The Subtle Sources of Sampling Bias Hiding in Your Data SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
Innovation & Entrepreneurship
Strategy / MBA Resources
Case Study SWOT Analysis Solution
Case Study Description of The Subtle Sources of Sampling Bias Hiding in Your Data
Plummeting data acquisition costs have been a big part of the surge in business analytics. We have much richer samples of data to use for insight. But more data doesn't inherently remove sampling bias; in fact, it may make it worse.
Swot Analysis of "The Subtle Sources of Sampling Bias Hiding in Your Data" written by Sam Ransbotham includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Sampling Bias facing as an external strategic factors. Some of the topics covered in The Subtle Sources of Sampling Bias Hiding in Your Data case study are - Strategic Management Strategies, and Innovation & Entrepreneurship.
Some of the macro environment factors that can be used to understand the The Subtle Sources of Sampling Bias Hiding in Your Data casestudy better are - – wage bills are increasing, increasing commodity prices, talent flight as more people leaving formal jobs, there is increasing trade war between United States & China, geopolitical disruptions, there is backlash against globalization, challanges to central banks by blockchain based private currencies,
supply chains are disrupted by pandemic , competitive advantages are harder to sustain because of technology dispersion, etc
Introduction to SWOT Analysis of The Subtle Sources of Sampling Bias Hiding in Your Data
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in The Subtle Sources of Sampling Bias Hiding in Your Data case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Sampling Bias, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Sampling Bias 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 The Subtle Sources of Sampling Bias Hiding in Your Data can be done for the following purposes –
1. Strategic planning using facts provided in The Subtle Sources of Sampling Bias Hiding in Your Data case study
2. Improving business portfolio management of Sampling Bias
3. Assessing feasibility of the new initiative in Innovation & Entrepreneurship field.
4. Making a Innovation & Entrepreneurship topic specific business decision
5. Set goals for the organization
6. Organizational restructuring of Sampling Bias
Strengths The Subtle Sources of Sampling Bias Hiding in Your Data | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Sampling Bias in The Subtle Sources of Sampling Bias Hiding in Your Data Harvard Business Review case study are -
Training and development
– Sampling Bias has one of the best training and development program in the industry. The effectiveness of the training programs can be measured in The Subtle Sources of Sampling Bias Hiding in Your Data 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.
Learning organization
- Sampling Bias 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 Sampling Bias is open place that encourages instructiveness, ideation, open minded discussions, and creativity. Employees and leaders in The Subtle Sources of Sampling Bias Hiding in Your Data Harvard Business Review case study emphasize – knowledge, initiative, and innovation.
Superior customer experience
– The customer experience strategy of Sampling Bias in the segment is based on four key concepts – personalization, simplification of complex needs, prompt response, and continuous engagement.
Digital Transformation in Innovation & Entrepreneurship segment
- digital transformation varies from industry to industry. For Sampling Bias digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Sampling Bias 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.
Operational resilience
– The operational resilience strategy in the The Subtle Sources of Sampling Bias Hiding in Your Data 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.
Analytics focus
– Sampling Bias 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 Sam Ransbotham 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.
Cross disciplinary teams
– Horizontal connected teams at the Sampling Bias 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.
Strong track record of project management
– Sampling Bias is known for sticking to its project targets. This enables the firm to manage – time, project costs, and have sustainable margins on the projects.
Successful track record of launching new products
– Sampling Bias has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Sampling Bias 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.
Effective Research and Development (R&D)
– Sampling Bias 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 The Subtle Sources of Sampling Bias Hiding in Your Data - 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 brand equity
– Sampling Bias has strong brand awareness and brand recognition among both - the exiting customers and potential new customers. Strong brand equity has enabled Sampling Bias to keep acquiring new customers and building profitable relationship with both the new and loyal customers.
Low bargaining power of suppliers
– Suppliers of Sampling Bias in the sector have low bargaining power. The Subtle Sources of Sampling Bias Hiding in Your Data has further diversified its suppliers portfolio by building a robust supply chain across various countries. This helps Sampling Bias to manage not only supply disruptions but also source products at highly competitive prices.
Weaknesses The Subtle Sources of Sampling Bias Hiding in Your Data | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of The Subtle Sources of Sampling Bias Hiding in Your Data are -
High operating costs
– Compare to the competitors, firm in the HBR case study The Subtle Sources of Sampling Bias Hiding in Your Data 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 Sampling Bias 's lucrative customers.
Slow to harness new channels of communication
– Even though competitors are using new communication channels such as Instagram, Tiktok, and Snap, Sampling Bias is slow explore the new channels of communication. These new channels of communication mentioned in marketing section of case study The Subtle Sources of Sampling Bias Hiding in Your Data can help to provide better information regarding products and services. It can also build an online community to further reach out to potential customers.
Ability to respond to the competition
– As the decision making is very deliberative, highlighted in the case study The Subtle Sources of Sampling Bias Hiding in Your Data, in the dynamic environment Sampling Bias has struggled to respond to the nimble upstart competition. Sampling Bias has reasonably good record with similar level competitors but it has struggled with new entrants taking away niches of its business.
No frontier risks strategy
– After analyzing the HBR case study The Subtle Sources of Sampling Bias Hiding in Your Data, it seems that company is thinking about the frontier risks that can impact Innovation & Entrepreneurship strategy. But it has very little resources allocation to manage the risks emerging from events such as natural disasters, climate change, melting of permafrost, tacking the rise of artificial intelligence, opportunities and threats emerging from commercialization of space etc.
Increasing silos among functional specialists
– The organizational structure of Sampling Bias is dominated by functional specialists. It is not different from other players in the Innovation & Entrepreneurship segment. Sampling Bias needs to de-silo the office environment to harness the true potential of its workforce. Secondly the de-silo will also help Sampling Bias to focus more on services rather than just following the product oriented approach.
