Tech Data (TECD) SWOT Analysis / TOWS Matrix / MBA Resources
Retail (Technology)
Strategy / MBA Resources
Introduction to SWOT Analysis
SWOT Analysis / TOWS Matrix for Tech Data (United States)
Based on various researches at Oak Spring University , Tech Data is operating in a macro-environment that has been destablized by – wage bills are increasing, increasing household debt because of falling income levels, customer relationship management is fast transforming because of increasing concerns over data privacy, talent flight as more people leaving formal jobs, there is backlash against globalization, supply chains are disrupted by pandemic , technology disruption,
increasing transportation and logistics costs, challanges to central banks by blockchain based private currencies, etc
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University, we believe that Tech Data can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Tech Data, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Tech Data 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 Tech Data can be done for the following purposes –
1. Strategic planning of Tech Data
2. Improving business portfolio management of Tech Data
3. Assessing feasibility of the new initiative in United States
4. Making a Retail (Technology) sector specific business decision
5. Set goals for the organization
6. Organizational restructuring of Tech Data
Strengths of Tech Data | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Tech Data are -
Digital Transformation in Retail (Technology) industry
- digital transformation varies from industry to industry. For Tech Data digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Tech Data 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.
Successful track record of launching new products
– Tech Data has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Tech Data 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.
Low bargaining power of suppliers
– Suppliers of Tech Data in the Services sector have low bargaining power. Tech Data has further diversified its suppliers portfolio by building a robust supply chain across various countries. This helps Tech Data to manage not only supply disruptions but also source products at highly competitive prices.
Ability to recruit top talent
– Tech Data is one of the leading players in the Retail (Technology) industry in United States. It is in a position to attract the best talent available in United States. The firm has a robust talent identification program that helps in identifying the brightest.
Ability to lead change in Retail (Technology)
– Tech Data is one of the leading players in the Retail (Technology) industry in United States. Over the years it has not only transformed the business landscape in the Retail (Technology) industry in United States but also across the existing markets. The ability to lead change has enabled Tech Data in – penetrating new markets, reaching out to new customers, and providing different value propositions to different customers in the international markets.
Operational resilience
– The operational resilience strategy of Tech Data comprises – understanding the underlying the factors in the Retail (Technology) 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 Retail (Technology) industry
– Tech Data has clearly differentiated products in the market place. This has enabled Tech Data to fetch slight price premium compare to the competitors in the Retail (Technology) industry. The sustainable margins have also helped Tech Data to invest into research and development (R&D) and innovation.
Cross disciplinary teams
– Horizontal connected teams at the Tech Data 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.
Highly skilled collaborators
– Tech Data has highly efficient outsourcing and offshoring strategy. It has resulted in greater operational flexibility and bringing down the costs in highly price sensitive Retail (Technology) industry. Secondly the value chain collaborators of Tech Data have helped the firm to develop new products and bring them quickly to the marketplace.
Superior customer experience
– The customer experience strategy of Tech Data in Retail (Technology) industry is based on four key concepts – personalization, simplification of complex needs, prompt response, and continuous engagement.
Effective Research and Development (R&D)
– Tech Data has innovation driven culture where significant part of the revenues are spent on the research and development activities. This has resulted in – Tech Data staying ahead in the Retail (Technology) industry in terms of – new product launches, superior customer experience, highly competitive pricing strategies, and great returns to the shareholders.
Strong track record of project management in the Retail (Technology) industry
– Tech Data is known for sticking to its project targets. This enables the firm to manage – time, project costs, and have sustainable margins on the projects.
Weaknesses of Tech Data | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Tech Data are -
No frontier risks strategy
– From the 10K / annual statement of Tech Data, it seems that company is thinking out the frontier risks that can impact Retail (Technology) industry. 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.
Ability to respond to the competition
– As the decision making is very deliberative at Tech Data, in the dynamic environment of Retail (Technology) industry it has struggled to respond to the nimble upstart competition. Tech Data has reasonably good record with similar level competitors but it has struggled with new entrants taking away niches of its business.
Slow decision making process
– As mentioned earlier in the report, Tech Data has a very deliberative decision making approach. This approach has resulted in prudent decisions, but it has also resulted in missing opportunities in the Retail (Technology) industry over the last five years. Tech Data 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.
Employees’ less understanding of Tech Data strategy
– From the outside it seems that the employees of Tech Data 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.
Skills based hiring in Retail (Technology) industry
– The stress on hiring functional specialists at Tech Data has created an environment where the organization is dominated by functional specialists rather than management generalist. This has resulted into product oriented approach rather than marketing oriented approach or consumers oriented approach.
Capital Spending Reduction
– Even during the low interest decade, Tech Data 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 Retail (Technology) industry using digital technology.
High bargaining power of channel partners in Retail (Technology) industry
– because of the regulatory requirements in United States, Tech Data 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 Retail (Technology) industry.
High cash cycle compare to competitors
Tech Data has a high cash cycle compare to other players in the Retail (Technology) industry. It needs to shorten the cash cycle by 12% to be more competitive in the marketplace, reduce inventory costs, and be more profitable.
