aspects of the design can lead to ambiguity and different interpretations
• Diagrams can become overly complex for large systems

3. Flow chart technique

This is a generic graphic representation of a process, product, or system, which gives people involved in the project a single reference point. Flow charts use basic shapes and arrows to define relationships between steps, decisions, or data.⁸

Strengths:

• Highly flexible without prescriptive shapes and visual systems
• Intuitive and easy to understand

Limitations:

• Difficult to draw for large and complex processes
• No standard language for general flow charts

4. Data flow diagrams

Data flow diagrams (DFDs) show the flow of information through a process. Using pre-defined symbols, DFDs visualize data inputs, outputs, storage points, and routes. The symbols generally fall into four types:⁹

• External entities are represented using squares. These are outside systems that are either the source or destination of data.
• Process is shown using rounded rectangles. These are any steps that change the data and produce an output.
• Data stores are visualized using open-ended rectangles. These are files or repositories that hold information.
• Data flow is represented via arrows. This is the route that data takes between the external entities, process, and data stores.

Strengths:

• Well suited for analysis and modeling data-heavy systems
• Help manage cybersecurity risks

Limitations:

• Less applicable for interactive or real-time software
• Limited scope and does not apply to more general business processes
• Requires technical knowledge of the data flow to create

5. Role activity diagrams

Role activity diagrams (RADs) are used to map out the intangible roles or ideas of behavior that are desired within the company. These can often be functions within the business, systems in IT, or customer and supplier roles.¹⁰

Strengths: 

• Easy to read and understand
• Provide a different perspective on a process

Limitations:

• Limited to mapping roles and behavior, not all processes

6. Interaction diagrams

A component of UML, interaction diagrams are business process models that graphically illustrate the interaction of various processes with each other within a system. Interaction diagrams come in two forms: sequence diagrams and collaboration diagrams.¹¹

Strengths: 

• Helps describe the flow of messages within a system
• Great for illustrating collaborations
• Identify possible connections between lifeline elements

Limitations:

• Not great for a precise definition of certain behaviors

There are two types of interaction diagrams typically used to capture the various aspects of interaction in a system:

• Sequence diagrams. A sequence diagram shows the interaction between objects in the sequence in which they take place. Sequence diagrams describe how the objects function within a system, and in what order, and are often used to document and understand what is required for new and existing systems.

• Collaboration diagram. Collaboration diagrams are used to define and clarify the roles of the objects that carry out a certain flow of events in a visual format, and serve as the main source of information when determining class responsibilities and interfaces.

7. Gantt charts

Gantt charts are a popular business process model for companies preparing for projects with distinct timelines, or that have time-sensitive processes that need to be captured and tracked. A Gantt chart plots a vertical list of tasks along a series of aligned, horizontal timelines. Each bar along the timeline represents the anticipated start and end date for a tasks, as well as its current status or progress.¹²

Strengths: 

• Quick overview of who is responsible for each task and when
• Easy for people involved in different parts of a process to see when they are meant to start and finish work
• Visualizes the whole project at once

Limitations:

• Includes little to no details on project scope and finances
• Does not visualize interactions between tasks or the overall shape of a process flow

8. Integrated definition for function modeling

Integrated definition (IDEF) for function modelling displays when parent activities give rise to child diagrams. There are 15 forms of IDEF and each addresses a different type of flow for functions, information, data, simulation model design, process description capture, and so on.¹³

Strengths: 

• Easy to understand, even without technical knowledge
• Useful for defining the scope of analysis

Limitations:

• Framework is very rigid to each use case

9. Colored Petri nets

When a system has numerous processes that interact and synchronise with each other, then colored Petri nets are ideal. This modeling technique is used to design, specify, simulate, and verify systems.¹⁴

Petri nets are unique in that they can represent both a state, such as passive, unsent, or waiting, and an action, such as send, receive, or transmit, in the same diagram. Colored nets use colors to differentiate their symbols, and use a formal, mathematical representation with well-defined syntax and semantics.

Strengths: 

• Mathematical foundations make it suitable for rigorous analysis
• Works well for concurrent activities

Limitations:

• Complexity can be difficult for beginners

10. Object-oriented methods

The object-oriented method of business process modeling is more than just modeling with objects: it encompasses message-passing, encapsulation (where internal detail is hidden), inheritance from class to subclass, and polymorphism (where the same procedure can operate on different data types).¹⁵

Strengths: 

• Modular structure promotes ease-of-use
• Features like inheritance make reusability easier

Limitations:

• More applicable for software development processes than general business processes

Think more strategically about your business process designs

Which business process modeling technique will you select for your business? Find the one that will ensure those involved in the system or process carry out their tasks in a consistent and efficient way, producing a predictable, measurable outcome.