High dependence on star products
– The top 2 products and services of the firm as mentioned in the The Subtle Sources of Sampling Bias Hiding in Your Data 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 Sampling Bias has relatively successful track record of launching new products.
Employees’ incomplete understanding of strategy
– From the instances in the HBR case study The Subtle Sources of Sampling Bias Hiding in Your Data, it seems that the employees of Sampling Bias 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.
Compensation and incentives
– The revenue per employee as mentioned in the HBR case study The Subtle Sources of Sampling Bias Hiding in Your Data, is just above the industry average. Sampling Bias 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.
Skills based hiring
– The stress on hiring functional specialists at Sampling Bias 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.
Capital Spending Reduction
– Even during the low interest decade, Sampling Bias 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 industry using digital technology.
High cash cycle compare to competitors
Sampling Bias 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.
Opportunities The Subtle Sources of Sampling Bias Hiding in Your Data | 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 The Subtle Sources of Sampling Bias Hiding in Your Data are -
Lowering marketing communication costs
– 5G expansion will open new opportunities for Sampling Bias in the field of marketing communication. It will bring down the cost of doing business, provide technology platform to build new products in the Innovation & Entrepreneurship segment, and it will provide faster access to the consumers.
Increase in government spending
– As the United States and other governments are increasing social spending and infrastructure spending to build economies post Covid-19, Sampling Bias can use these opportunities to build new business models that can help the communities that Sampling Bias operates in. Secondly it can use opportunities from government spending in Innovation & Entrepreneurship sector.
Reforming the budgeting process
- By establishing new metrics that will be used to evaluate both existing and potential projects Sampling Bias can not only reduce the costs of the project but also help it in integrating the projects with other processes within the organization.
Redefining models of collaboration and team work
– As explained in the weaknesses section, Sampling Bias is facing challenges because of the dominance of functional experts in the organization. The Subtle Sources of Sampling Bias Hiding in Your Data 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.
Harnessing reconfiguration of the global supply chains
– As the trade war between US and China heats up in the coming years, Sampling Bias 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, The Subtle Sources of Sampling Bias Hiding in Your Data, to buy more products closer to the markets, and it can leverage its size and influence to get better deal from the local markets.
Buying journey improvements
– Sampling Bias can improve the customer journey of consumers in the industry by using analytics and artificial intelligence. The Subtle Sources of Sampling Bias Hiding in Your Data 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
– Sampling Bias 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 The Subtle Sources of Sampling Bias Hiding in Your Data - to build a competitive advantage using analytics. The analytics driven competitive advantage can help Sampling Bias to build faster Go To Market strategies, better consumer insights, developing relevant product features, and building a highly efficient supply chain.
Loyalty marketing
– Sampling Bias 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.
Creating value in data economy
– The success of analytics program of Sampling Bias has opened avenues for new revenue streams for the organization in the industry. This can help Sampling Bias to build a more holistic ecosystem as suggested in the The Subtle Sources of Sampling Bias Hiding in Your Data case study. Sampling Bias 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 Sampling Bias 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 Innovation & Entrepreneurship segment.
Learning at scale
– Online learning technologies has now opened space for Sampling Bias 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.
Better consumer reach
– The expansion of the 5G network will help Sampling Bias to increase its market reach. Sampling Bias 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.
Manufacturing automation
– Sampling Bias can use the latest technology developments to improve its manufacturing and designing process in Innovation & Entrepreneurship 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 The Subtle Sources of Sampling Bias Hiding in Your Data External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats mentioned in the HBR case study The Subtle Sources of Sampling Bias Hiding in Your Data are -
Stagnating economy with rate increase
– Sampling Bias 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 Sampling Bias in the Innovation & Entrepreneurship industry. The Innovation & Entrepreneurship 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.
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 Sampling Bias.
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.
Increasing wage structure of Sampling Bias
– 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 Sampling Bias.
Technology acceleration in Forth Industrial Revolution
– Sampling Bias has witnessed rapid integration of technology during Covid-19 in the Innovation & Entrepreneurship industry. As one of the leading players in the industry, Sampling Bias needs to keep up with the evolution of technology in the Innovation & Entrepreneurship 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.
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. Sampling Bias 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.
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 Sampling Bias in the Innovation & Entrepreneurship sector and impact the bottomline of the organization.
Learning curve for new practices
– As the technology based on artificial intelligence and machine learning platform is getting complex, as highlighted in case study The Subtle Sources of Sampling Bias Hiding in Your Data, Sampling Bias may face longer learning curve for training and development of existing employees. This can open space for more nimble competitors in the field of Innovation & Entrepreneurship .
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 Sampling Bias business can come under increasing regulations regarding data privacy, data security, etc.
High dependence on third party suppliers
– Sampling Bias 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.
Barriers of entry lowering
– As technology is more democratized, the barriers to entry in the industry are lowering. It can presents Sampling Bias with greater competitive threats in the near to medium future. Secondly it will also put downward pressure on pricing throughout the sector.
Shortening product life cycle
– it is one of the major threat that Sampling Bias is facing in Innovation & Entrepreneurship sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, etc.
Weighted SWOT Analysis of The Subtle Sources of Sampling Bias Hiding in Your Data 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 The Subtle Sources of Sampling Bias Hiding in Your Data 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 The Subtle Sources of Sampling Bias Hiding in Your Data 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 The Subtle Sources of Sampling Bias Hiding in Your Data 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 The Subtle Sources of Sampling Bias Hiding in Your Data 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 Sampling Bias needs to make to build a sustainable competitive advantage.
