The Power of Product Recommendation Networks SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
Leadership & Managing People
Strategy / MBA Resources
Case Study SWOT Analysis Solution
Case Study Description of The Power of Product Recommendation Networks
Much as relationships in social networks have been analyzed to understand and influence how ideas flow among people, researchers wondered whether it might be possible to use the structure of product recommendation networks online to understand or influence how demand flows among products. The short answer is yes, and the implications for marketers are important.
Authors :: Gal Oestreicher-Singer, Arun Sundararajan
Swot Analysis of "The Power of Product Recommendation Networks" written by Gal Oestreicher-Singer, Arun Sundararajan includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Networks Recommendation facing as an external strategic factors. Some of the topics covered in The Power of Product Recommendation Networks case study are - Strategic Management Strategies, and Leadership & Managing People.
Some of the macro environment factors that can be used to understand the The Power of Product Recommendation Networks casestudy better are - – challanges to central banks by blockchain based private currencies, technology disruption, wage bills are increasing, increasing transportation and logistics costs, central banks are concerned over increasing inflation, supply chains are disrupted by pandemic , there is increasing trade war between United States & China,
there is backlash against globalization, increasing household debt because of falling income levels, etc
Introduction to SWOT Analysis of The Power of Product Recommendation Networks
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in The Power of Product Recommendation Networks case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Networks Recommendation, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Networks Recommendation 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 The Power of Product Recommendation Networks can be done for the following purposes –
1. Strategic planning using facts provided in The Power of Product Recommendation Networks case study
2. Improving business portfolio management of Networks Recommendation
3. Assessing feasibility of the new initiative in Leadership & Managing People field.
4. Making a Leadership & Managing People topic specific business decision
5. Set goals for the organization
6. Organizational restructuring of Networks Recommendation
Strengths The Power of Product Recommendation Networks | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Networks Recommendation in The Power of Product Recommendation Networks Harvard Business Review case study are -
Ability to recruit top talent
– Networks Recommendation is one of the leading recruiters in the industry. Managers in the The Power of Product Recommendation Networks are in a position to attract the best talent available. The firm has a robust talent identification program that helps in identifying the brightest.
Cross disciplinary teams
– Horizontal connected teams at the Networks Recommendation 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 brand equity
– Networks Recommendation has strong brand awareness and brand recognition among both - the exiting customers and potential new customers. Strong brand equity has enabled Networks Recommendation to keep acquiring new customers and building profitable relationship with both the new and loyal customers.
Superior customer experience
– The customer experience strategy of Networks Recommendation in the segment is based on four key concepts – personalization, simplification of complex needs, prompt response, and continuous engagement.
Analytics focus
– Networks Recommendation 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 Gal Oestreicher-Singer, Arun Sundararajan 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.
Innovation driven organization
– Networks Recommendation is one of the most innovative firm in sector. Manager in The Power of Product Recommendation Networks Harvard Business Review case study can use Clayton Christensen Disruptive Innovation strategies to further increase the scale of innovtions in the organization.
Training and development
– Networks Recommendation has one of the best training and development program in the industry. The effectiveness of the training programs can be measured in The Power of Product Recommendation Networks Harvard Business Review case study by analyzing – employees retention, in-house promotion, loyalty, new venture initiation, lack of conflict, and high level of both employees and customer engagement.
Learning organization
- Networks Recommendation 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 Networks Recommendation is open place that encourages instructiveness, ideation, open minded discussions, and creativity. Employees and leaders in The Power of Product Recommendation Networks Harvard Business Review case study emphasize – knowledge, initiative, and innovation.
Digital Transformation in Leadership & Managing People segment
- digital transformation varies from industry to industry. For Networks Recommendation digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Networks Recommendation 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.
Operational resilience
– The operational resilience strategy in the The Power of Product Recommendation Networks 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.
High switching costs
– The high switching costs that Networks Recommendation 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.
Highly skilled collaborators
– Networks Recommendation 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 The Power of Product Recommendation Networks HBR case study have helped the firm to develop new products and bring them quickly to the marketplace.
Weaknesses The Power of Product Recommendation Networks | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of The Power of Product Recommendation Networks are -
Interest costs
– Compare to the competition, Networks Recommendation 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.
Compensation and incentives
– The revenue per employee as mentioned in the HBR case study The Power of Product Recommendation Networks, is just above the industry average. Networks Recommendation needs to redesign the compensation structure and incentives to increase the revenue per employees. Some of the steps that it can take are – hiring more specialists on project basis, etc.
Skills based hiring
– The stress on hiring functional specialists at Networks Recommendation 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.
Increasing silos among functional specialists
– The organizational structure of Networks Recommendation is dominated by functional specialists. It is not different from other players in the Leadership & Managing People segment. Networks Recommendation needs to de-silo the office environment to harness the true potential of its workforce. Secondly the de-silo will also help Networks Recommendation to focus more on services rather than just following the product oriented approach.
No frontier risks strategy
– After analyzing the HBR case study The Power of Product Recommendation Networks, it seems that company is thinking about the frontier risks that can impact Leadership & Managing People 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, Networks Recommendation 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.
