SWOT Analysis / TOWS Matrix for Scientific Learning (United States)
Based on various researches at Oak Spring University , Scientific Learning is operating in a macro-environment that has been destablized by – central banks are concerned over increasing inflation, increasing commodity prices, technology disruption, banking and financial system is disrupted by Bitcoin and other crypto currencies, talent flight as more people leaving formal jobs, increasing transportation and logistics costs, supply chains are disrupted by pandemic ,
geopolitical disruptions, increasing government debt because of Covid-19 spendings, etc
Introduction to SWOT Analysis of Scientific Learning
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University, we believe that Scientific Learning can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Scientific Learning, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Scientific Learning 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 Scientific Learning can be done for the following purposes –
1. Strategic planning of Scientific Learning
2. Improving business portfolio management of Scientific Learning
3. Assessing feasibility of the new initiative in United States
4. Making a Software & Programming sector specific business decision
5. Set goals for the organization
6. Organizational restructuring of Scientific Learning
Strengths of Scientific Learning | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Scientific Learning are -
High brand equity
– Scientific Learning has strong brand awareness and brand recognition among both - the exiting customers and potential new customers. Strong brand equity has enabled Scientific Learning to keep acquiring new customers and building profitable relationship with both the new and loyal customers.
Operational resilience
– The operational resilience strategy of Scientific Learning comprises – understanding the underlying the factors in the Software & Programming 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.
Highly skilled collaborators
– Scientific Learning has highly efficient outsourcing and offshoring strategy. It has resulted in greater operational flexibility and bringing down the costs in highly price sensitive Software & Programming industry. Secondly the value chain collaborators of Scientific Learning have helped the firm to develop new products and bring them quickly to the marketplace.
Learning organization
- Scientific Learning 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 Scientific Learning is open place that encourages instructiveness, ideation, open minded discussions, and creativity. Employees and leaders at Scientific Learning emphasize – knowledge, initiative, and innovation.
Low bargaining power of suppliers
– Suppliers of Scientific Learning in the Technology sector have low bargaining power. Scientific Learning has further diversified its suppliers portfolio by building a robust supply chain across various countries. This helps Scientific Learning to manage not only supply disruptions but also source products at highly competitive prices.
Sustainable margins compare to other players in Software & Programming industry
– Scientific Learning has clearly differentiated products in the market place. This has enabled Scientific Learning to fetch slight price premium compare to the competitors in the Software & Programming industry. The sustainable margins have also helped Scientific Learning to invest into research and development (R&D) and innovation.
Innovation driven organization
– Scientific Learning is one of the most innovative firm in Software & Programming sector.
Superior customer experience
– The customer experience strategy of Scientific Learning in Software & Programming industry is based on four key concepts – personalization, simplification of complex needs, prompt response, and continuous engagement.
High switching costs
– The high switching costs that Scientific Learning 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.
Digital Transformation in Software & Programming industry
- digital transformation varies from industry to industry. For Scientific Learning digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Scientific Learning 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.
Strong track record of project management in the Software & Programming industry
– Scientific Learning is known for sticking to its project targets. This enables the firm to manage – time, project costs, and have sustainable margins on the projects.
Training and development
– Scientific Learning has one of the best training and development program in Technology industry. The effectiveness of the training programs can be measured in – employees retention, in-house promotion, loyalty, new venture initiation, lack of conflict, and high level of both employees and customer engagement.
Weaknesses of Scientific Learning | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Scientific Learning are -
Slow to strategic competitive environment developments
– As Scientific Learning is one of the leading players in the Software & Programming industry, it takes time to assess the upcoming competitions. This has led to missing out on atleast 2-3 big opportunities in the Software & Programming industry in last five years.
High bargaining power of channel partners in Software & Programming industry
– because of the regulatory requirements in United States, Scientific Learning 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 Software & Programming industry.
Need for greater diversity
– Scientific Learning 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.
Increasing silos among functional specialists
– The organizational structure of Scientific Learning is dominated by functional specialists. It is not different from other players in the Software & Programming industry, but Scientific Learning needs to de-silo the office environment to harness the true potential of its workforce. Secondly the de-silo will also help Scientific Learning to focus more on services in the Software & Programming industry rather than just following the product oriented approach.
High dependence on Scientific Learning ‘s star products
– The top 2 products and services of Scientific Learning still accounts for major business revenue. This dependence on star products in Software & Programming industry has resulted into insufficient focus on developing new products, even though Scientific Learning has relatively successful track record of launching new products.
Slow decision making process
– As mentioned earlier in the report, Scientific Learning has a very deliberative decision making approach. This approach has resulted in prudent decisions, but it has also resulted in missing opportunities in the Software & Programming industry over the last five years. Scientific Learning 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.
