×




Causal Inference SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis

Case Study SWOT Analysis Solution

Case Study Description of Causal Inference


Discusses what causation is and what one can (and cannot) learn about causation from observational (nonexperimental) data.

Authors :: Arthur Schleifer Jr.

Topics :: Strategy & Execution

Tags :: Decision making, Financial analysis, SWOT Analysis, SWOT Matrix, TOWS, Weighted SWOT Analysis

Swot Analysis of "Causal Inference" written by Arthur Schleifer Jr. includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Causation Nonexperimental facing as an external strategic factors. Some of the topics covered in Causal Inference case study are - Strategic Management Strategies, Decision making, Financial analysis and Strategy & Execution.


Some of the macro environment factors that can be used to understand the Causal Inference casestudy better are - – supply chains are disrupted by pandemic , increasing household debt because of falling income levels, there is backlash against globalization, talent flight as more people leaving formal jobs, increasing energy prices, customer relationship management is fast transforming because of increasing concerns over data privacy, increasing commodity prices, there is increasing trade war between United States & China, technology disruption, etc



12 Hrs

$59.99
per Page
  • 100% Plagiarism Free
  • On Time Delivery | 27x7
  • PayPal Secure
  • 300 Words / Page
  • Buy Now

24 Hrs

$49.99
per Page
  • 100% Plagiarism Free
  • On Time Delivery | 27x7
  • PayPal Secure
  • 300 Words / Page
  • Buy Now

48 Hrs

$39.99
per Page
  • 100% Plagiarism Free
  • On Time Delivery | 27x7
  • PayPal Secure
  • 300 Words / Page
  • Buy Now







Introduction to SWOT Analysis of Causal Inference


SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in Causal Inference case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Causation Nonexperimental, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Causation Nonexperimental 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 Causal Inference can be done for the following purposes –
1. Strategic planning using facts provided in Causal Inference case study
2. Improving business portfolio management of Causation Nonexperimental
3. Assessing feasibility of the new initiative in Strategy & Execution field.
4. Making a Strategy & Execution topic specific business decision
5. Set goals for the organization
6. Organizational restructuring of Causation Nonexperimental




Strengths Causal Inference | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis

The strengths of Causation Nonexperimental in Causal Inference Harvard Business Review case study are -

Highly skilled collaborators

– Causation Nonexperimental 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 Causal Inference HBR case study have helped the firm to develop new products and bring them quickly to the marketplace.

Learning organization

- Causation Nonexperimental is a learning organization. It has inculcated three key characters of learning organization in its processes and operations – exploration, creativity, and expansiveness. The work place at Causation Nonexperimental is open place that encourages instructiveness, ideation, open minded discussions, and creativity. Employees and leaders in Causal Inference Harvard Business Review case study emphasize – knowledge, initiative, and innovation.

Cross disciplinary teams

– Horizontal connected teams at the Causation Nonexperimental are driving operational speed, building greater agility, and keeping the organization nimble to compete with new competitors. It helps are organization to ideate new ideas, and execute them swiftly in the marketplace.

High switching costs

– The high switching costs that Causation Nonexperimental has built up over years in its products and services combo offer has resulted in high retention of customers, lower marketing costs, and greater ability of the firm to focus on its customers.

Ability to lead change in Strategy & Execution field

– Causation Nonexperimental 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 Causation Nonexperimental in – penetrating new markets, reaching out to new customers, and providing different value propositions to different customers in the international markets.

Diverse revenue streams

– Causation Nonexperimental is present in almost all the verticals within the industry. This has provided firm in Causal Inference 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.

Ability to recruit top talent

– Causation Nonexperimental is one of the leading recruiters in the industry. Managers in the Causal Inference are in a position to attract the best talent available. The firm has a robust talent identification program that helps in identifying the brightest.

Operational resilience

– The operational resilience strategy in the Causal Inference 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.

Superior customer experience

– The customer experience strategy of Causation Nonexperimental in the segment is based on four key concepts – personalization, simplification of complex needs, prompt response, and continuous engagement.

Strong track record of project management

– Causation Nonexperimental is known for sticking to its project targets. This enables the firm to manage – time, project costs, and have sustainable margins on the projects.