Register now and join one of our project management courses or business management courses to learn more about the different types of process modeling available to your business.

MIT Sloan School of Management
Business Process Design for Strategic Management

University of Cape Town (UCT)
Foundations of Business Management online short course

Saïd Business School, University of Oxford
Oxford Leading Strategic Projects Programme

University of Cape Town (UCT)
Advanced Project Management online short course

The post 10 types of process modeling techniques explained, with examples appeared first on GetSmarter Blog.

In today’s dynamic and competitive business environment, it’s vital to update your management skills if you’re set on building your career.

The London School of Economics and Political Science (LSE) offers you the chance to do this, with the MBA Essentials online certificate course. During this 10-week course, you’ll increase your strategic, managerial, and leadership skills by focusing on three important principles: Business strategy, key financial knowledge, and human behavioural insights. Watch the testimonial video to hear what past participants thought of the course.

How the LSE MBA Essentials students benefit from an online learning platform

The course helped these participants improve their performance and learn to lead with influence. Here are their testimonials:

Giseli B.

Global Finance and Operations Lead, Dell Technologies

“I’m very satisfied with the overall experience of the LSE MBA Essentials course. The course content was well-structured, relevant, and thoughtfully curated, offering a solid foundation across key business areas. I particularly appreciated how the modules balanced theoretical frameworks with practical application, making the material highly engaging and immediately useful. The online learning experience was smooth and intuitive. The platform was user-friendly, and the combination of video lectures, interactive elements, and real-world case studies helped reinforce key concepts effectively. The pacing of the course also allowed for flexibility while maintaining a strong sense of progression.”

Hiba J.

CEO, Co-Founder, WETRAIN

“The overall impression about the content is simply outstanding and very comprehensive. The online experience is unmatched by any online course taken whether short or long – the GetSmarter and LSE online campus provides easy to follow and systematic approach that supported the learning experience regardless of technology savviness. The group discussions and moderators allowed for easy networking and unbelievable insights from a global network of experienced individuals. Whether anyone is looking to enhance their skill set or simply look for an up-to-date learning experience to further a new career; this course is simply on point. Thank you is a major understatement. Looking forward to more executive courses.”

Carolina F.

Partner and CBDO, T&C Consulting

“I really enjoyed the online learning experience. It worked perfectly for me because I could adjust everything to my own schedule and time zone. That flexibility made it much easier to stay committed and keep up with the modules. The topics were very useful, and I loved the way they were introduced and explored through the readings and videos; everything felt carefully chosen and easy to connect with. It made me want to keep going, and I found myself really looking forward to each new module. What I appreciated just as much was learning from everyone else in the course. The discussion forums were full of rich, interesting perspectives. Hearing from classmates with different backgrounds, cultures, and experiences opened my mind and added so much value to the whole experience. Overall, this program was fantastic.”

How the LSE MBA Essentials course helped leaders drive their business to stay ahead

Akos J.

Director, Global Compensation and Benefits, Tetra Pak

“The MBA Essentials course provided exactly what I was looking for. It gave me confidence and a refresher in corporate strategy and finance topics, and very sound and solid theoretical knowledge on leadership. The opportunity to engage with other classmates in the forum discussions provides a perfect platform to exchange ideas and challenge each other’s thinking process. The online tool experience is amazing. I had no issues and it’s super user-friendly. The overall course experience is something I can highly recommend to any fellow business leader who doesn’t have the resources (time or financial) to invest in a full MBA programme.”

Marouan L.

Manager, Financial Services, Customer, and Operations Consulting, PwC Greece

“This was a great learning experience. The material was of excellent quality and adapted to professionals who need to gain high-level knowledge in various subjects of business and management. The quizzes and written assignments were smartly designed. The discussion forums with like-minded individuals and tutors were very interesting. I think I have learned a lot through this journey and gained confidence in various subjects. The online learning design and support were great. Overall, it was an excellent experience that I would recommend without any reservation to persons who wish to boost their knowledge and careers.”

How the LSE MBA Essentials course helped professionals improve their current role and future potential

David L.

“Overall, I considered the course good value for money as one can see the amount of resources and effort that has been put into designing the material and format. I think the course will add value to my career prospects as I hadn’t previously had much formal exposure to the financial aspects of business management. Anybody who has experience of running budgets, but hasn’t had any significant formal financial business training, will find the course useful. It explains many of the reasons as to why we do a whole host of budget tasks, but perhaps have never been told why we do them.”

