Case Study Description of Multiple Regression and Marketing-Mix Models
This technical note provides a basic introduction to multiple linear regression. The concept of regression using a single independent variable is first introduced and then some of the practical challenges associated with it--including multiple independent variables in a regression--are discussed. Particular attention is paid to bias in the regression coefficients in the presence of omitted variables. The concept of the economic significance of a model is introduced and is contrasted with statistical significance. At Darden, it is used in a course elective titled "Big Data in Marketing."
Swot Analysis of "Multiple Regression and Marketing-Mix Models" written by Rajkumar Venkatesan, Shea Gibbs includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Regression Significance facing as an external strategic factors. Some of the topics covered in Multiple Regression and Marketing-Mix Models case study are - Strategic Management Strategies, Marketing and Sales & Marketing.
Some of the macro environment factors that can be used to understand the Multiple Regression and Marketing-Mix Models casestudy better are - – banking and financial system is disrupted by Bitcoin and other crypto currencies, talent flight as more people leaving formal jobs, there is increasing trade war between United States & China, central banks are concerned over increasing inflation, geopolitical disruptions, increasing energy prices, wage bills are increasing,
increasing transportation and logistics costs, digital marketing is dominated by two big players Facebook and Google, etc
Introduction to SWOT Analysis of Multiple Regression and Marketing-Mix Models
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in Multiple Regression and Marketing-Mix Models case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Regression Significance, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Regression Significance 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 Multiple Regression and Marketing-Mix Models can be done for the following purposes –
1. Strategic planning using facts provided in Multiple Regression and Marketing-Mix Models case study
2. Improving business portfolio management of Regression Significance
3. Assessing feasibility of the new initiative in Sales & Marketing field.
4. Making a Sales & Marketing topic specific business decision
5. Set goals for the organization
6. Organizational restructuring of Regression Significance
Strengths Multiple Regression and Marketing-Mix Models | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Regression Significance in Multiple Regression and Marketing-Mix Models Harvard Business Review case study are -
Learning organization
- Regression Significance 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 Regression Significance is open place that encourages instructiveness, ideation, open minded discussions, and creativity. Employees and leaders in Multiple Regression and Marketing-Mix Models Harvard Business Review case study emphasize – knowledge, initiative, and innovation.
Superior customer experience
– The customer experience strategy of Regression Significance in the segment is based on four key concepts – personalization, simplification of complex needs, prompt response, and continuous engagement.
Organizational Resilience of Regression Significance
– The covid-19 pandemic has put organizational resilience at the centre of everthing that Regression Significance does. Organizational resilience comprises - Financial Resilience, Operational Resilience, Technological Resilience, Organizational Resilience, Business Model Resilience, and Reputation Resilience.
Low bargaining power of suppliers
– Suppliers of Regression Significance in the sector have low bargaining power. Multiple Regression and Marketing-Mix Models has further diversified its suppliers portfolio by building a robust supply chain across various countries. This helps Regression Significance to manage not only supply disruptions but also source products at highly competitive prices.
Analytics focus
– Regression Significance 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 Rajkumar Venkatesan, Shea Gibbs 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.
Digital Transformation in Sales & Marketing segment
- digital transformation varies from industry to industry. For Regression Significance digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Regression Significance 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 recruit top talent
– Regression Significance is one of the leading recruiters in the industry. Managers in the Multiple Regression and Marketing-Mix Models are in a position to attract the best talent available. The firm has a robust talent identification program that helps in identifying the brightest.
Diverse revenue streams
– Regression Significance is present in almost all the verticals within the industry. This has provided firm in Multiple Regression and Marketing-Mix Models 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.
Cross disciplinary teams
– Horizontal connected teams at the Regression Significance 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.
Ability to lead change in Sales & Marketing field
– Regression Significance 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 Significance in – penetrating new markets, reaching out to new customers, and providing different value propositions to different customers in the international markets.
Successful track record of launching new products
– Regression Significance has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Regression Significance 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.
High brand equity
– Regression Significance has strong brand awareness and brand recognition among both - the exiting customers and potential new customers. Strong brand equity has enabled Regression Significance to keep acquiring new customers and building profitable relationship with both the new and loyal customers.
Weaknesses Multiple Regression and Marketing-Mix Models | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Multiple Regression and Marketing-Mix Models are -
Slow to harness new channels of communication
– Even though competitors are using new communication channels such as Instagram, Tiktok, and Snap, Regression Significance is slow explore the new channels of communication. These new channels of communication mentioned in marketing section of case study Multiple Regression and Marketing-Mix Models can help to provide better information regarding products and services. It can also build an online community to further reach out to potential customers.
No frontier risks strategy
– After analyzing the HBR case study Multiple Regression and Marketing-Mix Models, it seems that company is thinking about the frontier risks that can impact Sales & Marketing 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.
High bargaining power of channel partners
– Because of the regulatory requirements, Rajkumar Venkatesan, Shea Gibbs suggests that, Regression Significance 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.
High dependence on star products
– The top 2 products and services of the firm as mentioned in the Multiple Regression and Marketing-Mix Models 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 Regression Significance has relatively successful track record of launching new products.
Skills based hiring
– The stress on hiring functional specialists at Regression Significance 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.
