Data Mining: On the Trail to Marketing Gold SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
Sales & Marketing
Strategy / MBA Resources
Case Study SWOT Analysis Solution
Case Study Description of Data Mining: On the Trail to Marketing Gold
What is data mining, and how does it differ from traditional statistical modeling? Along with finding the answers here, managers can take a look at important recent developments in data mining, examine some of its marketing-related applications, and learn how to establish and maintain a data mining system. Armed with this information, they can then determine their firm's level of commitment to the process. Companies that do not want to commit the financial and personnel resources to data mining can still secure many of its benefits through outsourcing.
Authors :: Shawn Thelen, Sandra Mottner, Barry Berman
Swot Analysis of "Data Mining: On the Trail to Marketing Gold" written by Shawn Thelen, Sandra Mottner, Barry Berman includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Mining Data facing as an external strategic factors. Some of the topics covered in Data Mining: On the Trail to Marketing Gold case study are - Strategic Management Strategies, Data, Operations management and Sales & Marketing.
Some of the macro environment factors that can be used to understand the Data Mining: On the Trail to Marketing Gold casestudy better are - – customer relationship management is fast transforming because of increasing concerns over data privacy, increasing inequality as vast percentage of new income is going to the top 1%, geopolitical disruptions, challanges to central banks by blockchain based private currencies, technology disruption, there is increasing trade war between United States & China, there is backlash against globalization,
banking and financial system is disrupted by Bitcoin and other crypto currencies, talent flight as more people leaving formal jobs, etc
Introduction to SWOT Analysis of Data Mining: On the Trail to Marketing Gold
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in Data Mining: On the Trail to Marketing Gold case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Mining Data, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Mining 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 Data Mining: On the Trail to Marketing Gold can be done for the following purposes –
1. Strategic planning using facts provided in Data Mining: On the Trail to Marketing Gold case study
2. Improving business portfolio management of Mining Data
3. Assessing feasibility of the new initiative in Sales & Marketing field.
4. Making a Sales & Marketing topic specific business decision
5. Set goals for the organization
6. Organizational restructuring of Mining Data
Strengths Data Mining: On the Trail to Marketing Gold | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Mining Data in Data Mining: On the Trail to Marketing Gold Harvard Business Review case study are -
Digital Transformation in Sales & Marketing segment
- digital transformation varies from industry to industry. For Mining Data digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Mining 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.
Strong track record of project management
– Mining Data is known for sticking to its project targets. This enables the firm to manage – time, project costs, and have sustainable margins on the projects.
Operational resilience
– The operational resilience strategy in the Data Mining: On the Trail to Marketing Gold 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.
Superior customer experience
– The customer experience strategy of Mining Data in the segment is based on four key concepts – personalization, simplification of complex needs, prompt response, and continuous engagement.
Ability to recruit top talent
– Mining Data is one of the leading recruiters in the industry. Managers in the Data Mining: On the Trail to Marketing Gold 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
– Mining Data has strong brand awareness and brand recognition among both - the exiting customers and potential new customers. Strong brand equity has enabled Mining Data to keep acquiring new customers and building profitable relationship with both the new and loyal customers.
High switching costs
– The high switching costs that Mining Data 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.
Learning organization
- Mining 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 Mining Data is open place that encourages instructiveness, ideation, open minded discussions, and creativity. Employees and leaders in Data Mining: On the Trail to Marketing Gold Harvard Business Review case study emphasize – knowledge, initiative, and innovation.
Sustainable margins compare to other players in Sales & Marketing industry
– Data Mining: On the Trail to Marketing Gold firm has clearly differentiated products in the market place. This has enabled Mining Data to fetch slight price premium compare to the competitors in the Sales & Marketing industry. The sustainable margins have also helped Mining Data to invest into research and development (R&D) and innovation.
Cross disciplinary teams
– Horizontal connected teams at the Mining Data 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.
Successful track record of launching new products
– Mining Data has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Mining Data 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.
Organizational Resilience of Mining Data
– The covid-19 pandemic has put organizational resilience at the centre of everthing that Mining Data does. Organizational resilience comprises - Financial Resilience, Operational Resilience, Technological Resilience, Organizational Resilience, Business Model Resilience, and Reputation Resilience.
Weaknesses Data Mining: On the Trail to Marketing Gold | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Data Mining: On the Trail to Marketing Gold 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 Mining Data supply chain. Even after few cautionary changes mentioned in the HBR case study - Data Mining: On the Trail to Marketing Gold, it is still heavily dependent upon the existing supply chain. The existing supply chain though brings in cost efficiencies but it has left Mining Data vulnerable to further global disruptions in South East Asia.
Interest costs
– Compare to the competition, Mining Data 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.
High operating costs
– Compare to the competitors, firm in the HBR case study Data Mining: On the Trail to Marketing Gold 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 Mining Data 's lucrative customers.
Slow to strategic competitive environment developments
– As Data Mining: On the Trail to Marketing Gold HBR case study mentions - Mining 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
Mining 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.
