Case Study Description of Practical Regression: Discrete Dependent Variables
This is the ninth in a series of lecture notes which, if tied together into a textbook, might be entitled "Practical Regression." The purpose of the notes is to supplement the theoretical content of most statistics texts with practical advice based on nearly three decades of experience of the author, combined with over one hundred years of experience of colleagues who have offered guidance. As the title "Practical Regression" suggests, these notes are a guide to performing regression in practice. This note returns to the topic of endogeneity, explaining how a predictor variable can be endogenous (and therefore its coefficient can be biased) if causality is in doubt. Through an extended example of the learning curve in medicine, the note introduces the concept of instrumental variables (IV), provides an intuitive explanation for why instruments solve the causality problem, and explains how to estimate IV and two-stage least squares regressions. The note describes statistical tests for the validity of instruments.
Swot Analysis of "Practical Regression: Discrete Dependent Variables" written by David Dranove includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Regression Practical facing as an external strategic factors. Some of the topics covered in Practical Regression: Discrete Dependent Variables case study are - Strategic Management Strategies, Financial management, Market research and Finance & Accounting.
Some of the macro environment factors that can be used to understand the Practical Regression: Discrete Dependent Variables casestudy better are - – banking and financial system is disrupted by Bitcoin and other crypto currencies, increasing transportation and logistics costs, digital marketing is dominated by two big players Facebook and Google, increasing commodity prices, there is increasing trade war between United States & China, competitive advantages are harder to sustain because of technology dispersion, challanges to central banks by blockchain based private currencies,
wage bills are increasing, cloud computing is disrupting traditional business models, etc
Introduction to SWOT Analysis of Practical Regression: Discrete Dependent Variables
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in Practical Regression: Discrete Dependent Variables case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Regression Practical, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Regression Practical operates in.
According to Harvard Business Review, 75% of the managers use SWOT analysis for various purposes such as – evaluating current scenario, strategic planning, new venture feasibility, personal growth goals, new market entry, Go To market strategies, portfolio management and strategic trade-off assessment, organizational restructuring, etc.
SWOT Objectives / Importance of SWOT Analysis and SWOT Matrix
SWOT analysis of Practical Regression: Discrete Dependent Variables can be done for the following purposes –
1. Strategic planning using facts provided in Practical Regression: Discrete Dependent Variables case study
2. Improving business portfolio management of Regression Practical
3. Assessing feasibility of the new initiative in Finance & Accounting field.
4. Making a Finance & Accounting topic specific business decision
5. Set goals for the organization
6. Organizational restructuring of Regression Practical
Strengths Practical Regression: Discrete Dependent Variables | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Regression Practical in Practical Regression: Discrete Dependent Variables Harvard Business Review case study are -
High brand equity
– Regression Practical has strong brand awareness and brand recognition among both - the exiting customers and potential new customers. Strong brand equity has enabled Regression Practical to keep acquiring new customers and building profitable relationship with both the new and loyal customers.
Ability to recruit top talent
– Regression Practical is one of the leading recruiters in the industry. Managers in the Practical Regression: Discrete Dependent Variables are in a position to attract the best talent available. The firm has a robust talent identification program that helps in identifying the brightest.
Effective Research and Development (R&D)
– Regression Practical has innovation driven culture where significant part of the revenues are spent on the research and development activities. This has resulted in, as mentioned in case study Practical Regression: Discrete Dependent Variables - staying ahead in the industry in terms of – new product launches, superior customer experience, highly competitive pricing strategies, and great returns to the shareholders.
Operational resilience
– The operational resilience strategy in the Practical Regression: Discrete Dependent Variables Harvard Business Review case study comprises – understanding the underlying the factors in the industry, building diversified operations across different geographies so that disruption in one part of the world doesn’t impact the overall performance of the firm, and integrating the various business operations and processes through its digital transformation drive.
Strong track record of project management
– Regression Practical is known for sticking to its project targets. This enables the firm to manage – time, project costs, and have sustainable margins on the projects.
Analytics focus
– Regression Practical is putting a lot of focus on utilizing the power of analytics in business decision making. This has put it among the leading players in the industry. The technology infrastructure suggested by David Dranove can also help it to harness the power of analytics for – marketing optimization, demand forecasting, customer relationship management, inventory management, information sharing across the value chain etc.
Successful track record of launching new products
– Regression Practical has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Regression Practical has effective processes in place that helps in exploring new product needs, doing quick pilot testing, and then launching the products quickly using its extensive distribution network.
