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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 – there is backlash against globalization, customer relationship management is fast transforming because of increasing concerns over data privacy, supply chains are disrupted by pandemic , geopolitical disruptions, technology disruption, increasing household debt because of falling income levels, increasing inequality as vast percentage of new income is going to the top 1%, digital marketing is dominated by two big players Facebook and Google, talent flight as more people leaving formal jobs, 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 -

High brand equity

– Datawatch has strong brand awareness and brand recognition among both - the exiting customers and potential new customers. Strong brand equity has enabled Datawatch to keep acquiring new customers and building profitable relationship with both the new and loyal customers.

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.

Cross disciplinary teams

– Horizontal connected teams at the Datawatch 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

– Datawatch 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 Datawatch have helped the firm to develop new products and bring them quickly to the marketplace.

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.

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.

Superior customer experience

– The customer experience strategy of Datawatch in Software & Programming industry is based on four key concepts – personalization, simplification of complex needs, prompt response, and continuous engagement.

Innovation driven organization

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

Successful track record of launching new products

– Datawatch has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Datawatch 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.

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.

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.

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.






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

The weaknesses of Datawatch are -

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.

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.

High dependence on Datawatch ‘s star products

– The top 2 products and services of Datawatch 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 Datawatch has relatively successful track record of launching new products.

Products dominated business model

– Even though Datawatch 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. Datawatch should strive to include more intangible value offerings along with its core products and services.

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.

Ability to respond to the competition

– As the decision making is very deliberative at Datawatch, in the dynamic environment of Software & Programming industry it has struggled to respond to the nimble upstart competition. Datawatch has reasonably good record with similar level competitors but it has struggled with new entrants taking away niches of its business.

High operating costs

– Compare to the competitors, Datawatch 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 Datawatch lucrative customers.

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.

Compensation and incentives

– The revenue per employee of Datawatch 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.

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.

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.




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


The opportunities of Datawatch are -

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.

Loyalty marketing

– Datawatch 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.

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.

Building a culture of innovation

– managers at Datawatch 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.

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.

Creating value in data economy

– The success of analytics program of Datawatch has opened avenues for new revenue streams for the organization in Software & Programming industry. This can help Datawatch to build a more holistic ecosystem for Datawatch products in the Software & Programming industry by providing – data insight services, data privacy related products, data based consulting services, etc.

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 Datawatch in the Software & Programming industry. Now Datawatch can target international markets with far fewer capital restrictions requirements than the existing system.

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.

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.

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.

Increase in government spending

– As the United States and other governments are increasing social spending and infrastructure spending to build economies post Covid-19, Datawatch can use these opportunities to build new business models that can help the communities that Datawatch operates in. Secondly it can use opportunities from government spending in Software & Programming sector.

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.




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


The threats of Datawatch are -

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.

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.

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.

High level of anxiety and lack of motivation

– the Great Resignation in United States is the sign of broader dissatisfaction among the workforce in United States. Datawatch needs to understand the core reasons impacting the Software & Programming industry. This will help it in building a better workplace.

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.

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.

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.

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.

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.

Regulatory challenges

– Datawatch 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.

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.

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.




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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