Innovation driven organization

– Causation Nonexperimental is one of the most innovative firm in sector. Manager in Causal Inference Harvard Business Review case study can use Clayton Christensen Disruptive Innovation strategies to further increase the scale of innovtions in the organization.

Digital Transformation in Strategy & Execution segment

- digital transformation varies from industry to industry. For Causation Nonexperimental digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Causation Nonexperimental 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 Causal Inference | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis

The weaknesses of Causal Inference are -

Low market penetration in new markets

– Outside its home market of Causation Nonexperimental, firm in the HBR case study Causal Inference needs to spend more promotional, marketing, and advertising efforts to penetrate international markets.

High dependence on star products

– The top 2 products and services of the firm as mentioned in the Causal Inference HBR case study still accounts for major business revenue. This dependence on star products in has resulted into insufficient focus on developing new products, even though Causation Nonexperimental has relatively successful track record of launching new products.

Aligning sales with marketing

– It come across in the case study Causal Inference 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 Causal Inference can leverage the sales team experience to cultivate customer relationships as Causation Nonexperimental is planning to shift buying processes online.

Interest costs

– Compare to the competition, Causation Nonexperimental 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.

Employees’ incomplete understanding of strategy

– From the instances in the HBR case study Causal Inference, it seems that the employees of Causation Nonexperimental don’t have comprehensive understanding of the firm’s strategy. This is reflected in number of promotional campaigns over the last few years that had mixed messaging and competing priorities. Some of the strategic activities and services promoted in the promotional campaigns were not consistent with the organization’s strategy.

Products dominated business model

– Even though Causation Nonexperimental 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 - Causal Inference should strive to include more intangible value offerings along with its core products and services.

Ability to respond to the competition

– As the decision making is very deliberative, highlighted in the case study Causal Inference, in the dynamic environment Causation Nonexperimental has struggled to respond to the nimble upstart competition. Causation Nonexperimental has reasonably good record with similar level competitors but it has struggled with new entrants taking away niches of its business.

Lack of clear differentiation of Causation Nonexperimental products

– To increase the profitability and margins on the products, Causation Nonexperimental needs to provide more differentiated products than what it is currently offering in the marketplace.

High cash cycle compare to competitors

Causation Nonexperimental 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.

Increasing silos among functional specialists

– The organizational structure of Causation Nonexperimental is dominated by functional specialists. It is not different from other players in the Strategy & Execution segment. Causation Nonexperimental needs to de-silo the office environment to harness the true potential of its workforce. Secondly the de-silo will also help Causation Nonexperimental to focus more on services rather than just following the product oriented approach.

High operating costs

– Compare to the competitors, firm in the HBR case study Causal Inference 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 Causation Nonexperimental 's lucrative customers.




Opportunities Causal Inference | 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 Causal Inference are -

Loyalty marketing

– Causation Nonexperimental 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.

Remote work and new talent hiring opportunities

– The widespread usage of remote working technologies during Covid-19 has opened opportunities for Causation Nonexperimental 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 Causation Nonexperimental to hire the very best people irrespective of their geographical location.

Low interest rates

– Even though inflation is raising its head in most developed economies, Causation Nonexperimental can still utilize the low interest rates to borrow money for capital investment. Secondly it can also use the increase of government spending in infrastructure projects to get new business.

Developing new processes and practices

– Causation Nonexperimental can develop new processes and procedures in Strategy & Execution 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.

Building a culture of innovation

– managers at Causation Nonexperimental 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 Strategy & Execution segment.

Manufacturing automation

– Causation Nonexperimental can use the latest technology developments to improve its manufacturing and designing process in Strategy & Execution 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.

Finding new ways to collaborate

– Covid-19 has not only transformed business models of companies in Strategy & Execution industry, but it has also influenced the consumer preferences. Causation Nonexperimental can tie-up with other value chain partners to explore new opportunities regarding meeting customer demands and building a rewarding and engaging relationship.

Reconfiguring business model

– The expansion of digital payment system, the bringing down of international transactions costs using Bitcoin and other blockchain based currencies, etc can help Causation Nonexperimental to reconfigure its entire business model. For example it can used blockchain based technologies to reduce piracy of its products in the big markets such as China. Secondly it can use the popularity of e-commerce in various developing markets to build a Direct to Customer business model rather than the current Channel Heavy distribution network.

Learning at scale

– Online learning technologies has now opened space for Causation Nonexperimental 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.

