Relational Data Models in Enterprise-Level Information Systems SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
Technology & Operations
Strategy / MBA Resources
Case Study SWOT Analysis Solution
Case Study Description of Relational Data Models in Enterprise-Level Information Systems
Provides an overview of some important aspects of the relational data models that underlie today's enterprise-level information technologies, such as enterprise resource planning and customer relationship management. Key concepts covered include relational data and integration. A stylized example is provided.
Swot Analysis of "Relational Data Models in Enterprise-Level Information Systems" written by Mark Cotteleer includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Relational Enterprise facing as an external strategic factors. Some of the topics covered in Relational Data Models in Enterprise-Level Information Systems case study are - Strategic Management Strategies, IT and Technology & Operations.
Some of the macro environment factors that can be used to understand the Relational Data Models in Enterprise-Level Information Systems casestudy better are - – challanges to central banks by blockchain based private currencies, cloud computing is disrupting traditional business models, wage bills are increasing, geopolitical disruptions, technology disruption, banking and financial system is disrupted by Bitcoin and other crypto currencies, increasing household debt because of falling income levels,
increasing energy prices, increasing transportation and logistics costs, etc
Introduction to SWOT Analysis of Relational Data Models in Enterprise-Level Information Systems
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in Relational Data Models in Enterprise-Level Information Systems case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Relational Enterprise, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Relational Enterprise 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 Relational Data Models in Enterprise-Level Information Systems can be done for the following purposes –
1. Strategic planning using facts provided in Relational Data Models in Enterprise-Level Information Systems case study
2. Improving business portfolio management of Relational Enterprise
3. Assessing feasibility of the new initiative in Technology & Operations field.
4. Making a Technology & Operations topic specific business decision
5. Set goals for the organization
6. Organizational restructuring of Relational Enterprise
Strengths Relational Data Models in Enterprise-Level Information Systems | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Relational Enterprise in Relational Data Models in Enterprise-Level Information Systems Harvard Business Review case study are -
Highly skilled collaborators
– Relational Enterprise has highly efficient outsourcing and offshoring strategy. It has resulted in greater operational flexibility and bringing down the costs in highly price sensitive segment. Secondly the value chain collaborators of the firm in Relational Data Models in Enterprise-Level Information Systems HBR case study have helped the firm to develop new products and bring them quickly to the marketplace.
High brand equity
– Relational Enterprise has strong brand awareness and brand recognition among both - the exiting customers and potential new customers. Strong brand equity has enabled Relational Enterprise to keep acquiring new customers and building profitable relationship with both the new and loyal customers.
Cross disciplinary teams
– Horizontal connected teams at the Relational Enterprise 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.
Ability to recruit top talent
– Relational Enterprise is one of the leading recruiters in the industry. Managers in the Relational Data Models in Enterprise-Level Information Systems are in a position to attract the best talent available. The firm has a robust talent identification program that helps in identifying the brightest.
Innovation driven organization
– Relational Enterprise is one of the most innovative firm in sector. Manager in Relational Data Models in Enterprise-Level Information Systems Harvard Business Review case study can use Clayton Christensen Disruptive Innovation strategies to further increase the scale of innovtions in the organization.
Organizational Resilience of Relational Enterprise
– The covid-19 pandemic has put organizational resilience at the centre of everthing that Relational Enterprise does. Organizational resilience comprises - Financial Resilience, Operational Resilience, Technological Resilience, Organizational Resilience, Business Model Resilience, and Reputation Resilience.
Successful track record of launching new products
– Relational Enterprise has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Relational Enterprise 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.
Strong track record of project management
– Relational Enterprise 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
– Relational Enterprise 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 industry. The technology infrastructure suggested by Mark Cotteleer can also help 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 Technology & Operations industry
– Relational Data Models in Enterprise-Level Information Systems firm has clearly differentiated products in the market place. This has enabled Relational Enterprise to fetch slight price premium compare to the competitors in the Technology & Operations industry. The sustainable margins have also helped Relational Enterprise to invest into research and development (R&D) and innovation.
Effective Research and Development (R&D)
– Relational Enterprise has innovation driven culture where significant part of the revenues are spent on the research and development activities. This has resulted in, as mentioned in case study Relational Data Models in Enterprise-Level Information Systems - staying ahead in the 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 Relational Enterprise 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 Relational Data Models in Enterprise-Level Information Systems | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Relational Data Models in Enterprise-Level Information Systems are -
High bargaining power of channel partners
– Because of the regulatory requirements, Mark Cotteleer suggests that, Relational Enterprise 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 industry.
Aligning sales with marketing
– It come across in the case study Relational Data Models in Enterprise-Level Information Systems that the firm needs to have more collaboration between its sales team and marketing team. Sales professionals in the industry have deep experience in developing customer relationships. Marketing department in the case Relational Data Models in Enterprise-Level Information Systems can leverage the sales team experience to cultivate customer relationships as Relational Enterprise is planning to shift buying processes online.
Skills based hiring
– The stress on hiring functional specialists at Relational Enterprise 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.
Slow to strategic competitive environment developments
– As Relational Data Models in Enterprise-Level Information Systems HBR case study mentions - Relational Enterprise takes time to assess the upcoming competitions. This has led to missing out on atleast 2-3 big opportunities in the industry in last five years.
Increasing silos among functional specialists
– The organizational structure of Relational Enterprise is dominated by functional specialists. It is not different from other players in the Technology & Operations segment. Relational Enterprise needs to de-silo the office environment to harness the true potential of its workforce. Secondly the de-silo will also help Relational Enterprise to focus more on services rather than just following the product oriented approach.
Low market penetration in new markets
– Outside its home market of Relational Enterprise, firm in the HBR case study Relational Data Models in Enterprise-Level Information Systems needs to spend more promotional, marketing, and advertising efforts to penetrate international markets.
