Datawatch (DWCH) SWOT Analysis / TOWS Matrix / MBA Resources
Software & Programming
Strategy / 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 – 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, challanges to central banks by blockchain based private currencies, supply chains are disrupted by pandemic , increasing transportation and logistics costs, increasing energy prices, increasing household debt because of falling income levels,
central banks are concerned over increasing inflation, increasing government debt because of Covid-19 spendings, etc
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 -
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Weaknesses of Datawatch | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Datawatch are -
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.
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.
Low market penetration in new markets
– Outside its home market of United States, Datawatch needs to spend more promotional, marketing, and advertising efforts to penetrate international markets.
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.
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.
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.
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.
Capital Spending Reduction
– Even during the low interest decade, Datawatch 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.
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.
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.
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.
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.
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.
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.
Lowering marketing communication costs
– 5G expansion will open new opportunities for Datawatch in the field of marketing communication. It will bring down the cost of doing business, provide technology platform to build new products in the Software & Programming industry, and it will provide faster access to the consumers.
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.
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.
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.
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.
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.
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.
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. Datawatch can tie-up with other value chain partners to explore new opportunities regarding meeting customer demands and building a rewarding and engaging relationship.
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.
Threats Datawatch External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats of Datawatch are -
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.