Data Analytics: From Bias to Better Decisions SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
Strategy & Execution
Strategy / MBA Resources
Case Study SWOT Analysis Solution
Case Study Description of Data Analytics: From Bias to Better Decisions
Even with impressively large data sets and the best analytics tools, we are still vulnerable to a range of decision-making pitfalls, especially when information overload leads us to take shortcuts in reasoning. As a result, in some instances, data and analytics actually make matters worse. The authors show that leaders need to be aware of three common data-related decision making pitfalls: the confirmation trap, the over-confidence trap and the over-fitting trap. They describe each in detail and provide practical tips for overcoming each type of bias.
Swot Analysis of "Data Analytics: From Bias to Better Decisions" written by Megan MacGarvie, Kristina McElheran includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Trap Analytics facing as an external strategic factors. Some of the topics covered in Data Analytics: From Bias to Better Decisions case study are - Strategic Management Strategies, Strategy and Strategy & Execution.
Some of the macro environment factors that can be used to understand the Data Analytics: From Bias to Better Decisions casestudy better are - – competitive advantages are harder to sustain because of technology dispersion, customer relationship management is fast transforming because of increasing concerns over data privacy, talent flight as more people leaving formal jobs, cloud computing is disrupting traditional business models, wage bills are increasing, increasing inequality as vast percentage of new income is going to the top 1%, technology disruption,
geopolitical disruptions, banking and financial system is disrupted by Bitcoin and other crypto currencies, etc
Introduction to SWOT Analysis of Data Analytics: From Bias to Better Decisions
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in Data Analytics: From Bias to Better Decisions case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Trap Analytics, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Trap Analytics 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 Data Analytics: From Bias to Better Decisions can be done for the following purposes –
1. Strategic planning using facts provided in Data Analytics: From Bias to Better Decisions case study
2. Improving business portfolio management of Trap Analytics
3. Assessing feasibility of the new initiative in Strategy & Execution field.
4. Making a Strategy & Execution topic specific business decision
5. Set goals for the organization
6. Organizational restructuring of Trap Analytics
Strengths Data Analytics: From Bias to Better Decisions | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Trap Analytics in Data Analytics: From Bias to Better Decisions Harvard Business Review case study are -
Organizational Resilience of Trap Analytics
– The covid-19 pandemic has put organizational resilience at the centre of everthing that Trap Analytics does. Organizational resilience comprises - Financial Resilience, Operational Resilience, Technological Resilience, Organizational Resilience, Business Model Resilience, and Reputation Resilience.
Training and development
– Trap Analytics has one of the best training and development program in the industry. The effectiveness of the training programs can be measured in Data Analytics: From Bias to Better Decisions 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.
Strong track record of project management
– Trap Analytics is known for sticking to its project targets. This enables the firm to manage – time, project costs, and have sustainable margins on the projects.
Highly skilled collaborators
– Trap Analytics 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 Data Analytics: From Bias to Better Decisions HBR case study have helped the firm to develop new products and bring them quickly to the marketplace.
Superior customer experience
– The customer experience strategy of Trap Analytics in the segment is based on four key concepts – personalization, simplification of complex needs, prompt response, and continuous engagement.
Digital Transformation in Strategy & Execution segment
- digital transformation varies from industry to industry. For Trap Analytics digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Trap Analytics 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 Strategy & Execution industry
– Data Analytics: From Bias to Better Decisions firm has clearly differentiated products in the market place. This has enabled Trap Analytics to fetch slight price premium compare to the competitors in the Strategy & Execution industry. The sustainable margins have also helped Trap Analytics to invest into research and development (R&D) and innovation.
Successful track record of launching new products
– Trap Analytics has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Trap Analytics 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.
Low bargaining power of suppliers
– Suppliers of Trap Analytics in the sector have low bargaining power. Data Analytics: From Bias to Better Decisions has further diversified its suppliers portfolio by building a robust supply chain across various countries. This helps Trap Analytics to manage not only supply disruptions but also source products at highly competitive prices.
Ability to lead change in Strategy & Execution field
– Trap Analytics is one of the leading players in its industry. Over the years it has not only transformed the business landscape in its segment but also across the whole industry. The ability to lead change has enabled Trap Analytics in – penetrating new markets, reaching out to new customers, and providing different value propositions to different customers in the international markets.
Cross disciplinary teams
– Horizontal connected teams at the Trap Analytics 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.
High switching costs
– The high switching costs that Trap Analytics 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 Data Analytics: From Bias to Better Decisions | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Data Analytics: From Bias to Better Decisions are -
Need for greater diversity
– Trap Analytics 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.
High cash cycle compare to competitors
Trap Analytics 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.
Compensation and incentives
– The revenue per employee as mentioned in the HBR case study Data Analytics: From Bias to Better Decisions, is just above the industry average. Trap Analytics 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 dependence on star products
– The top 2 products and services of the firm as mentioned in the Data Analytics: From Bias to Better Decisions 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 Trap Analytics has relatively successful track record of launching new products.
Lack of clear differentiation of Trap Analytics products
– To increase the profitability and margins on the products, Trap Analytics needs to provide more differentiated products than what it is currently offering in the marketplace.
Skills based hiring
– The stress on hiring functional specialists at Trap Analytics has created an environment where the organization is dominated by functional specialists rather than management generalist. This has resulted into product oriented approach rather than marketing oriented approach or consumers oriented approach.
