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 – banking and financial system is disrupted by Bitcoin and other crypto currencies, there is backlash against globalization, digital marketing is dominated by two big players Facebook and Google, increasing transportation and logistics costs, increasing energy prices, cloud computing is disrupting traditional business models, competitive advantages are harder to sustain because of technology dispersion,
challanges to central banks by blockchain based private currencies, increasing household debt because of falling income levels, 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 -
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.
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.
Digital Transformation in Software & Programming industry
- digital transformation varies from industry to industry. For Data Applications digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Data Applications 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
– 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.
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.
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.
Ability to lead change in Software & Programming
– Data Applications is one of the leading players in the Software & Programming industry in Japan. Over the years it has not only transformed the business landscape in the Software & Programming industry in Japan but also across the existing markets. The ability to lead change has enabled Data Applications in – penetrating new markets, reaching out to new customers, and providing different value propositions to different customers in the international markets.
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.
Analytics focus
– Data Applications 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 Software & Programming industry. The technology infrastructure of Japan is also helping it to harness the power of analytics for – marketing optimization, demand forecasting, customer relationship management, inventory management, information sharing across the value chain etc.
Learning organization
- Data Applications 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 Data Applications is open place that encourages instructiveness, ideation, open minded discussions, and creativity. Employees and leaders at Data Applications emphasize – knowledge, initiative, and innovation.
High switching costs
– The high switching costs that Data Applications 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 of Data Applications | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Data Applications are -
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.
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 cash cycle compare to competitors
Data Applications has a high cash cycle compare to other players in the Software & Programming industry. It needs to shorten the cash cycle by 12% to be more competitive in the marketplace, reduce inventory costs, and be more profitable.
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.
High bargaining power of channel partners in Software & Programming industry
– because of the regulatory requirements in Japan, Data Applications 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.
Interest costs
– Compare to the competition, Data Applications 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.
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.
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.
Lack of clear differentiation of Data Applications products
– To increase the profitability and margins on the products, Data Applications needs to provide more differentiated products than what it is currently offering in the marketplace.
Need for greater diversity
– Data Applications 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.
Aligning sales with marketing
– From the outside it seems that Data Applications needs to have more collaboration between its sales team and marketing team. Sales professionals in the Software & Programming industry have deep experience in developing customer relationships. Marketing department at Data Applications can leverage the sales team experience to cultivate customer relationships as Data Applications is planning to shift buying processes online.
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.
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. Data Applications can tie-up with other value chain partners to explore new opportunities regarding meeting customer demands and building a rewarding and engaging relationship.
Building a culture of innovation
– managers at Data Applications can make experimentation a productive activity and build a culture of innovation using approaches such as – mining transaction data, A/B testing of websites and selling platforms, engaging potential customers over various needs, and building on small ideas in the Software & Programming industry.
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.
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.
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 Data Applications in the Software & Programming industry. Now Data Applications can target international markets with far fewer capital restrictions requirements than the existing system.
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.
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.
Buying journey improvements
– Data Applications 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.
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.
Better consumer reach
– The expansion of the 5G network will help Data Applications to increase its market reach. Data Applications 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, 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.
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.
Threats Data Applications External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats of Data Applications are -
Environmental challenges
– Data Applications 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. Data Applications can take advantage of this fund but it will also bring new competitors in the Software & Programming industry.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Increasing wage structure of Data Applications
– 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 Data Applications.
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 Data Applications business can come under increasing regulations regarding data privacy, data security, etc.
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.
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.