Changes in consumer behavior post Covid-19

– Consumer behavior has changed in the Strategy & Execution industry because of Covid-19 restrictions. Some of this behavior will stay once things get back to normal. Causation Nonexperimental can take advantage of these changes in consumer behavior to build a far more efficient business model. For example consumer regular ordering of products can reduce both last mile delivery costs and market penetration costs. Causation Nonexperimental can further use this consumer data to build better customer loyalty, provide better products and service collection, and improve the value proposition in inflationary times.

Redefining models of collaboration and team work

– As explained in the weaknesses section, Causation Nonexperimental is facing challenges because of the dominance of functional experts in the organization. Causal Inference 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.

Creating value in data economy

– The success of analytics program of Causation Nonexperimental has opened avenues for new revenue streams for the organization in the industry. This can help Causation Nonexperimental to build a more holistic ecosystem as suggested in the Causal Inference case study. Causation Nonexperimental can build new products and services such as - data insight services, data privacy related products, data based consulting services, etc.

Better consumer reach

– The expansion of the 5G network will help Causation Nonexperimental to increase its market reach. Causation Nonexperimental 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.




Threats Causal Inference External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis


The threats mentioned in the HBR case study Causal Inference are -

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 Causation Nonexperimental business can come under increasing regulations regarding data privacy, data security, etc.

High dependence on third party suppliers

– Causation Nonexperimental 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.

Learning curve for new practices

– As the technology based on artificial intelligence and machine learning platform is getting complex, as highlighted in case study Causal Inference, Causation Nonexperimental may face longer learning curve for training and development of existing employees. This can open space for more nimble competitors in the field of Strategy & Execution .

Shortening product life cycle

– it is one of the major threat that Causation Nonexperimental is facing in Strategy & Execution sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, etc.

Stagnating economy with rate increase

– Causation Nonexperimental 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.

Regulatory challenges

– Causation Nonexperimental 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 Strategy & Execution industry regulations.

Increasing wage structure of Causation Nonexperimental

– 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 Causation Nonexperimental.

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.

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.

Easy access to finance

– Easy access to finance in Strategy & Execution field will also reduce the barriers to entry in the industry, thus putting downward pressure on the prices because of increasing competition. Causation Nonexperimental 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, Causation Nonexperimental 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 Causal Inference .

Trade war between China and United States

– The trade war between two of the biggest economies can hugely impact the opportunities for Causation Nonexperimental in the Strategy & Execution industry. The Strategy & Execution 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.

Environmental challenges

– Causation Nonexperimental 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. Causation Nonexperimental can take advantage of this fund but it will also bring new competitors in the Strategy & Execution industry.




Weighted SWOT Analysis of Causal Inference 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 Causal Inference 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 Causal Inference 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 Causal Inference 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 Causal Inference 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 Causation Nonexperimental needs to make to build a sustainable competitive advantage.



--- ---

Jim Sharpe: Extrusion Technology, Inc. (C) SWOT Analysis / TOWS Matrix

H. Kent Bowen, Barbara Feinberg , Innovation & Entrepreneurship


Kevin Bertolini: Stop-Loss Strategy SWOT Analysis / TOWS Matrix

Hubert Pun, Alex Zhang , Leadership & Managing People


Investment Banking at Thomas Weisel Partners SWOT Analysis / TOWS Matrix

Malcolm P. Baker, Lauren Barley , Finance & Accounting


Sorrell Ridge: Slotting Allowances SWOT Analysis / TOWS Matrix

John A. Quelch, Aimee L. Stern , Sales & Marketing


The Judgment of Princeton SWOT Analysis / TOWS Matrix

Phillip E. Pfeifer , Leadership & Managing People


Discovery Limited SWOT Analysis / TOWS Matrix

Michael E. Porter, Mark R. Kramer, Aldo Sesia , Strategy & Execution


Rob Parson at Morgan Stanley (C) SWOT Analysis / TOWS Matrix

M. Diane Burton , Organizational Development


Organic Growth at Sonnentor SWOT Analysis / TOWS Matrix

Dietmar Sternad , Strategy & Execution


Intel Asia-Pacific: The Catch & Win Campaign SWOT Analysis / TOWS Matrix

Peter C. Bell, John Lyons, Peter Dingle, Ash Supersad , Leadership & Managing People