Low market penetration in new markets
– Outside its home market of Trap Analytics, firm in the HBR case study Data Analytics: From Bias to Better Decisions needs to spend more promotional, marketing, and advertising efforts to penetrate international markets.
High operating costs
– Compare to the competitors, firm in the HBR case study Data Analytics: From Bias to Better Decisions 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 Trap Analytics 's lucrative customers.
Workers concerns about automation
– As automation is fast increasing in the segment, Trap Analytics 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.
Slow to harness new channels of communication
– Even though competitors are using new communication channels such as Instagram, Tiktok, and Snap, Trap Analytics is slow explore the new channels of communication. These new channels of communication mentioned in marketing section of case study Data Analytics: From Bias to Better Decisions can help to provide better information regarding products and services. It can also build an online community to further reach out to potential customers.
Slow to strategic competitive environment developments
– As Data Analytics: From Bias to Better Decisions HBR case study mentions - Trap Analytics 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.
Opportunities Data Analytics: From Bias to Better Decisions | 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 Data Analytics: From Bias to Better Decisions are -
Learning at scale
– Online learning technologies has now opened space for Trap Analytics 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.
Harnessing reconfiguration of the global supply chains
– As the trade war between US and China heats up in the coming years, Trap Analytics 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, Data Analytics: From Bias to Better Decisions, to buy more products closer to the markets, and it can leverage its size and influence to get better deal from the local markets.
Leveraging digital technologies
– Trap Analytics 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.
Developing new processes and practices
– Trap Analytics can develop new processes and procedures in Strategy & Execution 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.
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 Trap Analytics 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.
Creating value in data economy
– The success of analytics program of Trap Analytics has opened avenues for new revenue streams for the organization in the industry. This can help Trap Analytics to build a more holistic ecosystem as suggested in the Data Analytics: From Bias to Better Decisions case study. Trap Analytics can build new products and services such as - data insight services, data privacy related products, data based consulting services, etc.
Finding new ways to collaborate
– Covid-19 has not only transformed business models of companies in Strategy & Execution industry, but it has also influenced the consumer preferences. Trap Analytics can tie-up with other value chain partners to explore new opportunities regarding meeting customer demands and building a rewarding and engaging relationship.
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 Trap Analytics in the consumer business. Now Trap Analytics can target international markets with far fewer capital restrictions requirements than the existing system.
Reforming the budgeting process
- By establishing new metrics that will be used to evaluate both existing and potential projects Trap Analytics 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, Trap Analytics is facing challenges because of the dominance of functional experts in the organization. Data Analytics: From Bias to Better Decisions 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.
Better consumer reach
– The expansion of the 5G network will help Trap Analytics to increase its market reach. Trap Analytics 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.
Lowering marketing communication costs
– 5G expansion will open new opportunities for Trap Analytics in the field of marketing communication. It will bring down the cost of doing business, provide technology platform to build new products in the Strategy & Execution segment, and it will provide faster access to the consumers.
Low interest rates
– Even though inflation is raising its head in most developed economies, Trap Analytics 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.
Threats Data Analytics: From Bias to Better Decisions External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats mentioned in the HBR case study Data Analytics: From Bias to Better Decisions are -
Learning curve for new practices
– As the technology based on artificial intelligence and machine learning platform is getting complex, as highlighted in case study Data Analytics: From Bias to Better Decisions, Trap Analytics may face longer learning curve for training and development of existing employees. This can open space for more nimble competitors in the field of Strategy & Execution .
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 Trap Analytics.
Regulatory challenges
– Trap Analytics 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 Strategy & Execution industry regulations.
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 Trap Analytics business can come under increasing regulations regarding data privacy, data security, etc.
Consumer confidence and its impact on Trap Analytics 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.
Technology acceleration in Forth Industrial Revolution
– Trap Analytics has witnessed rapid integration of technology during Covid-19 in the Strategy & Execution industry. As one of the leading players in the industry, Trap Analytics needs to keep up with the evolution of technology in the Strategy & Execution 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.
Environmental challenges
– Trap Analytics 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. Trap Analytics can take advantage of this fund but it will also bring new competitors in the Strategy & Execution industry.
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. Trap Analytics needs to understand the core reasons impacting the Strategy & Execution industry. This will help it in building a better workplace.
Easy access to finance
– Easy access to finance in Strategy & Execution field will also reduce the barriers to entry in the industry, thus putting downward pressure on the prices because of increasing competition. Trap Analytics can utilize it by borrowing at lower rates and invest it into research and development, capital expenditure to fortify its core competitive advantage.
Barriers of entry lowering
– As technology is more democratized, the barriers to entry in the industry are lowering. It can presents Trap Analytics with greater competitive threats in the near to medium future. Secondly it will also put downward pressure on pricing throughout the sector.
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. Trap Analytics 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.
High dependence on third party suppliers
– Trap Analytics 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.
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.
Weighted SWOT Analysis of Data Analytics: From Bias to Better Decisions 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 Data Analytics: From Bias to Better Decisions 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 Data Analytics: From Bias to Better Decisions 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 Data Analytics: From Bias to Better Decisions 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 Data Analytics: From Bias to Better Decisions 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 Trap Analytics needs to make to build a sustainable competitive advantage.