High cash cycle compare to competitors
Networks Recommendation 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 The Power of Product Recommendation Networks, in the dynamic environment Networks Recommendation has struggled to respond to the nimble upstart competition. Networks Recommendation has reasonably good record with similar level competitors but it has struggled with new entrants taking away niches of its business.
Slow to harness new channels of communication
– Even though competitors are using new communication channels such as Instagram, Tiktok, and Snap, Networks Recommendation is slow explore the new channels of communication. These new channels of communication mentioned in marketing section of case study The Power of Product Recommendation Networks can help to provide better information regarding products and services. It can also build an online community to further reach out to potential customers.
Capital Spending Reduction
– Even during the low interest decade, Networks Recommendation has not been able to do capital spending to the tune of the competition. This has resulted into fewer innovations and company facing stiff competition from both existing competitors and new entrants who are disrupting the industry using digital technology.
Slow to strategic competitive environment developments
– As The Power of Product Recommendation Networks HBR case study mentions - Networks Recommendation 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.
Opportunities The Power of Product Recommendation Networks | 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 The Power of Product Recommendation Networks are -
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 Networks Recommendation in the consumer business. Now Networks Recommendation can target international markets with far fewer capital restrictions requirements than the existing system.
Reforming the budgeting process
- By establishing new metrics that will be used to evaluate both existing and potential projects Networks Recommendation can not only reduce the costs of the project but also help it in integrating the projects with other processes within the organization.
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 Networks Recommendation 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.
Redefining models of collaboration and team work
– As explained in the weaknesses section, Networks Recommendation is facing challenges because of the dominance of functional experts in the organization. The Power of Product Recommendation Networks 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.
Learning at scale
– Online learning technologies has now opened space for Networks Recommendation 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.
Remote work and new talent hiring opportunities
– The widespread usage of remote working technologies during Covid-19 has opened opportunities for Networks Recommendation 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 Networks Recommendation to hire the very best people irrespective of their geographical location.
Creating value in data economy
– The success of analytics program of Networks Recommendation has opened avenues for new revenue streams for the organization in the industry. This can help Networks Recommendation to build a more holistic ecosystem as suggested in the The Power of Product Recommendation Networks case study. Networks Recommendation can build new products and services such as - data insight services, data privacy related products, data based consulting services, etc.
Manufacturing automation
– Networks Recommendation can use the latest technology developments to improve its manufacturing and designing process in Leadership & Managing People 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.
Leveraging digital technologies
– Networks Recommendation 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.
Using analytics as competitive advantage
– Networks Recommendation 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 The Power of Product Recommendation Networks - to build a competitive advantage using analytics. The analytics driven competitive advantage can help Networks Recommendation to build faster Go To Market strategies, better consumer insights, developing relevant product features, and building a highly efficient supply chain.
Buying journey improvements
– Networks Recommendation can improve the customer journey of consumers in the industry by using analytics and artificial intelligence. The Power of Product Recommendation Networks 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.
Harnessing reconfiguration of the global supply chains
– As the trade war between US and China heats up in the coming years, Networks Recommendation 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, The Power of Product Recommendation Networks, to buy more products closer to the markets, and it can leverage its size and influence to get better deal from the local markets.
Changes in consumer behavior post Covid-19
– Consumer behavior has changed in the Leadership & Managing People industry because of Covid-19 restrictions. Some of this behavior will stay once things get back to normal. Networks Recommendation 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. Networks Recommendation 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.
Threats The Power of Product Recommendation Networks External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats mentioned in the HBR case study The Power of Product Recommendation Networks are -
Trade war between China and United States
– The trade war between two of the biggest economies can hugely impact the opportunities for Networks Recommendation in the Leadership & Managing People industry. The Leadership & Managing People 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.
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 Networks Recommendation in the Leadership & Managing People sector and impact the bottomline 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. Networks Recommendation 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.
Shortening product life cycle
– it is one of the major threat that Networks Recommendation is facing in Leadership & Managing People sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, etc.
Increasing wage structure of Networks Recommendation
– 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 Networks Recommendation.
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 Leadership & Managing People field will also reduce the barriers to entry in the industry, thus putting downward pressure on the prices because of increasing competition. Networks Recommendation can utilize it by borrowing at lower rates and invest it into research and development, capital expenditure to fortify its core competitive advantage.
Consumer confidence and its impact on Networks Recommendation 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.
Learning curve for new practices
– As the technology based on artificial intelligence and machine learning platform is getting complex, as highlighted in case study The Power of Product Recommendation Networks, Networks Recommendation may face longer learning curve for training and development of existing employees. This can open space for more nimble competitors in the field of Leadership & Managing People .
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.
Increasing international competition and downward pressure on margins
– Apart from technology driven competitive advantage dilution, Networks Recommendation 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 The Power of Product Recommendation Networks .
Barriers of entry lowering
– As technology is more democratized, the barriers to entry in the industry are lowering. It can presents Networks Recommendation with greater competitive threats in the near to medium future. Secondly it will also put downward pressure on pricing throughout the sector.
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 Networks Recommendation.
Weighted SWOT Analysis of The Power of Product Recommendation Networks 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 The Power of Product Recommendation Networks 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 The Power of Product Recommendation Networks 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 The Power of Product Recommendation Networks 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 The Power of Product Recommendation Networks 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 Networks Recommendation needs to make to build a sustainable competitive advantage.