Workers concerns about automation
– As automation is fast increasing in the segment, Relational Enterprise 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.
Employees’ incomplete understanding of strategy
– From the instances in the HBR case study Relational Data Models in Enterprise-Level Information Systems, it seems that the employees of Relational Enterprise 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.
Ability to respond to the competition
– As the decision making is very deliberative, highlighted in the case study Relational Data Models in Enterprise-Level Information Systems, in the dynamic environment Relational Enterprise has struggled to respond to the nimble upstart competition. Relational Enterprise has reasonably good record with similar level competitors but it has struggled with new entrants taking away niches of its business.
Lack of clear differentiation of Relational Enterprise products
– To increase the profitability and margins on the products, Relational Enterprise needs to provide more differentiated products than what it is currently offering in the marketplace.
Compensation and incentives
– The revenue per employee as mentioned in the HBR case study Relational Data Models in Enterprise-Level Information Systems, is just above the industry average. Relational Enterprise 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.
Opportunities Relational Data Models in Enterprise-Level Information Systems | External Strategic Factors
What are Opportunities in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The opportunities highlighted in the Harvard Business Review case study Relational Data Models in Enterprise-Level Information Systems are -
Developing new processes and practices
– Relational Enterprise can develop new processes and procedures in Technology & Operations 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.
Finding new ways to collaborate
– Covid-19 has not only transformed business models of companies in Technology & Operations industry, but it has also influenced the consumer preferences. Relational Enterprise can tie-up with other value chain partners to explore new opportunities regarding meeting customer demands and building a rewarding and engaging relationship.
Buying journey improvements
– Relational Enterprise can improve the customer journey of consumers in the industry by using analytics and artificial intelligence. Relational Data Models in Enterprise-Level Information Systems suggest that firm 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.
Using analytics as competitive advantage
– Relational Enterprise has spent a significant amount of money and effort to integrate analytics and machine learning into its operations in the sector. This continuous investment in analytics has enabled, as illustrated in the Harvard case study Relational Data Models in Enterprise-Level Information Systems - to build a competitive advantage using analytics. The analytics driven competitive advantage can help Relational Enterprise to build faster Go To Market strategies, better consumer insights, developing relevant product features, and building a highly efficient supply chain.
Remote work and new talent hiring opportunities
– The widespread usage of remote working technologies during Covid-19 has opened opportunities for Relational Enterprise 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 Relational Enterprise to hire the very best people irrespective of their geographical location.
Increase in government spending
– As the United States and other governments are increasing social spending and infrastructure spending to build economies post Covid-19, Relational Enterprise can use these opportunities to build new business models that can help the communities that Relational Enterprise operates in. Secondly it can use opportunities from government spending in Technology & Operations sector.
Use of Bitcoin and other crypto currencies for transactions
– The popularity of Bitcoin and other crypto currencies as asset class and medium of transaction has opened new opportunities for Relational Enterprise in the consumer business. Now Relational Enterprise can target international markets with far fewer capital restrictions requirements than the existing system.
Better consumer reach
– The expansion of the 5G network will help Relational Enterprise to increase its market reach. Relational Enterprise 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.
Low interest rates
– Even though inflation is raising its head in most developed economies, Relational Enterprise 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, Relational Enterprise is facing challenges because of the dominance of functional experts in the organization. Relational Data Models in Enterprise-Level Information Systems case study suggests that firm can utilize new technology to build more coordinated teams and streamline operations and communications using tools such as CAD, Zoom, etc.
Learning at scale
– Online learning technologies has now opened space for Relational Enterprise 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.
Loyalty marketing
– Relational Enterprise 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 Relational Enterprise can not only reduce the costs of the project but also help it in integrating the projects with other processes within the organization.
Threats Relational Data Models in Enterprise-Level Information Systems External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats mentioned in the HBR case study Relational Data Models in Enterprise-Level Information Systems are -
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 Relational Enterprise in the Technology & Operations sector and impact the bottomline of the organization.
Shortening product life cycle
– it is one of the major threat that Relational Enterprise is facing in Technology & Operations sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, etc.
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
– Relational Enterprise 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 Technology & Operations industry regulations.
Stagnating economy with rate increase
– Relational Enterprise 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 field.
Trade war between China and United States
– The trade war between two of the biggest economies can hugely impact the opportunities for Relational Enterprise in the Technology & Operations industry. The Technology & Operations 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.
Increasing international competition and downward pressure on margins
– Apart from technology driven competitive advantage dilution, Relational Enterprise 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 prominent markets illustrated in HBR case study Relational Data Models in Enterprise-Level Information Systems .
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. Relational Enterprise needs to understand the core reasons impacting the Technology & Operations industry. This will help it in building a better workplace.
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 Relational Enterprise.
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. Relational Enterprise 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.
Consumer confidence and its impact on Relational Enterprise 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 the industry and other sectors.
Easy access to finance
– Easy access to finance in Technology & Operations field will also reduce the barriers to entry in the industry, thus putting downward pressure on the prices because of increasing competition. Relational Enterprise can utilize it by borrowing at lower rates and invest it into research and development, capital expenditure to fortify its core competitive advantage.
Weighted SWOT Analysis of Relational Data Models in Enterprise-Level Information Systems Template, Example
Not all factors mentioned under the Strengths, Weakness, Opportunities, and Threats quadrants in the SWOT Analysis are equal. Managers in the HBR case study Relational Data Models in Enterprise-Level Information Systems 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 the case study Relational Data Models in Enterprise-Level Information Systems 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 the Harvard case study Relational Data Models in Enterprise-Level Information Systems 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 Relational Data Models in Enterprise-Level Information Systems is 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 Relational Enterprise needs to make to build a sustainable competitive advantage.