Aligning sales with marketing
– It come across in the case study Multiple Regression and Marketing-Mix Models 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 Multiple Regression and Marketing-Mix Models can leverage the sales team experience to cultivate customer relationships as Regression Significance is planning to shift buying processes online.
Interest costs
– Compare to the competition, Regression Significance 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.
High cash cycle compare to competitors
Regression Significance 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.
Ability to respond to the competition
– As the decision making is very deliberative, highlighted in the case study Multiple Regression and Marketing-Mix Models, in the dynamic environment Regression Significance has struggled to respond to the nimble upstart competition. Regression Significance has reasonably good record with similar level competitors but it has struggled with new entrants taking away niches of its business.
Employees’ incomplete understanding of strategy
– From the instances in the HBR case study Multiple Regression and Marketing-Mix Models, it seems that the employees of Regression Significance 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, Regression Significance 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.
Opportunities Multiple Regression and Marketing-Mix Models | 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 Multiple Regression and Marketing-Mix Models are -
Building a culture of innovation
– managers at Regression Significance 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 Sales & Marketing segment.
Harnessing reconfiguration of the global supply chains
– As the trade war between US and China heats up in the coming years, Regression Significance 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, Multiple Regression and Marketing-Mix Models, to buy more products closer to the markets, and it can leverage its size and influence to get better deal from the local markets.
Buying journey improvements
– Regression Significance can improve the customer journey of consumers in the industry by using analytics and artificial intelligence. Multiple Regression and Marketing-Mix Models 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.
Finding new ways to collaborate
– Covid-19 has not only transformed business models of companies in Sales & Marketing industry, but it has also influenced the consumer preferences. Regression Significance can tie-up with other value chain partners to explore new opportunities regarding meeting customer demands and building a rewarding and engaging relationship.
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 Significance can use these opportunities to build new business models that can help the communities that Regression Significance operates in. Secondly it can use opportunities from government spending in Sales & Marketing sector.
Reforming the budgeting process
- By establishing new metrics that will be used to evaluate both existing and potential projects Regression Significance 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 Regression Significance has opened avenues for new revenue streams for the organization in the industry. This can help Regression Significance to build a more holistic ecosystem as suggested in the Multiple Regression and Marketing-Mix Models case study. Regression Significance can build new products and services such as - data insight services, data privacy related products, data based consulting services, etc.
Loyalty marketing
– Regression Significance 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.
Using analytics as competitive advantage
– Regression Significance 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 Multiple Regression and Marketing-Mix Models - to build a competitive advantage using analytics. The analytics driven competitive advantage can help Regression Significance to build faster Go To Market strategies, better consumer insights, developing relevant product features, and building a highly efficient supply chain.
Leveraging digital technologies
– Regression Significance 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.
Manufacturing automation
– Regression Significance can use the latest technology developments to improve its manufacturing and designing process in Sales & Marketing 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.
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 Significance can explore opportunities that can attract volunteers and are consistent with its mission and vision.
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 Regression Significance 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.
Threats Multiple Regression and Marketing-Mix Models External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats mentioned in the HBR case study Multiple Regression and Marketing-Mix Models are -
Increasing wage structure of Regression Significance
– 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 Significance.
Technology acceleration in Forth Industrial Revolution
– Regression Significance has witnessed rapid integration of technology during Covid-19 in the Sales & Marketing industry. As one of the leading players in the industry, Regression Significance needs to keep up with the evolution of technology in the Sales & Marketing 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.
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.
Instability in the European markets
– European Union markets are facing three big challenges post Covid – expanded balance sheets, Brexit related business disruption, and aggressive Russia looking to distract the existing security mechanism. Regression Significance will face different problems in different parts of Europe. For example it will face inflationary pressures in UK, France, and Germany, balance sheet expansion and demand challenges in Southern European countries, and geopolitical instability in the Eastern Europe.
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 Significance with greater competitive threats in the near to medium future. Secondly it will also put downward pressure on pricing throughout the sector.
Stagnating economy with rate increase
– Regression Significance 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.
Trade war between China and United States
– The trade war between two of the biggest economies can hugely impact the opportunities for Regression Significance in the Sales & Marketing industry. The Sales & Marketing 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.
Increasing international competition and downward pressure on margins
– Apart from technology driven competitive advantage dilution, Regression Significance 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 Multiple Regression and Marketing-Mix Models .
Learning curve for new practices
– As the technology based on artificial intelligence and machine learning platform is getting complex, as highlighted in case study Multiple Regression and Marketing-Mix Models, Regression Significance may face longer learning curve for training and development of existing employees. This can open space for more nimble competitors in the field of Sales & Marketing .
High dependence on third party suppliers
– Regression Significance 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.
Shortening product life cycle
– it is one of the major threat that Regression Significance is facing in Sales & Marketing sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, etc.
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 Significance.
Weighted SWOT Analysis of Multiple Regression and Marketing-Mix Models 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 Multiple Regression and Marketing-Mix Models 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 Multiple Regression and Marketing-Mix Models 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 Multiple Regression and Marketing-Mix Models 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 Multiple Regression and Marketing-Mix Models 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 Significance needs to make to build a sustainable competitive advantage.