Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
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Case Study Description of Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture
Many software products in the market today handle big data and conduct advanced analytics. One of these is Statistical Analysis System (SAS), a popular software program especially in advanced analytics and data management. Many organizations, both federal and private, organize their databases in SAS format. The main hurdle which limits the number of SAS users, besides the high cost of its one-year only licenses, is a much steeper learning curve than is typical for other software such as STATA and Eviews. Students are often amazed by how simple it is to generate these statistics from raw data in SAS and are further motivated to learn SAS. This teaching material uses an application-oriented approach, with solving practical questions as the main takeaway.
Swot Analysis of "Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture" written by Yunwei Gai includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Sas Data facing as an external strategic factors. Some of the topics covered in Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture case study are - Strategic Management Strategies, IT and Technology & Operations.
Some of the macro environment factors that can be used to understand the Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture casestudy better are - – supply chains are disrupted by pandemic , wage bills are increasing, there is increasing trade war between United States & China, banking and financial system is disrupted by Bitcoin and other crypto currencies, challanges to central banks by blockchain based private currencies, digital marketing is dominated by two big players Facebook and Google, increasing government debt because of Covid-19 spendings,
increasing inequality as vast percentage of new income is going to the top 1%, increasing household debt because of falling income levels, etc
Introduction to SWOT Analysis of Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Sas Data, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Sas Data 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 Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture can be done for the following purposes –
1. Strategic planning using facts provided in Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture case study
2. Improving business portfolio management of Sas Data
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 Sas Data
Strengths Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Sas Data in Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture Harvard Business Review case study are -
Superior customer experience
– The customer experience strategy of Sas Data in the segment is based on four key concepts – personalization, simplification of complex needs, prompt response, and continuous engagement.
Innovation driven organization
– Sas Data is one of the most innovative firm in sector. Manager in Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture Harvard Business Review case study can use Clayton Christensen Disruptive Innovation strategies to further increase the scale of innovtions in the organization.
Diverse revenue streams
– Sas Data is present in almost all the verticals within the industry. This has provided firm in Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture case study 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.
Analytics focus
– Sas Data 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 Yunwei Gai 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.
Training and development
– Sas Data has one of the best training and development program in the industry. The effectiveness of the training programs can be measured in Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture Harvard Business Review case study by analyzing – employees retention, in-house promotion, loyalty, new venture initiation, lack of conflict, and high level of both employees and customer engagement.
Effective Research and Development (R&D)
– Sas Data 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 Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture - staying ahead in the industry in terms of – new product launches, superior customer experience, highly competitive pricing strategies, and great returns to the shareholders.
Learning organization
- Sas Data 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 Sas Data is open place that encourages instructiveness, ideation, open minded discussions, and creativity. Employees and leaders in Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture Harvard Business Review case study emphasize – knowledge, initiative, and innovation.
Digital Transformation in Technology & Operations segment
- digital transformation varies from industry to industry. For Sas Data digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Sas Data has successfully integrated the four key components of digital transformation – digital integration in processes, digital integration in marketing and customer relationship management, digital integration into the value chain, and using technology to explore new products and market opportunities.
High brand equity
– Sas Data has strong brand awareness and brand recognition among both - the exiting customers and potential new customers. Strong brand equity has enabled Sas Data to keep acquiring new customers and building profitable relationship with both the new and loyal customers.
Low bargaining power of suppliers
– Suppliers of Sas Data in the sector have low bargaining power. Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture has further diversified its suppliers portfolio by building a robust supply chain across various countries. This helps Sas Data to manage not only supply disruptions but also source products at highly competitive prices.
Ability to recruit top talent
– Sas Data is one of the leading recruiters in the industry. Managers in the Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture are in a position to attract the best talent available. The firm has a robust talent identification program that helps in identifying the brightest.
Operational resilience
– The operational resilience strategy in the Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture Harvard Business Review case study comprises – understanding the underlying the factors in the 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.
Weaknesses Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture are -
Slow to strategic competitive environment developments
– As Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture HBR case study mentions - Sas Data 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.
High cash cycle compare to competitors
Sas Data has a high cash cycle compare to other players in the 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 operating costs
– Compare to the competitors, firm in the HBR case study Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture has high operating costs in the. This can be harder to sustain given the new emerging competition from nimble players who are using technology to attract Sas Data 's lucrative customers.
Products dominated business model
– Even though Sas Data has some of the most successful products in the industry, this business model has made each new product launch extremely critical for continuous financial growth of the organization. firm in the HBR case study - Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture should strive to include more intangible value offerings along with its core products and services.
