Data Applications (3848) SWOT Analysis / TOWS Matrix / MBA Resources
Software & Programming
Strategy / MBA Resources
Introduction to SWOT Analysis
SWOT Analysis / TOWS Matrix for Data Applications (Japan)
Based on various researches at Oak Spring University , Data Applications is operating in a macro-environment that has been destablized by – wage bills are increasing, increasing transportation and logistics costs, geopolitical disruptions, increasing commodity prices, there is increasing trade war between United States & China, increasing inequality as vast percentage of new income is going to the top 1%, banking and financial system is disrupted by Bitcoin and other crypto currencies,
challanges to central banks by blockchain based private currencies, increasing energy prices, etc
Introduction to SWOT Analysis of Data Applications
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University, we believe that Data Applications can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Data Applications, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Data Applications 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 Data Applications can be done for the following purposes –
1. Strategic planning of Data Applications
2. Improving business portfolio management of Data Applications
3. Assessing feasibility of the new initiative in Japan
4. Making a Software & Programming sector specific business decision
5. Set goals for the organization
6. Organizational restructuring of Data Applications
Strengths of Data Applications | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Data Applications are -
Organizational Resilience of Data Applications
– The covid-19 pandemic has put organizational resilience at the centre of everthing Data Applications does. Organizational resilience comprises - Financial Resilience, Operational Resilience, Technological Resilience, Organizational Resilience, Business Model Resilience, and Reputation Resilience.
Training and development
– Data Applications 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.
Strong track record of project management in the Software & Programming industry
– Data Applications is known for sticking to its project targets. This enables the firm to manage – time, project costs, and have sustainable margins on the projects.
Successful track record of launching new products
– Data Applications has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Data Applications 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.
Sustainable margins compare to other players in Software & Programming industry
– Data Applications has clearly differentiated products in the market place. This has enabled Data Applications to fetch slight price premium compare to the competitors in the Software & Programming industry. The sustainable margins have also helped Data Applications to invest into research and development (R&D) and innovation.
Ability to recruit top talent
– Data Applications is one of the leading players in the Software & Programming industry in Japan. It is in a position to attract the best talent available in Japan. The firm has a robust talent identification program that helps in identifying the brightest.
Low bargaining power of suppliers
– Suppliers of Data Applications in the Technology sector have low bargaining power. Data Applications has further diversified its suppliers portfolio by building a robust supply chain across various countries. This helps Data Applications to manage not only supply disruptions but also source products at highly competitive prices.
Cross disciplinary teams
– Horizontal connected teams at the Data Applications 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
– Data Applications has strong brand awareness and brand recognition among both - the exiting customers and potential new customers. Strong brand equity has enabled Data Applications to keep acquiring new customers and building profitable relationship with both the new and loyal customers.
Operational resilience
– The operational resilience strategy of Data Applications 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.
Effective Research and Development (R&D)
– Data Applications has innovation driven culture where significant part of the revenues are spent on the research and development activities. This has resulted in – Data Applications staying ahead in the Software & Programming industry in terms of – new product launches, superior customer experience, highly competitive pricing strategies, and great returns to the shareholders.
Highly skilled collaborators
– Data Applications 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 Data Applications have helped the firm to develop new products and bring them quickly to the marketplace.
Weaknesses of Data Applications | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Data Applications are -
Slow to harness new channels of communication
– Even though competitors are using new communication channels such as Instagram, Tiktok, and Snap, Data Applications is slow explore the new channels of communication. These new channels of communication can help Data Applications to provide better information regarding Software & Programming products and services. It can also build an online community to further reach out to potential customers.
Products dominated business model
– Even though Data Applications has some of the most successful models in the Software & Programming industry, this business model has made each new product launch extremely critical for continuous financial growth of the organization. Data Applications should strive to include more intangible value offerings along with its core products and services.
Slow to strategic competitive environment developments
– As Data Applications 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.
Compensation and incentives
– The revenue per employee of Data Applications 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.
Low market penetration in new markets
– Outside its home market of Japan, Data Applications needs to spend more promotional, marketing, and advertising efforts to penetrate international markets.
Capital Spending Reduction
– Even during the low interest decade, Data Applications 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.
Workers concerns about automation
– As automation is fast increasing in the Software & Programming industry, Data Applications 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.
