Merged Datasets: An Analytic Tool for Evidence-Based Management SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
Technology & Operations
Strategy / MBA Resources
Case Study SWOT Analysis Solution
Case Study Description of Merged Datasets: An Analytic Tool for Evidence-Based Management
Many businesses fail to merge and analyze data effectively. When data are merged from diverse independent sources across a business-something that is now practical and inexpensive-it becomes possible to conduct rigorous pretest-posttest comparisons of complex datasets with a precision, speed, and breadth that have not been practical until now. This article describes a method for merging independent datasets and using the compiled data to run informative quantitative analyses that facilitate sound decision making. This approach can help support several critical tasks in evidence-based management: documenting changes in the corporate culture; measuring linkages between "soft" perceptual variables and "hard" performance metrics; conducting rigorous pretest-posttest comparisons; and evaluating program effectiveness.
Authors :: Palmer Morrel-Samuels, Ed Francis, Steve Shucard
Swot Analysis of "Merged Datasets: An Analytic Tool for Evidence-Based Management" written by Palmer Morrel-Samuels, Ed Francis, Steve Shucard includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Datasets Posttest facing as an external strategic factors. Some of the topics covered in Merged Datasets: An Analytic Tool for Evidence-Based Management case study are - Strategic Management Strategies, Decision making and Technology & Operations.
Some of the macro environment factors that can be used to understand the Merged Datasets: An Analytic Tool for Evidence-Based Management casestudy better are - – there is increasing trade war between United States & China, wage bills are increasing, there is backlash against globalization, increasing transportation and logistics costs, increasing government debt because of Covid-19 spendings, competitive advantages are harder to sustain because of technology dispersion, digital marketing is dominated by two big players Facebook and Google,
geopolitical disruptions, challanges to central banks by blockchain based private currencies, etc
Introduction to SWOT Analysis of Merged Datasets: An Analytic Tool for Evidence-Based Management
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in Merged Datasets: An Analytic Tool for Evidence-Based Management case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Datasets Posttest, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Datasets Posttest 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 Merged Datasets: An Analytic Tool for Evidence-Based Management can be done for the following purposes –
1. Strategic planning using facts provided in Merged Datasets: An Analytic Tool for Evidence-Based Management case study
2. Improving business portfolio management of Datasets Posttest
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 Datasets Posttest
Strengths Merged Datasets: An Analytic Tool for Evidence-Based Management | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Datasets Posttest in Merged Datasets: An Analytic Tool for Evidence-Based Management Harvard Business Review case study are -
Organizational Resilience of Datasets Posttest
– The covid-19 pandemic has put organizational resilience at the centre of everthing that Datasets Posttest does. Organizational resilience comprises - Financial Resilience, Operational Resilience, Technological Resilience, Organizational Resilience, Business Model Resilience, and Reputation Resilience.
Ability to recruit top talent
– Datasets Posttest is one of the leading recruiters in the industry. Managers in the Merged Datasets: An Analytic Tool for Evidence-Based Management are in a position to attract the best talent available. The firm has a robust talent identification program that helps in identifying the brightest.
High brand equity
– Datasets Posttest has strong brand awareness and brand recognition among both - the exiting customers and potential new customers. Strong brand equity has enabled Datasets Posttest to keep acquiring new customers and building profitable relationship with both the new and loyal customers.
Superior customer experience
– The customer experience strategy of Datasets Posttest in the segment is based on four key concepts – personalization, simplification of complex needs, prompt response, and continuous engagement.
Analytics focus
– Datasets Posttest 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 Palmer Morrel-Samuels, Ed Francis, Steve Shucard 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.
Digital Transformation in Technology & Operations segment
- digital transformation varies from industry to industry. For Datasets Posttest digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Datasets Posttest 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.