Slow to harness new channels of communication
– Even though competitors are using new communication channels such as Instagram, Tiktok, and Snap, Tech Data is slow explore the new channels of communication. These new channels of communication can help Tech Data to provide better information regarding Retail (Technology) products and services. It can also build an online community to further reach out to potential customers.
Workers concerns about automation
– As automation is fast increasing in the Retail (Technology) industry, Tech Data 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.
Need for greater diversity
– Tech Data 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.
Tech Data Opportunities | External Strategic Factors
What are Opportunities in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The opportunities of Tech Data 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. Tech Data can explore opportunities that can attract volunteers and are consistent with its mission and vision.
Developing new processes and practices
– Tech Data can develop new processes and procedures in Retail (Technology) 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.
Increase in government spending
– As the United States and other governments are increasing social spending and infrastructure spending to build economies post Covid-19, Tech Data can use these opportunities to build new business models that can help the communities that Tech Data operates in. Secondly it can use opportunities from government spending in Retail (Technology) sector.
Changes in consumer behavior post Covid-19
– consumer behavior has changed in the Retail (Technology) industry because of Covid-19 restrictions. Some of this behavior will stay once things get back to normal. Tech Data 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. Tech Data 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.
Redefining models of collaboration and team work
– As explained in the weaknesses section, Tech Data is facing challenges because of the dominance of functional experts in the organization. Tech Data can utilize new technology in the field of Retail (Technology) industry to build more coordinated teams and streamline operations and communications using tools such as CAD, Zoom, etc.
Manufacturing automation
– Tech Data can use the latest technology developments to improve its manufacturing and designing process in Retail (Technology) 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 Tech Data 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.
Building a culture of innovation
– managers at Tech Data 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 Retail (Technology) industry.
Reforming the budgeting process
- By establishing new metrics that will be used to evaluate both existing and potential projects Tech Data can not only reduce the costs of the project but also help it in integrating the projects with other processes within the organization.
Better consumer reach
– The expansion of the 5G network will help Tech Data to increase its market reach. Tech Data 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.
Remote work and new talent hiring opportunities
– The widespread usage of remote working technologies during Covid-19 has opened opportunities for Tech Data 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 Tech Data to hire the very best people irrespective of their geographical location.
Lowering marketing communication costs
– 5G expansion will open new opportunities for Tech Data in the field of marketing communication. It will bring down the cost of doing business, provide technology platform to build new products in the Retail (Technology) industry, and it will provide faster access to the consumers.
Loyalty marketing
– Tech Data has focused on building a highly responsive customer relationship management platform. This platform is built on in-house data and driven by analytics and artificial intelligence. The customer analytics can help the organization to fine tune its loyalty marketing efforts, increase the wallet share of the organization, reduce wastage on mainstream advertising spending, build better pricing strategies using personalization, etc.
Threats Tech Data External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats of Tech Data are -
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.
Trade war between China and United States
– The trade war between two of the biggest economies can hugely impact the opportunities for Tech Data in Retail (Technology) industry. The Retail (Technology) 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.
Barriers of entry lowering
– As technology is more democratized, the barriers to entry to Retail (Technology) industry are lowering. It can presents Tech Data with greater competitive threats in the near to medium future. Secondly it will also put downward pressure on pricing throughout the Retail (Technology) sector.
Learning curve for new practices
– As the technology based on artificial intelligence and machine learning platform is getting complex, Tech Data may face longer learning curve for training and development of existing employees. This can open space for more nimble competitors in the field of Retail (Technology) sector.
Consumer confidence and its impact on Tech Data demand
– There is a high probability of declining consumer confidence, given – high inflammation rate, rise of gig economy, lower job stability, increasing cost of living, higher interest rates, and aging demography. All the factors contribute to people saving higher rate of their income, resulting in lower consumer demand in Retail (Technology) industry and other sectors.
Environmental challenges
– Tech Data 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. Tech Data can take advantage of this fund but it will also bring new competitors in the Retail (Technology) industry.
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.
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 Tech Data in the Retail (Technology) sector and impact the bottomline of the organization.
Stagnating economy with rate increase
– Tech Data 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 Retail (Technology) industry.
Technology acceleration in Forth Industrial Revolution
– Tech Data has witnessed rapid integration of technology during Covid-19 in the Retail (Technology) industry. As one of the leading players in the industry, Tech Data needs to keep up with the evolution of technology in the Retail (Technology) 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.
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. Tech Data 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.
Regulatory challenges
– Tech Data 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 Retail (Technology) industry regulations.
Shortening product life cycle
– it is one of the major threat that Tech Data is facing in Retail (Technology) sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, etc.
Weighted SWOT Analysis of Tech Data Template, Example
Not all factors mentioned under the Strengths, Weakness, Opportunities, and Threats quadrants in the SWOT Analysis are equal. Managers at Tech Data 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 Tech Data 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 Tech Data 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 Tech Data 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 Tech Data needs to make to build a sustainable competitive advantage.