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Datawatch (DWCH) SWOT Analysis / TOWS Matrix / MBA Resources

Introduction to SWOT Analysis

SWOT Analysis / TOWS Matrix for Datawatch (United States)


Based on various researches at Oak Spring University , Datawatch is operating in a macro-environment that has been destablized by – customer relationship management is fast transforming because of increasing concerns over data privacy, wage bills are increasing, increasing transportation and logistics costs, increasing commodity prices, competitive advantages are harder to sustain because of technology dispersion, cloud computing is disrupting traditional business models, there is backlash against globalization, increasing energy prices, increasing government debt because of Covid-19 spendings, etc



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Introduction to SWOT Analysis of Datawatch


SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University, we believe that Datawatch can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Datawatch, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Datawatch 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 Datawatch can be done for the following purposes –
1. Strategic planning of Datawatch
2. Improving business portfolio management of Datawatch
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 Datawatch




Strengths of Datawatch | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis

The strengths of Datawatch are -

Analytics focus

– Datawatch 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 United States 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.

Operational resilience

– The operational resilience strategy of Datawatch 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.

Innovation driven organization

– Datawatch is one of the most innovative firm in Software & Programming sector.

Effective Research and Development (R&D)

– Datawatch has innovation driven culture where significant part of the revenues are spent on the research and development activities. This has resulted in – Datawatch 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.

Digital Transformation in Software & Programming industry

- digital transformation varies from industry to industry. For Datawatch digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Datawatch 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.

High switching costs

– The high switching costs that Datawatch 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.

Strong track record of project management in the Software & Programming industry

– Datawatch is known for sticking to its project targets. This enables the firm to manage – time, project costs, and have sustainable margins on the projects.

Ability to recruit top talent

– Datawatch is one of the leading players in the Software & Programming 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.

Learning organization

- Datawatch 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 Datawatch is open place that encourages instructiveness, ideation, open minded discussions, and creativity. Employees and leaders at Datawatch emphasize – knowledge, initiative, and innovation.

Organizational Resilience of Datawatch

– The covid-19 pandemic has put organizational resilience at the centre of everthing Datawatch does. Organizational resilience comprises - Financial Resilience, Operational Resilience, Technological Resilience, Organizational Resilience, Business Model Resilience, and Reputation Resilience.

Sustainable margins compare to other players in Software & Programming industry

– Datawatch has clearly differentiated products in the market place. This has enabled Datawatch to fetch slight price premium compare to the competitors in the Software & Programming industry. The sustainable margins have also helped Datawatch to invest into research and development (R&D) and innovation.

Low bargaining power of suppliers

– Suppliers of Datawatch in the Technology sector have low bargaining power. Datawatch has further diversified its suppliers portfolio by building a robust supply chain across various countries. This helps Datawatch to manage not only supply disruptions but also source products at highly competitive prices.






Weaknesses of Datawatch | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis

The weaknesses of Datawatch are -

Slow to harness new channels of communication

– Even though competitors are using new communication channels such as Instagram, Tiktok, and Snap, Datawatch is slow explore the new channels of communication. These new channels of communication can help Datawatch to provide better information regarding Software & Programming products and services. It can also build an online community to further reach out to potential customers.

Skills based hiring in Software & Programming industry

– The stress on hiring functional specialists at Datawatch 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.

Workers concerns about automation

– As automation is fast increasing in the Software & Programming industry, Datawatch 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.

Lack of clear differentiation of Datawatch products

– To increase the profitability and margins on the products, Datawatch needs to provide more differentiated products than what it is currently offering in the marketplace.

Slow to strategic competitive environment developments

– As Datawatch 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.

Employees’ less understanding of Datawatch strategy

– From the outside it seems that the employees of Datawatch 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.