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 Sas Data supply chain. Even after few cautionary changes mentioned in the HBR case study - Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture, it is still heavily dependent upon the existing supply chain. The existing supply chain though brings in cost efficiencies but it has left Sas Data vulnerable to further global disruptions in South East Asia.
High bargaining power of channel partners
– Because of the regulatory requirements, Yunwei Gai suggests that, Sas Data 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.
Need for greater diversity
– Sas Data 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.
Aligning sales with marketing
– It come across in the case study Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture 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 Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture can leverage the sales team experience to cultivate customer relationships as Sas Data is planning to shift buying processes online.
Lack of clear differentiation of Sas Data products
– To increase the profitability and margins on the products, Sas Data needs to provide more differentiated products than what it is currently offering in the marketplace.
Employees’ incomplete understanding of strategy
– From the instances in the HBR case study Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture, it seems that the employees of Sas Data 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.
Low market penetration in new markets
– Outside its home market of Sas Data, firm in the HBR case study Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture needs to spend more promotional, marketing, and advertising efforts to penetrate international markets.
Opportunities Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture | 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 Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture are -
Low interest rates
– Even though inflation is raising its head in most developed economies, Sas Data 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.
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. Sas Data can tie-up with other value chain partners to explore new opportunities regarding meeting customer demands and building a rewarding and engaging relationship.
Using analytics as competitive advantage
– Sas Data 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 Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture - to build a competitive advantage using analytics. The analytics driven competitive advantage can help Sas Data to build faster Go To Market strategies, better consumer insights, developing relevant product features, and building a highly efficient supply chain.
Lowering marketing communication costs
– 5G expansion will open new opportunities for Sas Data in the field of marketing communication. It will bring down the cost of doing business, provide technology platform to build new products in the Technology & Operations segment, and it will provide faster access to the consumers.
Buying journey improvements
– Sas Data can improve the customer journey of consumers in the industry by using analytics and artificial intelligence. Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture 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.
Leveraging digital technologies
– Sas Data 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.
Creating value in data economy
– The success of analytics program of Sas Data has opened avenues for new revenue streams for the organization in the industry. This can help Sas Data to build a more holistic ecosystem as suggested in the Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture case study. Sas Data can build new products and services such as - data insight services, data privacy related products, data based consulting services, etc.
Building a culture of innovation
– managers at Sas Data 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 Technology & Operations segment.
Developing new processes and practices
– Sas Data 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.
Redefining models of collaboration and team work
– As explained in the weaknesses section, Sas Data is facing challenges because of the dominance of functional experts in the organization. Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture 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 Sas Data 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
– Sas Data 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.
Manufacturing automation
– Sas Data can use the latest technology developments to improve its manufacturing and designing process in Technology & Operations segment. 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.
Threats Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats mentioned in the HBR case study Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture are -
High dependence on third party suppliers
– Sas Data 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.
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. Sas Data 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 Sas Data 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.
Regulatory challenges
– Sas Data 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.
Barriers of entry lowering
– As technology is more democratized, the barriers to entry in the industry are lowering. It can presents Sas Data with greater competitive threats in the near to medium future. Secondly it will also put downward pressure on pricing throughout the sector.
Environmental challenges
– Sas Data 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. Sas Data can take advantage of this fund but it will also bring new competitors in the Technology & Operations industry.
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 Sas Data in the Technology & Operations sector and impact the bottomline of the organization.
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. Sas Data can utilize it by borrowing at lower rates and invest it into research and development, capital expenditure to fortify its core competitive advantage.
Stagnating economy with rate increase
– Sas Data 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.
Increasing wage structure of Sas Data
– 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 Sas Data.
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 Sas Data business can come under increasing regulations regarding data privacy, data security, etc.
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 Sas Data.
Technology acceleration in Forth Industrial Revolution
– Sas Data has witnessed rapid integration of technology during Covid-19 in the Technology & Operations industry. As one of the leading players in the industry, Sas Data needs to keep up with the evolution of technology in the Technology & Operations sector. According to Mckinsey study top managers believe that the adoption of technology in operations, communications is 20-25 times faster than what they planned in the beginning of 2019.
Weighted SWOT Analysis of Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture 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 Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture 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 Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture 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 Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture 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 Analyze Big Data Using SAS: An Interactive Goal Oriented Approach: The Complete Lecture 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 Sas Data needs to make to build a sustainable competitive advantage.
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