Solving the Problems of New Product Forecasting SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
Global Business
Strategy / MBA Resources
Case Study SWOT Analysis Solution
Case Study Description of Solving the Problems of New Product Forecasting
An important consideration in solving the problems of new product forecasting entails distinguishing new product forecasting from the process of forecasting existing products. Particular differences between the two can be identified across the dimensions of data, analytics, forecast, plan, and measurement. For example, new product forecasting features little to no data with which to begin the process, whereas data are available and accessible in forecasting existing products. The minimal data situation requires a qualitative approach that lays out assumptions to provide transparency; in contrast, quantitative techniques are predominantly used when forecasting existing products. Different assumptions help construct a range of new product forecast outcomes on which company contingencies can be planned versus a singular point forecast for an existing product. And the measure of forecast accuracy, which is a common metric in forecasting existing products, must give way to meaningfulness so that the new product forecast is actionable. Recognizing new product forecasting as a cross-functional, company-wide process helps resolve the problems of new product forecasting. While incapable of remedying all problems, a properly understood and organized new product forecasting effort can help the company better prepare, execute, and support a new product launch, affording a greater propensity to achieve new product success.
Swot Analysis of "Solving the Problems of New Product Forecasting" written by Kenneth B Kahn includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Forecasting Forecast facing as an external strategic factors. Some of the topics covered in Solving the Problems of New Product Forecasting case study are - Strategic Management Strategies, Forecasting, Marketing and Global Business.
Some of the macro environment factors that can be used to understand the Solving the Problems of New Product Forecasting casestudy better are - – there is backlash against globalization, wage bills are increasing, competitive advantages are harder to sustain because of technology dispersion, central banks are concerned over increasing inflation, increasing commodity prices, challanges to central banks by blockchain based private currencies, supply chains are disrupted by pandemic ,
talent flight as more people leaving formal jobs, increasing energy prices, etc
Introduction to SWOT Analysis of Solving the Problems of New Product Forecasting
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in Solving the Problems of New Product Forecasting case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Forecasting Forecast, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Forecasting Forecast 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 Solving the Problems of New Product Forecasting can be done for the following purposes –
1. Strategic planning using facts provided in Solving the Problems of New Product Forecasting case study
2. Improving business portfolio management of Forecasting Forecast
3. Assessing feasibility of the new initiative in Global Business field.
4. Making a Global Business topic specific business decision
5. Set goals for the organization
6. Organizational restructuring of Forecasting Forecast
Strengths Solving the Problems of New Product Forecasting | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Forecasting Forecast in Solving the Problems of New Product Forecasting Harvard Business Review case study are -
Digital Transformation in Global Business segment
- digital transformation varies from industry to industry. For Forecasting Forecast digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Forecasting Forecast 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.
Low bargaining power of suppliers
– Suppliers of Forecasting Forecast in the sector have low bargaining power. Solving the Problems of New Product Forecasting has further diversified its suppliers portfolio by building a robust supply chain across various countries. This helps Forecasting Forecast to manage not only supply disruptions but also source products at highly competitive prices.
Effective Research and Development (R&D)
– Forecasting Forecast 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 Solving the Problems of New Product Forecasting - staying ahead in the industry in terms of – new product launches, superior customer experience, highly competitive pricing strategies, and great returns to the shareholders.
High brand equity
– Forecasting Forecast has strong brand awareness and brand recognition among both - the exiting customers and potential new customers. Strong brand equity has enabled Forecasting Forecast to keep acquiring new customers and building profitable relationship with both the new and loyal customers.
Organizational Resilience of Forecasting Forecast
– The covid-19 pandemic has put organizational resilience at the centre of everthing that Forecasting Forecast does. Organizational resilience comprises - Financial Resilience, Operational Resilience, Technological Resilience, Organizational Resilience, Business Model Resilience, and Reputation Resilience.
Learning organization
- Forecasting Forecast 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 Forecasting Forecast is open place that encourages instructiveness, ideation, open minded discussions, and creativity. Employees and leaders in Solving the Problems of New Product Forecasting Harvard Business Review case study emphasize – knowledge, initiative, and innovation.
Diverse revenue streams
– Forecasting Forecast is present in almost all the verticals within the industry. This has provided firm in Solving the Problems of New Product Forecasting 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.
Highly skilled collaborators
– Forecasting Forecast 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 Solving the Problems of New Product Forecasting HBR case study have helped the firm to develop new products and bring them quickly to the marketplace.
Ability to recruit top talent
– Forecasting Forecast is one of the leading recruiters in the industry. Managers in the Solving the Problems of New Product Forecasting are in a position to attract the best talent available. The firm has a robust talent identification program that helps in identifying the brightest.
Successful track record of launching new products
– Forecasting Forecast has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Forecasting Forecast 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.
Innovation driven organization
– Forecasting Forecast is one of the most innovative firm in sector. Manager in Solving the Problems of New Product Forecasting Harvard Business Review case study can use Clayton Christensen Disruptive Innovation strategies to further increase the scale of innovtions in the organization.
High switching costs
– The high switching costs that Forecasting Forecast 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.
Weaknesses Solving the Problems of New Product Forecasting | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Solving the Problems of New Product Forecasting are -
Lack of clear differentiation of Forecasting Forecast products
– To increase the profitability and margins on the products, Forecasting Forecast needs to provide more differentiated products than what it is currently offering in the marketplace.
High bargaining power of channel partners
– Because of the regulatory requirements, Kenneth B Kahn suggests that, Forecasting Forecast 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.
Slow decision making process
– As mentioned earlier in the report, Forecasting Forecast has a very deliberative decision making approach. This approach has resulted in prudent decisions, but it has also resulted in missing opportunities in the industry over the last five years. Forecasting Forecast even though has strong showing on digital transformation primary two stages, it has struggled to capitalize the power of digital transformation in marketing efforts and new venture efforts.