High operating costs
– Compare to the competitors, Scientific Learning has high operating costs in the Software & Programming industry. This can be harder to sustain given the new emerging competition from nimble players who are using technology to attract Scientific Learning lucrative customers.
Capital Spending Reduction
– Even during the low interest decade, Scientific Learning 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 Software & Programming industry using digital technology.
Interest costs
– Compare to the competition, Scientific Learning 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 of Scientific Learning is just above the Software & Programming industry average. It 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.
Employees’ less understanding of Scientific Learning strategy
– From the outside it seems that the employees of Scientific Learning 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.
Scientific Learning Opportunities | External Strategic Factors
What are Opportunities in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The opportunities of Scientific Learning are -
Finding new ways to collaborate
– Covid-19 has not only transformed business models of companies in Software & Programming industry, but it has also influenced the consumer preferences. Scientific Learning can tie-up with other value chain partners to explore new opportunities regarding meeting customer demands and building a rewarding and engaging relationship.
Learning at scale
– Online learning technologies has now opened space for Scientific Learning 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.
Buying journey improvements
– Scientific Learning can improve the customer journey of consumers in the Software & Programming industry by using analytics and artificial intelligence. It 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.
Use of Bitcoin and other crypto currencies for transactions in Software & Programming industry
– The popularity of Bitcoin and other crypto currencies as asset class and medium of transaction has opened new opportunities for Scientific Learning in the Software & Programming industry. Now Scientific Learning can target international markets with far fewer capital restrictions requirements than the existing system.
Remote work and new talent hiring opportunities
– The widespread usage of remote working technologies during Covid-19 has opened opportunities for Scientific Learning 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 Scientific Learning to hire the very best people irrespective of their geographical location.
Manufacturing automation
– Scientific Learning can use the latest technology developments to improve its manufacturing and designing process in Software & Programming sector. 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.
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 Scientific Learning 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.
Using analytics as competitive advantage
– Scientific Learning has spent a significant amount of money and effort to integrate analytics and machine learning into its operations in Software & Programming sector. This continuous investment in analytics has enabled Scientific Learning to build a competitive advantage using analytics. The analytics driven competitive advantage can help Scientific Learning to build faster Go To Market strategies, better consumer insights, developing relevant product features, and building a highly efficient supply chain.
Better consumer reach
– The expansion of the 5G network will help Scientific Learning to increase its market reach. Scientific Learning 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.
Redefining models of collaboration and team work
– As explained in the weaknesses section, Scientific Learning is facing challenges because of the dominance of functional experts in the organization. Scientific Learning can utilize new technology in the field of Software & Programming industry to build more coordinated teams and streamline operations and communications using tools such as CAD, Zoom, etc.
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. Scientific Learning can explore opportunities that can attract volunteers and are consistent with its mission and vision.
Developing new processes and practices
– Scientific Learning can develop new processes and procedures in Software & Programming 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.
Low interest rates
– Even though inflation is raising its head in most developed economies, Scientific Learning 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 Scientific Learning External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats of Scientific Learning are -
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. Scientific Learning 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.
High dependence on third party suppliers
– Scientific Learning 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.
Easy access to finance
– Easy access to finance in Software & Programming industry will also reduce the barriers to entry in the industry, thus putting downward pressure on the prices because of increasing competition. Scientific Learning can utilize it by borrowing at lower rates and invest it into research and development, capital expenditure to fortify its core competitive advantage.
Environmental challenges
– Scientific Learning 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. Scientific Learning can take advantage of this fund but it will also bring new competitors in the Software & Programming industry.
Increasing international competition and downward pressure on margins
– Apart from technology driven competitive advantage dilution, Scientific Learning 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 Scientific Learning prominent markets.
Barriers of entry lowering
– As technology is more democratized, the barriers to entry to Software & Programming industry are lowering. It can presents Scientific Learning with greater competitive threats in the near to medium future. Secondly it will also put downward pressure on pricing throughout the Software & Programming sector.
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.
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 Scientific Learning business can come under increasing regulations regarding data privacy, data security, etc.
Trade war between China and United States
– The trade war between two of the biggest economies can hugely impact the opportunities for Scientific Learning in Software & Programming industry. The Software & Programming 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.
Stagnating economy with rate increase
– Scientific Learning 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 Software & Programming industry.
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. Scientific Learning needs to understand the core reasons impacting the Software & Programming industry. This will help it in building a better workplace.
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 wage structure of Scientific Learning
– 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 Scientific Learning.
Weighted SWOT Analysis of Scientific Learning Template, Example
Not all factors mentioned under the Strengths, Weakness, Opportunities, and Threats quadrants in the SWOT Analysis are equal. Managers at Scientific Learning 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 Scientific Learning 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 Scientific Learning 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 Scientific Learning 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 Scientific Learning needs to make to build a sustainable competitive advantage.