Case Study Description of Practical Regression: Causality and Instrumental Variables
This is the tenth 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 uses the theory of "supplier-induced demand" from health economics to illustrate key issues including reverse causality, the role of instrumental variables in establishing causality, and the characteristics of good instruments.
Swot Analysis of "Practical Regression: Causality and Instrumental Variables" written by David Dranove includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Causality Regression facing as an external strategic factors. Some of the topics covered in Practical Regression: Causality and Instrumental 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: Causality and Instrumental Variables casestudy better are - – there is backlash against globalization, cloud computing is disrupting traditional business models, technology disruption, increasing household debt because of falling income levels, digital marketing is dominated by two big players Facebook and Google, increasing energy prices, increasing transportation and logistics costs,
increasing government debt because of Covid-19 spendings, geopolitical disruptions, etc
Introduction to SWOT Analysis of Practical Regression: Causality and Instrumental Variables
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in Practical Regression: Causality and Instrumental Variables case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Causality Regression, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Causality Regression 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: Causality and Instrumental Variables can be done for the following purposes –
1. Strategic planning using facts provided in Practical Regression: Causality and Instrumental Variables case study
2. Improving business portfolio management of Causality Regression
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 Causality Regression
Strengths Practical Regression: Causality and Instrumental Variables | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Causality Regression in Practical Regression: Causality and Instrumental Variables Harvard Business Review case study are -
Ability to lead change in Finance & Accounting field
– Causality Regression 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 Causality Regression in – penetrating new markets, reaching out to new customers, and providing different value propositions to different customers in the international markets.
High brand equity
– Causality Regression has strong brand awareness and brand recognition among both - the exiting customers and potential new customers. Strong brand equity has enabled Causality Regression to keep acquiring new customers and building profitable relationship with both the new and loyal customers.
Operational resilience
– The operational resilience strategy in the Practical Regression: Causality and Instrumental 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.
Effective Research and Development (R&D)
– Causality Regression 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: Causality and Instrumental 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.
Organizational Resilience of Causality Regression
– The covid-19 pandemic has put organizational resilience at the centre of everthing that Causality Regression does. Organizational resilience comprises - Financial Resilience, Operational Resilience, Technological Resilience, Organizational Resilience, Business Model Resilience, and Reputation Resilience.
Sustainable margins compare to other players in Finance & Accounting industry
– Practical Regression: Causality and Instrumental Variables firm has clearly differentiated products in the market place. This has enabled Causality Regression to fetch slight price premium compare to the competitors in the Finance & Accounting industry. The sustainable margins have also helped Causality Regression to invest into research and development (R&D) and innovation.
Successful track record of launching new products
– Causality Regression has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Causality Regression 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.
Ability to recruit top talent
– Causality Regression is one of the leading recruiters in the industry. Managers in the Practical Regression: Causality and Instrumental 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.
Analytics focus
– Causality Regression 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.
Highly skilled collaborators
– Causality Regression has highly efficient outsourcing and offshoring strategy. It has resulted in greater operational flexibility and bringing down the costs in highly price sensitive segment. Secondly the value chain collaborators of the firm in Practical Regression: Causality and Instrumental Variables HBR case study have helped the firm to develop new products and bring them quickly to the marketplace.
Diverse revenue streams
– Causality Regression is present in almost all the verticals within the industry. This has provided firm in Practical Regression: Causality and Instrumental 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.
Digital Transformation in Finance & Accounting segment
- digital transformation varies from industry to industry. For Causality Regression digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Causality Regression 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.
Weaknesses Practical Regression: Causality and Instrumental Variables | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Practical Regression: Causality and Instrumental Variables are -
Slow to strategic competitive environment developments
– As Practical Regression: Causality and Instrumental Variables HBR case study mentions - Causality Regression takes time to assess the upcoming competitions. This has led to missing out on atleast 2-3 big opportunities in the industry in last five years.
No frontier risks strategy
– After analyzing the HBR case study Practical Regression: Causality and Instrumental 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.
Workers concerns about automation
– As automation is fast increasing in the segment, Causality Regression needs to come up with a strategy to reduce the workers concern regarding automation. Without a clear strategy, it could lead to disruption and uncertainty within the organization.
Increasing silos among functional specialists
– The organizational structure of Causality Regression is dominated by functional specialists. It is not different from other players in the Finance & Accounting segment. Causality Regression needs to de-silo the office environment to harness the true potential of its workforce. Secondly the de-silo will also help Causality Regression to focus more on services rather than just following the product oriented approach.
Interest costs
– Compare to the competition, Causality Regression 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.
Need for greater diversity
– Causality Regression 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.
High cash cycle compare to competitors
Causality Regression has a high cash cycle compare to other players in the industry. It needs to shorten the cash cycle by 12% to be more competitive in the marketplace, reduce inventory costs, and be more profitable.
Aligning sales with marketing
– It come across in the case study Practical Regression: Causality and Instrumental 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: Causality and Instrumental Variables can leverage the sales team experience to cultivate customer relationships as Causality Regression is planning to shift buying processes online.
Low market penetration in new markets
– Outside its home market of Causality Regression, firm in the HBR case study Practical Regression: Causality and Instrumental Variables needs to spend more promotional, marketing, and advertising efforts to penetrate international markets.
High operating costs
– Compare to the competitors, firm in the HBR case study Practical Regression: Causality and Instrumental Variables has high operating costs in the. This can be harder to sustain given the new emerging competition from nimble players who are using technology to attract Causality Regression 's lucrative customers.
Slow decision making process
– As mentioned earlier in the report, Causality Regression 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. Causality Regression 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.
