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 – competitive advantages are harder to sustain because of technology dispersion, central banks are concerned over increasing inflation, banking and financial system is disrupted by Bitcoin and other crypto currencies, increasing commodity prices, cloud computing is disrupting traditional business models, challanges to central banks by blockchain based private currencies, increasing transportation and logistics costs, talent flight as more people leaving formal jobs, technology disruption, 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.

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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

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

The strengths of Datawatch are -

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.

Ability to lead change in Software & Programming

– Datawatch is one of the leading players in the Software & Programming industry in United States. Over the years it has not only transformed the business landscape in the Software & Programming industry in United States but also across the existing markets. The ability to lead change has enabled Datawatch in – penetrating new markets, reaching out to new customers, and providing different value propositions to different customers in the international markets.

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.

Diverse revenue streams

– Datawatch is present in almost all the verticals within the Software & Programming industry. This has provided Datawatch a diverse revenue stream that has helped it to survive disruptions such as global pandemic in Covid-19, financial disruption of 2008, and supply chain disruption of 2021.

Training and development

– Datawatch 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.

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.

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.

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.

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.

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.

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

The weaknesses of Datawatch are -

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.

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.

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.

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.

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.

High bargaining power of channel partners in Software & Programming industry

– because of the regulatory requirements in United States, Datawatch 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, Datawatch 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.

Increasing silos among functional specialists

– The organizational structure of Datawatch is dominated by functional specialists. It is not different from other players in the Software & Programming industry, but Datawatch needs to de-silo the office environment to harness the true potential of its workforce. Secondly the de-silo will also help Datawatch to focus more on services in the Software & Programming industry rather than just following the product oriented approach.

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.

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.

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.

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

The opportunities of Datawatch are -

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.

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.

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.

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.

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.

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.

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.

Manufacturing automation

– Datawatch 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.

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.

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.

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.

Learning at scale

– Online learning technologies has now opened space for Datawatch to conduct training and development for its employees across the world. This will result in not only reducing the cost of training but also help employees in different part of the world to integrate with the headquarter work culture, ethos, and standards.

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.

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

The threats of Datawatch are -

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.

Learning curve for new practices

– As the technology based on artificial intelligence and machine learning platform is getting complex, Datawatch 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.

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.

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.

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.

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.

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 Datawatch business can come under increasing regulations regarding data privacy, data security, 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.

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 Datawatch in the Software & Programming sector and impact the bottomline of the organization.

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.

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.

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.

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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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