Liliana A.

Consultant, ICON-INSTITUT Public Sector GmbH

“The course is of superior quality both through the delivery of modules and interactive activity. By way of exposure, quality, and quantity of information, the course can be accessed by people with or without management experience. Responses are supervised and verified by professionals who provide you with useful feedback. The course is good value for money. I’ve explored new ideas and issues with people from different countries on different topics, supervised by professionals […] and have updated [my knowledge] with new trends in the financial and management field. This course will increase my career opportunities, especially in the private business area. I recommend this course for those who want professional development, but also for networking.”

Guy H.

“For me, the notes and content were ultra clear and well structured. I thought this quality was maintained consistently throughout the 10 modules, with great support from the GetSmarter team in the background. The GetSmarter online learning platform also performed well in that I never had any connectivity problems or ‘slows’, based here in London. There was a fair spread of topics, well balanced between the hard and fast ‘nuts and bolts’ of figure work, and the more diffuse aspects of customer behavioural psychology, and working with corporate culture. I also found plenty of takeouts in that an article or video we were referred to was in a clump of other related articles and videos that were also worth looking at. Importantly, it gave [me] the opportunity to apply theory to practical examples in case-study format, as well as relate previous work experiences to principles that were new to me. A well-constructed and worthwhile course from LSE.”

How the LSE MBA Essentials course provided practical takeaways

Rafael H.

Vice President, Mobility Key Accounts & Special Project, Siemens UAE

“[This is an] excellent course, which includes many practical examples that are relevant and useful in daily work. It helped me gain additional insights into peoples’ behaviours, influencing tactics, market views, and strategic directions. I’ve definitely enhanced my knowledge and feel very motivated to focus on my next career step. I highly recommend this course, especially for busy professionals!”

Santiago E.

Financial Lead, Vodafone Spain

“The course has been a fantastic experience from both a professional and personal perspective. I’ve developed a series of skills that today are essential for the management of any team, which I’m sure will allow me to move to a bigger role within my company. I also highlight the fact that upon finishing the course, you receive a certificate from the London School of Economics and Political Science, which is something that many people would like to see in their curriculum. I encourage anyone with a desire to continue developing their professional career to take this course. It’s been an incredible experience of very high quality, where I had the opportunity not only to learn, but also to meet people from all over the world.”

Courtney B.

Senior CRM Manager, HSBC Australia

“This course has reinvigorated and motivated me considerably over the past three months. I’ve learned so many interesting concepts covering economics, finance, and management that I would have never been exposed to in my marketing career. The continual assessments ensured I stayed on top of my learning every week, and couldn’t put it off and cram for one essay at the end. I believe I’ve absorbed a lot more of the content this way. Despite being in Australia, the time difference had no impact. I could respond to my peers in forums at any time during the week. I would highly recommend the LSE MBA Essentials course to anyone who is looking to challenge themselves and take their career to the next level.”

Who you’ll learn from

Now that you’ve heard from past participants, meet the convenors you’ll learn from throughout the course. The Course Convenor and Co-Designers are expert LSE faculty who have designed this online certificate course to provide you with an enriching, supportive learning experience. You’ll benefit from their vast experience and knowledge in the fields of business management and leadership.

Course Convenor

Dr. Connson Locke

Professorial Lecturer in Management, LSE

Connson joined LSE in 2008 from the Boston Consulting Group and her areas of expertise are leadership, negotiation, decision-making, and organisational behaviour. She is part of the academic leadership team for the Executive Global Master’s in Management, LSE’s cutting-edge alternative to an MBA, and also teaches the School’s most successful executive course on campus: Achieving Leadership Excellence. Connson holds a PhD and MSc in organisational behaviour from the University of California, Berkeley, and a BA in sociology from Harvard University. Her research interests include gender and leadership, diversity, and organisational culture.

Course Co-Designers

Dr. Jordi Blanes I Vidal

Associate Professor of Managerial Economics and Strategy, LSE

Jordi has been associated with the LSE for over 17 years, having completed his Master’s and PhD, both in Economics, at the School. In addition to being the associate professor of Managerial Economics and Strategy, he also teaches on the Executive Global Master’s in Management programme. He is an expert in organisational economics, leadership, human resource management, and the political economy. Before joining the LSE academic team, Jordi was a Prize Research Fellow at Nuffield College, Oxford University, and a visiting scholar at the National Bureau of Economic Research.