Diverse revenue streams
– Regression Practical is present in almost all the verticals within the industry. This has provided firm in Practical Regression: Discrete Dependent Variables case study a diverse revenue stream that has helped it to survive disruptions such as global pandemic in Covid-19, financial disruption of 2008, and supply chain disruption of 2021.
Superior customer experience
– The customer experience strategy of Regression Practical in the segment is based on four key concepts – personalization, simplification of complex needs, prompt response, and continuous engagement.
Organizational Resilience of Regression Practical
– The covid-19 pandemic has put organizational resilience at the centre of everthing that Regression Practical does. Organizational resilience comprises - Financial Resilience, Operational Resilience, Technological Resilience, Organizational Resilience, Business Model Resilience, and Reputation Resilience.
Digital Transformation in Finance & Accounting segment
- digital transformation varies from industry to industry. For Regression Practical digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Regression Practical has successfully integrated the four key components of digital transformation – digital integration in processes, digital integration in marketing and customer relationship management, digital integration into the value chain, and using technology to explore new products and market opportunities.
Ability to lead change in Finance & Accounting field
– Regression Practical is one of the leading players in its industry. Over the years it has not only transformed the business landscape in its segment but also across the whole industry. The ability to lead change has enabled Regression Practical in – penetrating new markets, reaching out to new customers, and providing different value propositions to different customers in the international markets.
Weaknesses Practical Regression: Discrete Dependent Variables | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Practical Regression: Discrete Dependent Variables are -
Lack of clear differentiation of Regression Practical products
– To increase the profitability and margins on the products, Regression Practical needs to provide more differentiated products than what it is currently offering in the marketplace.
High dependence on existing supply chain
– The disruption in the global supply chains because of the Covid-19 pandemic and blockage of the Suez Canal illustrated the fragile nature of Regression Practical supply chain. Even after few cautionary changes mentioned in the HBR case study - Practical Regression: Discrete Dependent Variables, it is still heavily dependent upon the existing supply chain. The existing supply chain though brings in cost efficiencies but it has left Regression Practical vulnerable to further global disruptions in South East Asia.
High bargaining power of channel partners
– Because of the regulatory requirements, David Dranove suggests that, Regression Practical is facing high bargaining power of the channel partners. So far it has not able to streamline the operations to reduce the bargaining power of the value chain partners in the industry.
No frontier risks strategy
– After analyzing the HBR case study Practical Regression: Discrete Dependent Variables, it seems that company is thinking about the frontier risks that can impact Finance & Accounting strategy. But it has very little resources allocation to manage the risks emerging from events such as natural disasters, climate change, melting of permafrost, tacking the rise of artificial intelligence, opportunities and threats emerging from commercialization of space etc.
Need for greater diversity
– Regression Practical has taken concrete steps on diversity, equity, and inclusion. But the efforts so far has resulted in limited success. It needs to expand the recruitment and selection process to hire more people from the minorities and underprivileged background.
Capital Spending Reduction
– Even during the low interest decade, Regression Practical has not been able to do capital spending to the tune of the competition. This has resulted into fewer innovations and company facing stiff competition from both existing competitors and new entrants who are disrupting the industry using digital technology.
Slow decision making process
– As mentioned earlier in the report, Regression Practical has a very deliberative decision making approach. This approach has resulted in prudent decisions, but it has also resulted in missing opportunities in the industry over the last five years. Regression Practical even though has strong showing on digital transformation primary two stages, it has struggled to capitalize the power of digital transformation in marketing efforts and new venture efforts.
Aligning sales with marketing
– It come across in the case study Practical Regression: Discrete Dependent Variables that the firm needs to have more collaboration between its sales team and marketing team. Sales professionals in the industry have deep experience in developing customer relationships. Marketing department in the case Practical Regression: Discrete Dependent Variables can leverage the sales team experience to cultivate customer relationships as Regression Practical is planning to shift buying processes online.
Interest costs
– Compare to the competition, Regression Practical has borrowed money from the capital market at higher rates. It needs to restructure the interest payment and costs so that it can compete better and improve profitability.
Slow to harness new channels of communication
– Even though competitors are using new communication channels such as Instagram, Tiktok, and Snap, Regression Practical is slow explore the new channels of communication. These new channels of communication mentioned in marketing section of case study Practical Regression: Discrete Dependent Variables can help to provide better information regarding products and services. It can also build an online community to further reach out to potential customers.
Products dominated business model
– Even though Regression Practical has some of the most successful products in the industry, this business model has made each new product launch extremely critical for continuous financial growth of the organization. firm in the HBR case study - Practical Regression: Discrete Dependent Variables should strive to include more intangible value offerings along with its core products and services.
