Note on Logistic Regression - The Binomial Case SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
Organizational Development
Strategy / MBA Resources
Case Study SWOT Analysis Solution
Case Study Description of Note on Logistic Regression - The Binomial Case
This note discusses logistic regression using binomial data. Also discussed is an explanation of how to estimate the parameters from logistic regression using Microsoft Excel (without any add-ins). The note is a follow up to Note on Logistic Regression, product #910E05, which discusses the case with Bernoulli data.
Swot Analysis of "Note on Logistic Regression - The Binomial Case" written by Hendrik Odegaard, Andrew Brennan includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Logistic Regression facing as an external strategic factors. Some of the topics covered in Note on Logistic Regression - The Binomial Case case study are - Strategic Management Strategies, Operations management and Organizational Development.
Some of the macro environment factors that can be used to understand the Note on Logistic Regression - The Binomial Case casestudy better are - – competitive advantages are harder to sustain because of technology dispersion, increasing commodity prices, there is increasing trade war between United States & China, increasing household debt because of falling income levels, geopolitical disruptions, increasing energy prices, increasing government debt because of Covid-19 spendings,
digital marketing is dominated by two big players Facebook and Google, technology disruption, etc
Introduction to SWOT Analysis of Note on Logistic Regression - The Binomial Case
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in Note on Logistic Regression - The Binomial Case case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Logistic Regression, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Logistic 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 Note on Logistic Regression - The Binomial Case can be done for the following purposes –
1. Strategic planning using facts provided in Note on Logistic Regression - The Binomial Case case study
2. Improving business portfolio management of Logistic Regression
3. Assessing feasibility of the new initiative in Organizational Development field.
4. Making a Organizational Development topic specific business decision
5. Set goals for the organization
6. Organizational restructuring of Logistic Regression
Strengths Note on Logistic Regression - The Binomial Case | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Logistic Regression in Note on Logistic Regression - The Binomial Case Harvard Business Review case study are -
Strong track record of project management
– Logistic Regression is known for sticking to its project targets. This enables the firm to manage – time, project costs, and have sustainable margins on the projects.
Ability to recruit top talent
– Logistic Regression is one of the leading recruiters in the industry. Managers in the Note on Logistic Regression - The Binomial Case are in a position to attract the best talent available. The firm has a robust talent identification program that helps in identifying the brightest.
Sustainable margins compare to other players in Organizational Development industry
– Note on Logistic Regression - The Binomial Case firm has clearly differentiated products in the market place. This has enabled Logistic Regression to fetch slight price premium compare to the competitors in the Organizational Development industry. The sustainable margins have also helped Logistic Regression to invest into research and development (R&D) and innovation.
Ability to lead change in Organizational Development field
– Logistic 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 Logistic Regression in – penetrating new markets, reaching out to new customers, and providing different value propositions to different customers in the international markets.
Effective Research and Development (R&D)
– Logistic 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 Note on Logistic Regression - The Binomial Case - 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 Note on Logistic Regression - The Binomial Case 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 Logistic Regression in the segment is based on four key concepts – personalization, simplification of complex needs, prompt response, and continuous engagement.
Cross disciplinary teams
– Horizontal connected teams at the Logistic Regression 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.
Highly skilled collaborators
– Logistic 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 Note on Logistic Regression - The Binomial Case HBR case study have helped the firm to develop new products and bring them quickly to the marketplace.
High brand equity
– Logistic Regression has strong brand awareness and brand recognition among both - the exiting customers and potential new customers. Strong brand equity has enabled Logistic Regression to keep acquiring new customers and building profitable relationship with both the new and loyal customers.
Diverse revenue streams
– Logistic Regression is present in almost all the verticals within the industry. This has provided firm in Note on Logistic Regression - The Binomial Case 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.
Successful track record of launching new products
– Logistic Regression has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Logistic 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.
Weaknesses Note on Logistic Regression - The Binomial Case | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Note on Logistic Regression - The Binomial Case are -
Lack of clear differentiation of Logistic Regression products
– To increase the profitability and margins on the products, Logistic Regression needs to provide more differentiated products than what it is currently offering in the marketplace.
High dependence on star products
– The top 2 products and services of the firm as mentioned in the Note on Logistic Regression - The Binomial Case 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 Logistic Regression has relatively successful track record of launching new products.
Skills based hiring
– The stress on hiring functional specialists at Logistic Regression has created an environment where the organization is dominated by functional specialists rather than management generalist. This has resulted into product oriented approach rather than marketing oriented approach or consumers oriented approach.
Slow to harness new channels of communication
– Even though competitors are using new communication channels such as Instagram, Tiktok, and Snap, Logistic Regression is slow explore the new channels of communication. These new channels of communication mentioned in marketing section of case study Note on Logistic Regression - The Binomial Case can help to provide better information regarding products and services. It can also build an online community to further reach out to potential customers.