Sustainable margins compare to other players in Technology & Operations industry
– Merged Datasets: An Analytic Tool for Evidence-Based Management firm has clearly differentiated products in the market place. This has enabled Datasets Posttest to fetch slight price premium compare to the competitors in the Technology & Operations industry. The sustainable margins have also helped Datasets Posttest to invest into research and development (R&D) and innovation.
Cross disciplinary teams
– Horizontal connected teams at the Datasets Posttest 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.
Operational resilience
– The operational resilience strategy in the Merged Datasets: An Analytic Tool for Evidence-Based Management 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.
Learning organization
- Datasets Posttest 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 Datasets Posttest is open place that encourages instructiveness, ideation, open minded discussions, and creativity. Employees and leaders in Merged Datasets: An Analytic Tool for Evidence-Based Management Harvard Business Review case study emphasize – knowledge, initiative, and innovation.
High switching costs
– The high switching costs that Datasets Posttest 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.
Successful track record of launching new products
– Datasets Posttest has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Datasets Posttest 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.
Weaknesses Merged Datasets: An Analytic Tool for Evidence-Based Management | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Merged Datasets: An Analytic Tool for Evidence-Based Management are -
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 Datasets Posttest supply chain. Even after few cautionary changes mentioned in the HBR case study - Merged Datasets: An Analytic Tool for Evidence-Based Management, it is still heavily dependent upon the existing supply chain. The existing supply chain though brings in cost efficiencies but it has left Datasets Posttest vulnerable to further global disruptions in South East Asia.
Increasing silos among functional specialists
– The organizational structure of Datasets Posttest is dominated by functional specialists. It is not different from other players in the Technology & Operations segment. Datasets Posttest needs to de-silo the office environment to harness the true potential of its workforce. Secondly the de-silo will also help Datasets Posttest to focus more on services rather than just following the product oriented approach.
Slow to strategic competitive environment developments
– As Merged Datasets: An Analytic Tool for Evidence-Based Management HBR case study mentions - Datasets Posttest 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.
Ability to respond to the competition
– As the decision making is very deliberative, highlighted in the case study Merged Datasets: An Analytic Tool for Evidence-Based Management, in the dynamic environment Datasets Posttest has struggled to respond to the nimble upstart competition. Datasets Posttest has reasonably good record with similar level competitors but it has struggled with new entrants taking away niches of its business.
High bargaining power of channel partners
– Because of the regulatory requirements, Palmer Morrel-Samuels, Ed Francis, Steve Shucard suggests that, Datasets Posttest 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.
Interest costs
– Compare to the competition, Datasets Posttest 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.
Compensation and incentives
– The revenue per employee as mentioned in the HBR case study Merged Datasets: An Analytic Tool for Evidence-Based Management, is just above the industry average. Datasets Posttest 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.
High cash cycle compare to competitors
Datasets Posttest 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.
Products dominated business model
– Even though Datasets Posttest 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 - Merged Datasets: An Analytic Tool for Evidence-Based Management should strive to include more intangible value offerings along with its core products and services.
High operating costs
– Compare to the competitors, firm in the HBR case study Merged Datasets: An Analytic Tool for Evidence-Based Management 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 Datasets Posttest 's lucrative customers.
High dependence on star products
– The top 2 products and services of the firm as mentioned in the Merged Datasets: An Analytic Tool for Evidence-Based Management HBR case study still accounts for major business revenue. This dependence on star products in has resulted into insufficient focus on developing new products, even though Datasets Posttest has relatively successful track record of launching new products.
Opportunities Merged Datasets: An Analytic Tool for Evidence-Based Management | 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 Merged Datasets: An Analytic Tool for Evidence-Based Management are -
Harnessing reconfiguration of the global supply chains
– As the trade war between US and China heats up in the coming years, Datasets Posttest 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, as suggested in case study, Merged Datasets: An Analytic Tool for Evidence-Based Management, to buy more products closer to the markets, and it can leverage its size and influence to get better deal from the local markets.