Opportunities Practical Regression: Discrete Dependent Variables | External Strategic Factors
What are Opportunities in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The opportunities highlighted in the Harvard Business Review case study Practical Regression: Discrete Dependent Variables are -
Reforming the budgeting process
- By establishing new metrics that will be used to evaluate both existing and potential projects Regression Practical can not only reduce the costs of the project but also help it in integrating the projects with other processes within the organization.
Identify volunteer opportunities
– Covid-19 has impacted working population in two ways – it has led to people soul searching about their professional choices, resulting in mass resignation. Secondly it has encouraged people to do things that they are passionate about. This has opened opportunities for businesses to build volunteer oriented socially driven projects. Regression Practical can explore opportunities that can attract volunteers and are consistent with its mission and vision.
Redefining models of collaboration and team work
– As explained in the weaknesses section, Regression Practical is facing challenges because of the dominance of functional experts in the organization. Practical Regression: Discrete Dependent Variables case study suggests that firm can utilize new technology to build more coordinated teams and streamline operations and communications using tools such as CAD, Zoom, etc.
Manufacturing automation
– Regression Practical can use the latest technology developments to improve its manufacturing and designing process in Finance & Accounting segment. It can use CAD and 3D printing to build a quick prototype and pilot testing products. It can leverage automation using machine learning and artificial intelligence to do faster production at lowers costs, and it can leverage the growth in satellite and tracking technologies to improve inventory management, transportation, and shipping.
Developing new processes and practices
– Regression Practical can develop new processes and procedures in Finance & Accounting industry using technology such as automation using artificial intelligence, real time transportation and products tracking, 3D modeling for concept development and new products pilot testing etc.
Remote work and new talent hiring opportunities
– The widespread usage of remote working technologies during Covid-19 has opened opportunities for Regression Practical to expand its talent hiring zone. According to McKinsey Global Institute, 20% of the high end workforce in fields such as finance, information technology, can continously work from remote local post Covid-19. This presents a really great opportunity for Regression Practical to hire the very best people irrespective of their geographical location.
Harnessing reconfiguration of the global supply chains
– As the trade war between US and China heats up in the coming years, Regression Practical can build a diversified supply chain model across various countries in - South East Asia, India, and other parts of the world. This reconfiguration of global supply chain can help, as suggested in case study, Practical Regression: Discrete Dependent Variables, to buy more products closer to the markets, and it can leverage its size and influence to get better deal from the local markets.
Building a culture of innovation
– managers at Regression Practical can make experimentation a productive activity and build a culture of innovation using approaches such as – mining transaction data, A/B testing of websites and selling platforms, engaging potential customers over various needs, and building on small ideas in the Finance & Accounting segment.
Increase in government spending
– As the United States and other governments are increasing social spending and infrastructure spending to build economies post Covid-19, Regression Practical can use these opportunities to build new business models that can help the communities that Regression Practical operates in. Secondly it can use opportunities from government spending in Finance & Accounting sector.
Better consumer reach
– The expansion of the 5G network will help Regression Practical to increase its market reach. Regression Practical will be able to reach out to new customers. Secondly 5G will also provide technology framework to build new tools and products that can help more immersive consumer experience and faster consumer journey.
Loyalty marketing
– Regression Practical has focused on building a highly responsive customer relationship management platform. This platform is built on in-house data and driven by analytics and artificial intelligence. The customer analytics can help the organization to fine tune its loyalty marketing efforts, increase the wallet share of the organization, reduce wastage on mainstream advertising spending, build better pricing strategies using personalization, etc.
Buying journey improvements
– Regression Practical can improve the customer journey of consumers in the industry by using analytics and artificial intelligence. Practical Regression: Discrete Dependent Variables suggest that firm can provide automated chats to help consumers solve their own problems, provide online suggestions to get maximum out of the products and services, and help consumers to build a community where they can interact with each other to develop new features and uses.
Use of Bitcoin and other crypto currencies for transactions
– The popularity of Bitcoin and other crypto currencies as asset class and medium of transaction has opened new opportunities for Regression Practical in the consumer business. Now Regression Practical can target international markets with far fewer capital restrictions requirements than the existing system.
Threats Practical Regression: Discrete Dependent Variables External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats mentioned in the HBR case study Practical Regression: Discrete Dependent Variables are -
Capital market disruption
– During the Covid-19, Dow Jones has touched record high. The valuations of a number of companies are way beyond their existing business model potential. This can lead to capital market correction which can put a number of suppliers, collaborators, value chain partners in great financial difficulty. It will directly impact the business of Regression Practical.