Products dominated business model
– Even though Mining 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 - Data Mining: On the Trail to Marketing Gold should strive to include more intangible value offerings along with its core products and services.
Lack of clear differentiation of Mining Data products
– To increase the profitability and margins on the products, Mining Data needs to provide more differentiated products than what it is currently offering in the marketplace.
No frontier risks strategy
– After analyzing the HBR case study Data Mining: On the Trail to Marketing Gold, it seems that company is thinking about the frontier risks that can impact Sales & Marketing 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.
Need for greater diversity
– Mining 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 Data Mining: On the Trail to Marketing Gold 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 Data Mining: On the Trail to Marketing Gold can leverage the sales team experience to cultivate customer relationships as Mining Data is planning to shift buying processes online.
Ability to respond to the competition
– As the decision making is very deliberative, highlighted in the case study Data Mining: On the Trail to Marketing Gold, in the dynamic environment Mining Data has struggled to respond to the nimble upstart competition. Mining Data has reasonably good record with similar level competitors but it has struggled with new entrants taking away niches of its business.
Opportunities Data Mining: On the Trail to Marketing Gold | 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 Mining: On the Trail to Marketing Gold are -
Remote work and new talent hiring opportunities
– The widespread usage of remote working technologies during Covid-19 has opened opportunities for Mining Data to expand its talent hiring zone. According to McKinsey Global Institute, 20% of the high end workforce in fields such as finance, information technology, can continously work from remote local post Covid-19. This presents a really great opportunity for Mining Data to hire the very best people irrespective of their geographical location.
Learning at scale
– Online learning technologies has now opened space for Mining 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.
Building a culture of innovation
– managers at Mining 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 Sales & Marketing segment.
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 Mining Data in the consumer business. Now Mining Data 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 Mining Data 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.
Buying journey improvements
– Mining Data can improve the customer journey of consumers in the industry by using analytics and artificial intelligence. Data Mining: On the Trail to Marketing Gold 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.
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. Mining Data can explore opportunities that can attract volunteers and are consistent with its mission and vision.
Loyalty marketing
– Mining 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.
Using analytics as competitive advantage
– Mining 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 Data Mining: On the Trail to Marketing Gold - to build a competitive advantage using analytics. The analytics driven competitive advantage can help Mining Data to build faster Go To Market strategies, better consumer insights, developing relevant product features, and building a highly efficient supply chain.
Increase in government spending
– As the United States and other governments are increasing social spending and infrastructure spending to build economies post Covid-19, Mining Data can use these opportunities to build new business models that can help the communities that Mining Data operates in. Secondly it can use opportunities from government spending in Sales & Marketing sector.
Reforming the budgeting process
- By establishing new metrics that will be used to evaluate both existing and potential projects Mining Data can not only reduce the costs of the project but also help it in integrating the projects with other processes within the organization.
Manufacturing automation
– Mining Data can use the latest technology developments to improve its manufacturing and designing process in Sales & Marketing 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.
Finding new ways to collaborate
– Covid-19 has not only transformed business models of companies in Sales & Marketing industry, but it has also influenced the consumer preferences. Mining Data can tie-up with other value chain partners to explore new opportunities regarding meeting customer demands and building a rewarding and engaging relationship.
Threats Data Mining: On the Trail to Marketing Gold External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats mentioned in the HBR case study Data Mining: On the Trail to Marketing Gold are -
Shortening product life cycle
– it is one of the major threat that Mining Data is facing in Sales & Marketing sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, etc.
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. Mining Data needs to understand the core reasons impacting the Sales & Marketing industry. This will help it in building a better workplace.
Regulatory challenges
– Mining 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 Sales & Marketing industry regulations.
Increasing wage structure of Mining 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 Mining Data.
Technology acceleration in Forth Industrial Revolution
– Mining Data has witnessed rapid integration of technology during Covid-19 in the Sales & Marketing industry. As one of the leading players in the industry, Mining Data needs to keep up with the evolution of technology in the Sales & Marketing 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
– Mining 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.
Consumer confidence and its impact on Mining 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.
High dependence on third party suppliers
– Mining 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.
Aging population
– As the populations of most advanced economies are aging, it will lead to high social security costs, higher savings among population, and lower demand for goods and services in the economy. The household savings in US, France, UK, Germany, and Japan are growing faster than predicted because of uncertainty caused by pandemic.
Barriers of entry lowering
– As technology is more democratized, the barriers to entry in the industry are lowering. It can presents Mining Data 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 Mining Data in the Sales & Marketing industry. The Sales & Marketing 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.
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. Mining 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.
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 Mining Data business can come under increasing regulations regarding data privacy, data security, etc.
Weighted SWOT Analysis of Data Mining: On the Trail to Marketing Gold 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 Mining: On the Trail to Marketing Gold 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 Mining: On the Trail to Marketing Gold 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 Mining: On the Trail to Marketing Gold 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 Mining: On the Trail to Marketing Gold 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 Mining Data needs to make to build a sustainable competitive advantage.