Dr. Barbara Fasolo

Associate Professor of Behavioural Science, LSE

Barbara is an associate professor of Behavioural Science at LSE and the programme director for LSE’s Executive Master’s in Behavioural Science. She received her Bachelor of Social Science degree in Italy with distinction and followed this up with a Master of Science degree, again with distinction, at LSE. An expert in choice processes and choice architecture, she has multiple publications in both peer-reviewed academic journals and media outlets, such as the Harvard Business Review. Barbara is the head of the LSE Behavioural Research Lab and is a member of various behavioural science and decision-making associations.

Khamid Irgashev

Chartered Accountant; Lecturer, LSE

Khamid is an ACA and ACCA chartered qualified accountant with considerable experience in various industries, including financial services (banking and insurance), retail, manufacturing, and publishing. Khamid also has a plethora of experience in coaching and leadership, has a Postgraduate Certificate in Higher Education, and is a fellow of the Higher Education Academy. In addition to his role at LSE, he is an assistant professor at Hult International Business School and a visiting lecturer at West London College. Over the past six years, he has had a leading role in teaching, coaching, and people management at LSE, Edinburgh Business School, University of London, and Hult International Business School.

While working your way towards an LSE certificate of competence, you’ll:

• Discover principles and techniques to effectively influence colleagues at all levels of your organisation
• Understand key economic principles and market forces that drive any business as you learn about the interaction between supply and demand
• Identify competitive advantage and how this is created as you discover the connection between the industry value chain and value creation
• Explore how to use financial tools such as budgeting, cost-volume-profit analysis, costing methods, and investment appraisal techniques to make better business decisions
• Learn to analyse financial statements and annual reports, using ratio analyses and financial insights to gauge the financial performance of a business
• Explore the advantages and disadvantages of vertical integration and horizontal expansion in business
• Improve your financial expertise as you explore the principles of financial accounting, identifying how various stakeholders use financial information
• Gain awareness of common decision traps that leaders fall into and how to become a better decision-maker
• Learn how to influence your peers and decisions made by consumers with nudging techniques as you explore the concept of choice architecture
• Investigate the dynamics of organisational change and culture, and the relationship between culture and leadership

As a world-leading social science university, LSE has 125 years of experience providing working professionals with the skills and confidence to enhance their personal impact.¹ Over this time, 16 Nobel Prize winners and 34 world leaders have taught or studied at LSE. This is your opportunity to learn from eminent thought leaders on an LSE course as you grow your global business network.

Are you ready to elevate your career? 

Register now to gain key leadership and strategic skills.

THE LONDON SCHOOL OF ECONOMICS AND POLITICAL SCIENCE (LSE)
MBA Essentials online certificate course

The post Student testimonials: Is LSE MBA Essentials worth it? appeared first on GetSmarter Blog.

Companies have access to more consumer information than ever before. However, the volume of data available raises the question of how and where to source the best information, and at what cost.

Transcript

We are in a world where there is more information about consumers than ever before.

So, have you ever wondered how companies decide where to locate a new supermarket or maybe how governments know exactly when to build new roads, schools, hospitals, and houses? Where and how do they get the information to know where to add new resources to an economy? Secondary data is data that is already available and would have been collected for purposes other than solving your particular research problem.

There are two main sources of secondary data. One of which is often sitting under our noses. If you work for a company or an organisation, it is likely that there is already an array of data to access. This is called internal data.

Increasingly, companies are sitting on a wealth of data that is collected by different parts of the organisation in the normal course of business.

For example, information about sales: when it comes to transactions, a company should know to whom and to which locations these are taking place. Companies may be sitting on valuable information gathered from research and surveys which had been carried out previously. Other forms of information could include point-of-sales data, website activity, or even apps.

These days, many companies often record information gathered from complaints or queries from customers.

External sources of data is data found outside the organisation and is made up of all available data in a wide variety of reports. For example, an organisation may be part of a trade body representing an industry, car manufacturers for example, which may have a wealth of information related to that particular industry already.

Then there is Stats SA, which publishes hundreds of reports every year. It’s everything from spending to health. Other sources of external data include libraries, information collected by government departments, textbooks, journal articles, and many, many more, which are easily accessible via the web.

Although it will take you some time to find the information you need from secondary sources, it will inevitably be much quicker than conducting new research yourself.

The post Interpret the Need for External and Internal Data Sources appeared first on GetSmarter Blog.