Regulatory challenges
– Regression Practical needs to prepare for regulatory challenges as consumer protection groups and other pressure groups are vigorously advocating for more regulations on big business - to reduce inequality, to create a level playing field, to product data privacy and consumer privacy, to reduce the influence of big money on democratic institutions, etc. This can lead to significant changes in the Finance & Accounting industry regulations.
Trade war between China and United States
– The trade war between two of the biggest economies can hugely impact the opportunities for Regression Practical in the Finance & Accounting industry. The Finance & Accounting industry is already at various protected from local competition in China, with the rise of trade war the protection levels may go up. This presents a clear threat of current business model in Chinese market.
High level of anxiety and lack of motivation
– the Great Resignation in United States is the sign of broader dissatisfaction among the workforce in United States. Regression Practical needs to understand the core reasons impacting the Finance & Accounting industry. This will help it in building a better workplace.
Easy access to finance
– Easy access to finance in Finance & Accounting field will also reduce the barriers to entry in the industry, thus putting downward pressure on the prices because of increasing competition. Regression Practical can utilize it by borrowing at lower rates and invest it into research and development, capital expenditure to fortify its core competitive advantage.
Increasing international competition and downward pressure on margins
– Apart from technology driven competitive advantage dilution, Regression Practical can face downward pressure on margins from increasing competition from international players. The international players have stable revenue in their home market and can use those resources to penetrate prominent markets illustrated in HBR case study Practical Regression: Discrete Dependent Variables .
Environmental challenges
– Regression Practical needs to have a robust strategy against the disruptions arising from climate change and energy requirements. EU has identified it as key priority area and spending 30% of its 880 billion Euros European post Covid-19 recovery funds on green technology. Regression Practical can take advantage of this fund but it will also bring new competitors in the Finance & Accounting industry.
Backlash against dominant players
– US Congress and other legislative arms of the government are getting tough on big business especially technology companies. The digital arm of Regression Practical business can come under increasing regulations regarding data privacy, data security, etc.
Aging population
– As the populations of most advanced economies are aging, it will lead to high social security costs, higher savings among population, and lower demand for goods and services in the economy. The household savings in US, France, UK, Germany, and Japan are growing faster than predicted because of uncertainty caused by pandemic.
Barriers of entry lowering
– As technology is more democratized, the barriers to entry in the industry are lowering. It can presents Regression Practical with greater competitive threats in the near to medium future. Secondly it will also put downward pressure on pricing throughout the sector.
Increasing wage structure of Regression Practical
– Post Covid-19 there is a sharp increase in the wages especially in the jobs that require interaction with people. The increasing wages can put downward pressure on the margins of Regression Practical.
Shortening product life cycle
– it is one of the major threat that Regression Practical is facing in Finance & Accounting sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, etc.
Technology disruption because of hacks, piracy etc
– The colonial pipeline illustrated, how vulnerable modern organization are to international hackers, miscreants, and disruptors. The cyber security interruption, data leaks, etc can seriously jeopardize the future growth of the organization.
Weighted SWOT Analysis of Practical Regression: Discrete Dependent Variables Template, Example
Not all factors mentioned under the Strengths, Weakness, Opportunities, and Threats quadrants in the SWOT Analysis are equal. Managers in the HBR case study Practical Regression: Discrete Dependent Variables needs to zero down on the relative importance of each factor mentioned in the Strengths, Weakness, Opportunities, and Threats quadrants.
We can provide the relative importance to each factor by assigning relative weights. Weighted SWOT analysis process is a three stage process –
First stage for doing weighted SWOT analysis of the case study Practical Regression: Discrete Dependent Variables is to rank the strengths and weaknesses of the organization. This will help you to assess the most important strengths and weaknesses of the firm and which one of the strengths and weaknesses mentioned in the initial lists are marginal and can be left out.
Second stage for conducting weighted SWOT analysis of the Harvard case study Practical Regression: Discrete Dependent Variables is to give probabilities to the external strategic factors thus better understanding the opportunities and threats arising out of macro environment changes and developments.
Third stage of constructing weighted SWOT analysis of Practical Regression: Discrete Dependent Variables is to provide strategic recommendations includes – joining likelihood of external strategic factors such as opportunities and threats to the internal strategic factors – strengths and weaknesses. You should start with external factors as they will provide the direction of the overall industry. Secondly by joining probabilities with internal strategic factors can help the company not only strategic fit but also the most probably strategic trade-off that Regression Practical needs to make to build a sustainable competitive advantage.