Interest costs
– Compare to the competition, Forecasting Forecast 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.
Increasing silos among functional specialists
– The organizational structure of Forecasting Forecast is dominated by functional specialists. It is not different from other players in the Global Business segment. Forecasting Forecast needs to de-silo the office environment to harness the true potential of its workforce. Secondly the de-silo will also help Forecasting Forecast to focus more on services rather than just following the product oriented approach.
Products dominated business model
– Even though Forecasting Forecast 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 - Solving the Problems of New Product Forecasting should strive to include more intangible value offerings along with its core products and services.
Workers concerns about automation
– As automation is fast increasing in the segment, Forecasting Forecast 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.
Employees’ incomplete understanding of strategy
– From the instances in the HBR case study Solving the Problems of New Product Forecasting, it seems that the employees of Forecasting Forecast 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, Forecasting Forecast 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 cash cycle compare to competitors
Forecasting Forecast 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.
No frontier risks strategy
– After analyzing the HBR case study Solving the Problems of New Product Forecasting, it seems that company is thinking about the frontier risks that can impact Global Business 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.
Opportunities Solving the Problems of New Product Forecasting | 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 Solving the Problems of New Product Forecasting are -
Remote work and new talent hiring opportunities
– The widespread usage of remote working technologies during Covid-19 has opened opportunities for Forecasting Forecast 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 Forecasting Forecast to hire the very best people irrespective of their geographical location.
Creating value in data economy
– The success of analytics program of Forecasting Forecast has opened avenues for new revenue streams for the organization in the industry. This can help Forecasting Forecast to build a more holistic ecosystem as suggested in the Solving the Problems of New Product Forecasting case study. Forecasting Forecast can build new products and services such as - data insight services, data privacy related products, data based consulting services, etc.
Developing new processes and practices
– Forecasting Forecast can develop new processes and procedures in Global Business 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.
Better consumer reach
– The expansion of the 5G network will help Forecasting Forecast to increase its market reach. Forecasting Forecast 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.
Buying journey improvements
– Forecasting Forecast can improve the customer journey of consumers in the industry by using analytics and artificial intelligence. Solving the Problems of New Product Forecasting 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.
Low interest rates
– Even though inflation is raising its head in most developed economies, Forecasting Forecast 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.
Finding new ways to collaborate
– Covid-19 has not only transformed business models of companies in Global Business industry, but it has also influenced the consumer preferences. Forecasting Forecast can tie-up with other value chain partners to explore new opportunities regarding meeting customer demands and building a rewarding and engaging relationship.
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. Forecasting Forecast can explore opportunities that can attract volunteers and are consistent with its mission and vision.
Learning at scale
– Online learning technologies has now opened space for Forecasting Forecast 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.
Using analytics as competitive advantage
– Forecasting Forecast 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 Solving the Problems of New Product Forecasting - to build a competitive advantage using analytics. The analytics driven competitive advantage can help Forecasting Forecast to build faster Go To Market strategies, better consumer insights, developing relevant product features, and building a highly efficient supply chain.
Changes in consumer behavior post Covid-19
– Consumer behavior has changed in the Global Business industry because of Covid-19 restrictions. Some of this behavior will stay once things get back to normal. Forecasting Forecast 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. Forecasting Forecast 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.
Leveraging digital technologies
– Forecasting Forecast 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.
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 Forecasting Forecast 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 Solving the Problems of New Product Forecasting External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats mentioned in the HBR case study Solving the Problems of New Product Forecasting are -
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.
High level of anxiety and lack of motivation
– the Great Resignation in United States is the sign of broader dissatisfaction among the workforce in United States. Forecasting Forecast needs to understand the core reasons impacting the Global Business industry. This will help it in building a better workplace.
Environmental challenges
– Forecasting Forecast 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. Forecasting Forecast can take advantage of this fund but it will also bring new competitors in the Global Business industry.
Easy access to finance
– Easy access to finance in Global Business field will also reduce the barriers to entry in the industry, thus putting downward pressure on the prices because of increasing competition. Forecasting Forecast can utilize it by borrowing at lower rates and invest it into research and development, capital expenditure to fortify its core competitive advantage.
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 Forecasting Forecast.
Shortening product life cycle
– it is one of the major threat that Forecasting Forecast is facing in Global Business sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, etc.
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 Forecasting Forecast in the Global Business sector and impact the bottomline of the organization.
Increasing wage structure of Forecasting Forecast
– 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 Forecasting Forecast.
Learning curve for new practices
– As the technology based on artificial intelligence and machine learning platform is getting complex, as highlighted in case study Solving the Problems of New Product Forecasting, Forecasting Forecast may face longer learning curve for training and development of existing employees. This can open space for more nimble competitors in the field of Global Business .
Regulatory challenges
– Forecasting Forecast 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 Global Business industry regulations.
Technology acceleration in Forth Industrial Revolution
– Forecasting Forecast has witnessed rapid integration of technology during Covid-19 in the Global Business industry. As one of the leading players in the industry, Forecasting Forecast needs to keep up with the evolution of technology in the Global Business 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.
Increasing international competition and downward pressure on margins
– Apart from technology driven competitive advantage dilution, Forecasting Forecast 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 Solving the Problems of New Product Forecasting .
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.
Weighted SWOT Analysis of Solving the Problems of New Product Forecasting 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 Solving the Problems of New Product Forecasting 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 Solving the Problems of New Product Forecasting 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 Solving the Problems of New Product Forecasting 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 Solving the Problems of New Product Forecasting 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 Forecasting Forecast needs to make to build a sustainable competitive advantage.