Slow decision making process
– As mentioned earlier in the report, Data Applications 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. Data Applications 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.
Increasing silos among functional specialists
– The organizational structure of Data Applications is dominated by functional specialists. It is not different from other players in the Software & Programming industry, but Data Applications needs to de-silo the office environment to harness the true potential of its workforce. Secondly the de-silo will also help Data Applications to focus more on services in the Software & Programming industry rather than just following the product oriented approach.
High dependence on Data Applications ‘s star products
– The top 2 products and services of Data Applications 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 Data Applications has relatively successful track record of launching new products.
High operating costs
– Compare to the competitors, Data Applications 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 Data Applications lucrative customers.
Data Applications Opportunities | External Strategic Factors
What are Opportunities in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The opportunities of Data Applications are -
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. Data Applications can explore opportunities that can attract volunteers and are consistent with its mission and vision.
Increase in government spending
– As the United States and other governments are increasing social spending and infrastructure spending to build economies post Covid-19, Data Applications can use these opportunities to build new business models that can help the communities that Data Applications operates in. Secondly it can use opportunities from government spending in Software & Programming sector.
Lowering marketing communication costs
– 5G expansion will open new opportunities for Data Applications in the field of marketing communication. It will bring down the cost of doing business, provide technology platform to build new products in the Software & Programming industry, and it will provide faster access to the consumers.
Using analytics as competitive advantage
– Data Applications 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 Data Applications to build a competitive advantage using analytics. The analytics driven competitive advantage can help Data Applications to build faster Go To Market strategies, better consumer insights, developing relevant product features, and building a highly efficient supply chain.
Reforming the budgeting process
- By establishing new metrics that will be used to evaluate both existing and potential projects Data Applications can not only reduce the costs of the project but also help it in integrating the projects with other processes within the organization.
Low interest rates
– Even though inflation is raising its head in most developed economies, Data Applications 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.
Redefining models of collaboration and team work
– As explained in the weaknesses section, Data Applications is facing challenges because of the dominance of functional experts in the organization. Data Applications 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.
Developing new processes and practices
– Data Applications 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.
Leveraging digital technologies
– Data Applications 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.
Creating value in data economy
– The success of analytics program of Data Applications has opened avenues for new revenue streams for the organization in Software & Programming industry. This can help Data Applications to build a more holistic ecosystem for Data Applications products in the Software & Programming industry by providing – data insight services, data privacy related products, data based consulting services, etc.
Harnessing reconfiguration of the global supply chains
– As the trade war between US and China heats up in the coming years, Data Applications 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 Data Applications to buy more products closer to the markets, and it can leverage its size and influence to get better deal from the local markets.
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 Data Applications 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.
Manufacturing automation
– Data Applications 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.
Threats Data Applications External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats of Data Applications are -
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. Data Applications can utilize it by borrowing at lower rates and invest it into research and development, capital expenditure to fortify its core competitive advantage.
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.
Increasing international competition and downward pressure on margins
– Apart from technology driven competitive advantage dilution, Data Applications 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 Data Applications prominent markets.
Technology acceleration in Forth Industrial Revolution
– Data Applications has witnessed rapid integration of technology during Covid-19 in the Software & Programming industry. As one of the leading players in the industry, Data Applications needs to keep up with the evolution of technology in the Software & Programming 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.
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 Data Applications in the Software & Programming sector and impact the bottomline of the organization.
Shortening product life cycle
– it is one of the major threat that Data Applications is facing in Software & Programming sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, etc.
Stagnating economy with rate increase
– Data Applications 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 dependence on third party suppliers
– Data Applications 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.
Trade war between China and United States
– The trade war between two of the biggest economies can hugely impact the opportunities for Data Applications 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.
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 Data Applications.
Regulatory challenges
– Data Applications 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 Software & Programming industry regulations.
Learning curve for new practices
– As the technology based on artificial intelligence and machine learning platform is getting complex, Data Applications may face longer learning curve for training and development of existing employees. This can open space for more nimble competitors in the field of Software & Programming sector.
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 Data Applications Template, Example
Not all factors mentioned under the Strengths, Weakness, Opportunities, and Threats quadrants in the SWOT Analysis are equal. Managers at Data Applications 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 Data Applications 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 Data Applications 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 Data Applications 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 Data Applications needs to make to build a sustainable competitive advantage.