Slow decision making process

– As mentioned earlier in the report, Datawatch 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. Datawatch 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 dependence on existing supply chain

– The disruption in the global supply chains because of the Covid-19 pandemic and blockage of the Suez Canal illustrated the fragile nature of Datawatch supply chain. Even after few cautionary changes, Datawatch is still heavily dependent upon the existing supply chain. The existing supply chain though brings in cost efficiencies but it has left Datawatch vulnerable to further global disruptions in South East Asia.

Need for greater diversity

– Datawatch 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.

High cash cycle compare to competitors

Datawatch 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.

Aligning sales with marketing

– From the outside it seems that Datawatch 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 Datawatch can leverage the sales team experience to cultivate customer relationships as Datawatch is planning to shift buying processes online.




Datawatch Opportunities | External Strategic Factors
What are Opportunities in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis


The opportunities of Datawatch are -

Harnessing reconfiguration of the global supply chains

– As the trade war between US and China heats up in the coming years, Datawatch 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 Datawatch to buy more products closer to the markets, and it can leverage its size and influence to get better deal from the local markets.

Remote work and new talent hiring opportunities

– The widespread usage of remote working technologies during Covid-19 has opened opportunities for Datawatch 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 Datawatch to hire the very best people irrespective of their geographical location.

Low interest rates

– Even though inflation is raising its head in most developed economies, Datawatch 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.

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. Datawatch can explore opportunities that can attract volunteers and are consistent with its mission and vision.

Reforming the budgeting process

- By establishing new metrics that will be used to evaluate both existing and potential projects Datawatch can not only reduce the costs of the project but also help it in integrating the projects with other processes within the organization.

Redefining models of collaboration and team work

– As explained in the weaknesses section, Datawatch is facing challenges because of the dominance of functional experts in the organization. Datawatch 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.

Changes in consumer behavior post Covid-19

– consumer behavior has changed in the Software & Programming industry because of Covid-19 restrictions. Some of this behavior will stay once things get back to normal. Datawatch 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. Datawatch 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.

Better consumer reach

– The expansion of the 5G network will help Datawatch to increase its market reach. Datawatch 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.

Leveraging digital technologies

– Datawatch 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.

Developing new processes and practices

– Datawatch 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.

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 Datawatch 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

– Datawatch 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 Datawatch to build a competitive advantage using analytics. The analytics driven competitive advantage can help Datawatch to build faster Go To Market strategies, better consumer insights, developing relevant product features, and building a highly efficient supply chain.

Buying journey improvements

– Datawatch 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.




Threats Datawatch External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis


The threats of Datawatch are -

Shortening product life cycle

– it is one of the major threat that Datawatch is facing in Software & Programming sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, etc.

Increasing wage structure of Datawatch

– 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 Datawatch.

Consumer confidence and its impact on Datawatch 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 Software & Programming industry and other sectors.

Environmental challenges

– Datawatch 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. Datawatch can take advantage of this fund but it will also bring new competitors in the Software & Programming industry.

Trade war between China and United States

– The trade war between two of the biggest economies can hugely impact the opportunities for Datawatch 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.

Barriers of entry lowering

– As technology is more democratized, the barriers to entry to Software & Programming industry are lowering. It can presents Datawatch with greater competitive threats in the near to medium future. Secondly it will also put downward pressure on pricing throughout the Software & Programming sector.

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. Datawatch can utilize it by borrowing at lower rates and invest it into research and development, capital expenditure to fortify its core competitive advantage.

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.

High dependence on third party suppliers

– Datawatch 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.

Increasing international competition and downward pressure on margins

– Apart from technology driven competitive advantage dilution, Datawatch 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 Datawatch prominent markets.

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. Datawatch 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.

Stagnating economy with rate increase

– Datawatch 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.

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 Datawatch.




Weighted SWOT Analysis of Datawatch Template, Example


Not all factors mentioned under the Strengths, Weakness, Opportunities, and Threats quadrants in the SWOT Analysis are equal. Managers at Datawatch 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 Datawatch 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 Datawatch 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 Datawatch 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 Datawatch needs to make to build a sustainable competitive advantage.



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