Redefining models of collaboration and team work
– As explained in the weaknesses section, Datasets Posttest is facing challenges because of the dominance of functional experts in the organization. Merged Datasets: An Analytic Tool for Evidence-Based Management 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.
Lowering marketing communication costs
– 5G expansion will open new opportunities for Datasets Posttest 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.
Developing new processes and practices
– Datasets Posttest 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.
Learning at scale
– Online learning technologies has now opened space for Datasets Posttest 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.
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. Datasets Posttest can tie-up with other value chain partners to explore new opportunities regarding meeting customer demands and building a rewarding and engaging relationship.
Low interest rates
– Even though inflation is raising its head in most developed economies, Datasets Posttest 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.
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. Datasets Posttest can explore opportunities that can attract volunteers and are consistent with its mission and vision.
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 Datasets Posttest in the consumer business. Now Datasets Posttest can target international markets with far fewer capital restrictions requirements than the existing system.
Reconfiguring business model
– The expansion of digital payment system, the bringing down of international transactions costs using Bitcoin and other blockchain based currencies, etc can help Datasets Posttest to reconfigure its entire business model. For example it can used blockchain based technologies to reduce piracy of its products in the big markets such as China. Secondly it can use the popularity of e-commerce in various developing markets to build a Direct to Customer business model rather than the current Channel Heavy distribution network.
Loyalty marketing
– Datasets Posttest 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.
Increase in government spending
– As the United States and other governments are increasing social spending and infrastructure spending to build economies post Covid-19, Datasets Posttest can use these opportunities to build new business models that can help the communities that Datasets Posttest operates in. Secondly it can use opportunities from government spending in Technology & Operations sector.
Using analytics as competitive advantage
– Datasets Posttest 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 Merged Datasets: An Analytic Tool for Evidence-Based Management - to build a competitive advantage using analytics. The analytics driven competitive advantage can help Datasets Posttest to build faster Go To Market strategies, better consumer insights, developing relevant product features, and building a highly efficient supply chain.
Threats Merged Datasets: An Analytic Tool for Evidence-Based Management External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats mentioned in the HBR case study Merged Datasets: An Analytic Tool for Evidence-Based Management are -
Consumer confidence and its impact on Datasets Posttest 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.
Barriers of entry lowering
– As technology is more democratized, the barriers to entry in the industry are lowering. It can presents Datasets Posttest with greater competitive threats in the near to medium future. Secondly it will also put downward pressure on pricing throughout the sector.
Trade war between China and United States
– The trade war between two of the biggest economies can hugely impact the opportunities for Datasets Posttest 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.
Technology acceleration in Forth Industrial Revolution
– Datasets Posttest has witnessed rapid integration of technology during Covid-19 in the Technology & Operations industry. As one of the leading players in the industry, Datasets Posttest 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.
Stagnating economy with rate increase
– Datasets Posttest 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.
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. Datasets Posttest can utilize it by borrowing at lower rates and invest it into research and development, capital expenditure to fortify its core competitive advantage.
Shortening product life cycle
– it is one of the major threat that Datasets Posttest is facing in Technology & Operations sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, 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 Datasets Posttest.
High dependence on third party suppliers
– Datasets Posttest 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.
Regulatory challenges
– Datasets Posttest 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.
Increasing wage structure of Datasets Posttest
– 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 Datasets Posttest.
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. Datasets Posttest needs to understand the core reasons impacting the Technology & Operations industry. This will help it in building a better workplace.
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 Datasets Posttest business can come under increasing regulations regarding data privacy, data security, etc.
Weighted SWOT Analysis of Merged Datasets: An Analytic Tool for Evidence-Based Management 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 Merged Datasets: An Analytic Tool for Evidence-Based Management 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 Merged Datasets: An Analytic Tool for Evidence-Based Management 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 Merged Datasets: An Analytic Tool for Evidence-Based Management 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 Merged Datasets: An Analytic Tool for Evidence-Based Management 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 Datasets Posttest needs to make to build a sustainable competitive advantage.