Opportunities Practical Regression: Causality and Instrumental 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: Causality and Instrumental Variables are -
Leveraging digital technologies
– Causality Regression can leverage digital technologies such as artificial intelligence and machine learning to automate the production process, customer analytics to get better insights into consumer behavior, realtime digital dashboards to get better sales tracking, logistics and transportation, product tracking, etc.
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 Causality Regression in the consumer business. Now Causality Regression can target international markets with far fewer capital restrictions requirements than the existing system.
Finding new ways to collaborate
– Covid-19 has not only transformed business models of companies in Finance & Accounting industry, but it has also influenced the consumer preferences. Causality Regression can tie-up with other value chain partners to explore new opportunities regarding meeting customer demands and building a rewarding and engaging relationship.
Harnessing reconfiguration of the global supply chains
– As the trade war between US and China heats up in the coming years, Causality Regression 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: Causality and Instrumental 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.
Manufacturing automation
– Causality Regression 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.
Building a culture of innovation
– managers at Causality Regression 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.
Learning at scale
– Online learning technologies has now opened space for Causality Regression to conduct training and development for its employees across the world. This will result in not only reducing the cost of training but also help employees in different part of the world to integrate with the headquarter work culture, ethos, and standards.
Creating value in data economy
– The success of analytics program of Causality Regression has opened avenues for new revenue streams for the organization in the industry. This can help Causality Regression to build a more holistic ecosystem as suggested in the Practical Regression: Causality and Instrumental Variables case study. Causality Regression can build new products and services such as - data insight services, data privacy related products, data based consulting services, etc.
Reforming the budgeting process
- By establishing new metrics that will be used to evaluate both existing and potential projects Causality Regression can not only reduce the costs of the project but also help it in integrating the projects with other processes within the organization.
Using analytics as competitive advantage
– Causality Regression has spent a significant amount of money and effort to integrate analytics and machine learning into its operations in the sector. This continuous investment in analytics has enabled, as illustrated in the Harvard case study Practical Regression: Causality and Instrumental Variables - to build a competitive advantage using analytics. The analytics driven competitive advantage can help Causality Regression to build faster Go To Market strategies, better consumer insights, developing relevant product features, and building a highly efficient supply chain.
Better consumer reach
– The expansion of the 5G network will help Causality Regression to increase its market reach. Causality Regression 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.
Remote work and new talent hiring opportunities
– The widespread usage of remote working technologies during Covid-19 has opened opportunities for Causality Regression 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 Causality Regression to hire the very best people irrespective of their geographical location.
Lowering marketing communication costs
– 5G expansion will open new opportunities for Causality Regression in the field of marketing communication. It will bring down the cost of doing business, provide technology platform to build new products in the Finance & Accounting segment, and it will provide faster access to the consumers.
Threats Practical Regression: Causality and Instrumental 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: Causality and Instrumental Variables are -
New competition
– After the dotcom bust of 2001, financial crisis of 2008-09, the business formation in US economy had declined. But in 2020 alone, there are more than 1.5 million new business applications in United States. This can lead to greater competition for Causality Regression in the Finance & Accounting sector and impact the bottomline of the organization.
Shortening product life cycle
– it is one of the major threat that Causality Regression is facing in Finance & Accounting sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, etc.
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 Causality Regression business can come under increasing regulations regarding data privacy, data security, etc.
Consumer confidence and its impact on Causality Regression demand
– There is a high probability of declining consumer confidence, given – high inflammation rate, rise of gig economy, lower job stability, increasing cost of living, higher interest rates, and aging demography. All the factors contribute to people saving higher rate of their income, resulting in lower consumer demand in the industry and other sectors.
Technology acceleration in Forth Industrial Revolution
– Causality Regression has witnessed rapid integration of technology during Covid-19 in the Finance & Accounting industry. As one of the leading players in the industry, Causality Regression needs to keep up with the evolution of technology in the Finance & Accounting sector. According to Mckinsey study top managers believe that the adoption of technology in operations, communications is 20-25 times faster than what they planned in the beginning of 2019.
Stagnating economy with rate increase
– Causality Regression can face lack of demand in the market place because of Fed actions to reduce inflation. This can lead to sluggish growth in the economy, lower demands, lower investments, higher borrowing costs, and consolidation in the field.
Barriers of entry lowering
– As technology is more democratized, the barriers to entry in the industry are lowering. It can presents Causality Regression with greater competitive threats in the near to medium future. Secondly it will also put downward pressure on pricing throughout the sector.
High dependence on third party suppliers
– Causality Regression high dependence on third party suppliers can disrupt its processes and delivery mechanism. For example -the current troubles of car makers because of chip shortage is because the chip companies started producing chips for electronic companies rather than car manufacturers.
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 Causality Regression.
Learning curve for new practices
– As the technology based on artificial intelligence and machine learning platform is getting complex, as highlighted in case study Practical Regression: Causality and Instrumental Variables, Causality Regression may face longer learning curve for training and development of existing employees. This can open space for more nimble competitors in the field of Finance & Accounting .
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. Causality Regression needs to understand the core reasons impacting the Finance & Accounting industry. This will help it in building a better workplace.
Increasing wage structure of Causality Regression
– 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 Causality Regression.
Regulatory challenges
– Causality Regression 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.
Weighted SWOT Analysis of Practical Regression: Causality and Instrumental 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: Causality and Instrumental 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: Causality and Instrumental 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: Causality and Instrumental 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: Causality and Instrumental 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 Causality Regression needs to make to build a sustainable competitive advantage.