Interest costs
– Compare to the competition, Logistic 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.
Slow to strategic competitive environment developments
– As Note on Logistic Regression - The Binomial Case HBR case study mentions - Logistic 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.
Products dominated business model
– Even though Logistic Regression 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 - Note on Logistic Regression - The Binomial Case should strive to include more intangible value offerings along with its core products and services.
Need for greater diversity
– Logistic 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.
Employees’ incomplete understanding of strategy
– From the instances in the HBR case study Note on Logistic Regression - The Binomial Case, it seems that the employees of Logistic Regression 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.
Capital Spending Reduction
– Even during the low interest decade, Logistic Regression 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.
High bargaining power of channel partners
– Because of the regulatory requirements, Hendrik Odegaard, Andrew Brennan suggests that, Logistic Regression 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.
Opportunities Note on Logistic Regression - The Binomial Case | 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 Note on Logistic Regression - The Binomial Case are -
Reforming the budgeting process
- By establishing new metrics that will be used to evaluate both existing and potential projects Logistic Regression can not only reduce the costs of the project but also help it in integrating the projects with other processes within the organization.
Creating value in data economy
– The success of analytics program of Logistic Regression has opened avenues for new revenue streams for the organization in the industry. This can help Logistic Regression to build a more holistic ecosystem as suggested in the Note on Logistic Regression - The Binomial Case case study. Logistic Regression can build new products and services such as - data insight services, data privacy related products, data based consulting services, etc.
Buying journey improvements
– Logistic Regression can improve the customer journey of consumers in the industry by using analytics and artificial intelligence. Note on Logistic Regression - The Binomial Case 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.
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 Logistic Regression 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.
Lowering marketing communication costs
– 5G expansion will open new opportunities for Logistic 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 Organizational Development segment, and it will provide faster access to the consumers.
Learning at scale
– Online learning technologies has now opened space for Logistic 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.
Changes in consumer behavior post Covid-19
– Consumer behavior has changed in the Organizational Development industry because of Covid-19 restrictions. Some of this behavior will stay once things get back to normal. Logistic Regression 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. Logistic Regression 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.
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 Logistic Regression in the consumer business. Now Logistic Regression can target international markets with far fewer capital restrictions requirements than the existing system.
Leveraging digital technologies
– Logistic 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.
Harnessing reconfiguration of the global supply chains
– As the trade war between US and China heats up in the coming years, Logistic 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, Note on Logistic Regression - The Binomial Case, to buy more products closer to the markets, and it can leverage its size and influence to get better deal from the local markets.
Increase in government spending
– As the United States and other governments are increasing social spending and infrastructure spending to build economies post Covid-19, Logistic Regression can use these opportunities to build new business models that can help the communities that Logistic Regression operates in. Secondly it can use opportunities from government spending in Organizational Development sector.
Remote work and new talent hiring opportunities
– The widespread usage of remote working technologies during Covid-19 has opened opportunities for Logistic 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 Logistic Regression 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, Logistic Regression 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.
Threats Note on Logistic Regression - The Binomial Case External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats mentioned in the HBR case study Note on Logistic Regression - The Binomial Case are -
Stagnating economy with rate increase
– Logistic 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.
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 Logistic Regression.
Trade war between China and United States
– The trade war between two of the biggest economies can hugely impact the opportunities for Logistic Regression in the Organizational Development industry. The Organizational Development 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.
Shortening product life cycle
– it is one of the major threat that Logistic Regression is facing in Organizational Development sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, etc.
Increasing international competition and downward pressure on margins
– Apart from technology driven competitive advantage dilution, Logistic Regression 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 Note on Logistic Regression - The Binomial Case .
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 Logistic Regression in the Organizational Development sector and impact the bottomline of the organization.
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 Logistic Regression business can come under increasing regulations regarding data privacy, data security, etc.
Regulatory challenges
– Logistic 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 Organizational Development industry regulations.
Learning curve for new practices
– As the technology based on artificial intelligence and machine learning platform is getting complex, as highlighted in case study Note on Logistic Regression - The Binomial Case, Logistic 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 Organizational Development .
Technology acceleration in Forth Industrial Revolution
– Logistic Regression has witnessed rapid integration of technology during Covid-19 in the Organizational Development industry. As one of the leading players in the industry, Logistic Regression needs to keep up with the evolution of technology in the Organizational Development 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.
Consumer confidence and its impact on Logistic 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.
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.
Weighted SWOT Analysis of Note on Logistic Regression - The Binomial Case 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 Note on Logistic Regression - The Binomial Case 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 Note on Logistic Regression - The Binomial Case 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 Note on Logistic Regression - The Binomial Case 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 Note on Logistic Regression - The Binomial Case 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 Logistic Regression needs to make to build a sustainable competitive advantage.