Consumer and market data provides valuable insights to decide the strategic direction of your business. However, innovation in the tech industry has resulted in most data being collected online, calling into question its authenticity and validity. As a marketer, you need to find new ways to validate secondary data to ensure it can inform high-level decision-making.

Transcript

I think some of the challenges we have are trying to keep ahead of the industry or at the same speed. And when I talk about the industry, I mean the tech industry and the way that people communicate. So we need to intersect those conversations. We need to be using platforms that consumers more readily use.

Some of the challenges around innovation, and this always comes up as you’re starting to move quite aggressively forward from a data collection perspective, is issues about reliability – issues about validity of the data that you’re collecting – because you’re now doing it through, in a lot of cases, in an online way – you don’t necessarily see the consumer in-person. So it’s about making sure that the integrity of what you’re doing remains true. We all know about issues around fake news, fake accounts… you need to be certain as to who you are actually talking to and finding a way to actually validate the data that you’re truly collecting.

In a lot of ways, the technology leads our innovation, and the way that people now engage with technology and the way that they consume technology as well as products, and the way that they interact is now forcing us as an industry to move forwards. So we’re kind of almost following, not necessarily innovating as much, purely from a data collection perspective. But it’s really about how can we make sure that the tools we have, the information that we’re collecting remains relevant, remains valid, and remains truthful to what we’re trying to understand.

The traditional model of market research was: the value lay in the data. Just the ability to be able to connect information had value, had intrinsic value, because no one knew anything. The cost of data and collecting that data was your primary driver in the industry. Now, with the advent of technology and the way that we’re moving with technology, we are now able to get it in far more cheaper ways through online platforms. You can do research in Zambia from an apartment in Moscow, for example, you don’t have to physically be there. This is fundamentally changing the nature of our business. We’re overwhelmed by the volume of data, because we have so many platforms and so many sources for us to be able to get data.

We can get primary data from the actual collection of the information from an individual. And we have huge volumes of secondary data, be it either social data or be it consumer data that our clients readily collect. The market research industry has had to reinvent itself in a lot of ways. Its value is not in its ability to be able to collect data, its value is what it does with that data. And the impact that that data has on its client’s business.

The post Explore the Challenges of Data Collection appeared first on GetSmarter Blog.

Data analysts play a key role in helping business leaders make informed choices. By collecting, storing, and analysing data, a data analyst can help distinguish between effective and ineffective practices, identify cost-cutting measures, and recommend solutions to key problems.

Transcript

With the start of the Fourth Industrial Revolution, businesses are presented with a significant problem: how do they appropriately collect, store, and analyse the large volumes of data that are retrieved from multiple departments in the company? Technological advances have made it much easier for data collection to occur. And this advancement is set to continue for the foreseeable future. This has led to an increased need for data analysts.

The key function of a data analyst is to extract relevant insights from data to inform business decisions. Data analysts should have analytical and reporting capabilities, be able to monitor quality and performance within an organisation, and offer solutions for improvement.

Some key functions of a data analyst include: collecting high-quality data, conducting statistical analysis on data, interpreting the results of these analyses, collating the results, creating reports based on the results, and finally presenting insights to relevant stakeholders.

Jane is a data analyst that has recently been hired by a large apparel company. Until now, the company has had little experience in data analytics, and Jane was hired to fill this gap. Jane’s initial steps are to establish an understanding of what business decisions the company’s trying to answer and what problems they are trying to solve.

After meeting with the company’s board of directors, she is told that the business is primarily interested in streamlining their supply chain and effectively scaling up clothing production. With this information, Jane moves on to identify the available data and data sources. This includes whether the data is numerical in nature, such as resource pricing and employee compensation, or whether it is non-numeric, such as demographics and education status.

She quickly realises that there’s no central database for locating the company’s data, but that each department collects and stores their own. Now that Jane has an understanding of how the company handles data, she defines robust data collection procedures that establish clear guidelines for how information from the company’s different branches are to be collected.

Jane is also working to establish a central database for all the company’s information. Once Jane has an understanding of the data pipeline and what types of data are available, she returns to the problem that the company is trying to solve. Based on her discussion with the company’s board and the data available to her, she chooses the appropriate types of statistical analysis she can perform on various datasets.

She then collates this data into digestible, informative pieces and presents her findings to the board, using data visualisation tools. Jane made sure to understand the types of data available to her and the sources that this data came from.

After performing the analysis, she created information reports and presented the results to the company board, who were then able to make data-driven decisions for the company’s future.

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