How to Use Big Data to Drive Your Supply Chain SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
Technology & Operations
Strategy / MBA Resources
Case Study SWOT Analysis Solution
Case Study Description of How to Use Big Data to Drive Your Supply Chain
Big data analytics has become an imperative for business leaders across every industry sector. Analytics applications that can deliver a competitive advantage appear all along the supply chain decision spectrum-from targeted location-based marketing to optimizing supply chain inventories to enabling supplier risk assessment. While many companies have used it to extract new insights and create new forms of value, other companies have yet to leverage big data to transform their supply chain operations. This article examines how leading companies use big data analytics to drive their supply chains and offers a framework for implementation based on lessons learned.
Swot Analysis of "How to Use Big Data to Drive Your Supply Chain" written by Nada Sanders includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Supply Analytics facing as an external strategic factors. Some of the topics covered in How to Use Big Data to Drive Your Supply Chain case study are - Strategic Management Strategies, Decision making, Supply chain, Technology and Technology & Operations.
Some of the macro environment factors that can be used to understand the How to Use Big Data to Drive Your Supply Chain casestudy better are - – increasing inequality as vast percentage of new income is going to the top 1%, there is increasing trade war between United States & China, geopolitical disruptions, banking and financial system is disrupted by Bitcoin and other crypto currencies, increasing household debt because of falling income levels, increasing commodity prices, technology disruption,
customer relationship management is fast transforming because of increasing concerns over data privacy, there is backlash against globalization, etc
Introduction to SWOT Analysis of How to Use Big Data to Drive Your Supply Chain
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in How to Use Big Data to Drive Your Supply Chain case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Supply Analytics, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Supply 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 How to Use Big Data to Drive Your Supply Chain can be done for the following purposes –
1. Strategic planning using facts provided in How to Use Big Data to Drive Your Supply Chain case study
2. Improving business portfolio management of Supply Analytics
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 Supply Analytics
Strengths How to Use Big Data to Drive Your Supply Chain | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Supply Analytics in How to Use Big Data to Drive Your Supply Chain Harvard Business Review case study are -
Ability to recruit top talent
– Supply Analytics is one of the leading recruiters in the industry. Managers in the How to Use Big Data to Drive Your Supply Chain 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 switching costs
– The high switching costs that Supply 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.
Diverse revenue streams
– Supply Analytics is present in almost all the verticals within the industry. This has provided firm in How to Use Big Data to Drive Your Supply Chain case study a diverse revenue stream that has helped it to survive disruptions such as global pandemic in Covid-19, financial disruption of 2008, and supply chain disruption of 2021.
Digital Transformation in Technology & Operations segment
- digital transformation varies from industry to industry. For Supply Analytics digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Supply 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.
Innovation driven organization
– Supply Analytics is one of the most innovative firm in sector. Manager in How to Use Big Data to Drive Your Supply Chain Harvard Business Review case study can use Clayton Christensen Disruptive Innovation strategies to further increase the scale of innovtions in the organization.
Training and development
– Supply Analytics has one of the best training and development program in the industry. The effectiveness of the training programs can be measured in How to Use Big Data to Drive Your Supply Chain 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.
Operational resilience
– The operational resilience strategy in the How to Use Big Data to Drive Your Supply Chain 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.
Sustainable margins compare to other players in Technology & Operations industry
– How to Use Big Data to Drive Your Supply Chain firm has clearly differentiated products in the market place. This has enabled Supply Analytics to fetch slight price premium compare to the competitors in the Technology & Operations industry. The sustainable margins have also helped Supply Analytics to invest into research and development (R&D) and innovation.
Strong track record of project management
– Supply 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.
Analytics focus
– Supply Analytics 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 Nada Sanders 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.
Highly skilled collaborators
– Supply 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 How to Use Big Data to Drive Your Supply Chain HBR case study have helped the firm to develop new products and bring them quickly to the marketplace.
High brand equity
– Supply Analytics has strong brand awareness and brand recognition among both - the exiting customers and potential new customers. Strong brand equity has enabled Supply Analytics to keep acquiring new customers and building profitable relationship with both the new and loyal customers.
Weaknesses How to Use Big Data to Drive Your Supply Chain | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of How to Use Big Data to Drive Your Supply Chain are -
Interest costs
– Compare to the competition, Supply Analytics 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.
Aligning sales with marketing
– It come across in the case study How to Use Big Data to Drive Your Supply Chain 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 How to Use Big Data to Drive Your Supply Chain can leverage the sales team experience to cultivate customer relationships as Supply Analytics is planning to shift buying processes online.
Capital Spending Reduction
– Even during the low interest decade, Supply Analytics 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 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 Supply Analytics supply chain. Even after few cautionary changes mentioned in the HBR case study - How to Use Big Data to Drive Your Supply Chain, it is still heavily dependent upon the existing supply chain. The existing supply chain though brings in cost efficiencies but it has left Supply Analytics vulnerable to further global disruptions in South East Asia.
Lack of clear differentiation of Supply Analytics products
– To increase the profitability and margins on the products, Supply Analytics needs to provide more differentiated products than what it is currently offering in the marketplace.
High operating costs
– Compare to the competitors, firm in the HBR case study How to Use Big Data to Drive Your Supply Chain 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 Supply Analytics 's lucrative customers.
Workers concerns about automation
– As automation is fast increasing in the segment, Supply 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.
Compensation and incentives
– The revenue per employee as mentioned in the HBR case study How to Use Big Data to Drive Your Supply Chain, is just above the industry average. Supply 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.
Slow to harness new channels of communication
– Even though competitors are using new communication channels such as Instagram, Tiktok, and Snap, Supply Analytics is slow explore the new channels of communication. These new channels of communication mentioned in marketing section of case study How to Use Big Data to Drive Your Supply Chain can help to provide better information regarding products and services. It can also build an online community to further reach out to potential customers.
High cash cycle compare to competitors
Supply 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.
Slow decision making process
– As mentioned earlier in the report, Supply Analytics has a very deliberative decision making approach. This approach has resulted in prudent decisions, but it has also resulted in missing opportunities in the industry over the last five years. Supply Analytics even though has strong showing on digital transformation primary two stages, it has struggled to capitalize the power of digital transformation in marketing efforts and new venture efforts.
Opportunities How to Use Big Data to Drive Your Supply Chain | 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 How to Use Big Data to Drive Your Supply Chain are -
Leveraging digital technologies
– Supply 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.
Creating value in data economy
– The success of analytics program of Supply Analytics has opened avenues for new revenue streams for the organization in the industry. This can help Supply Analytics to build a more holistic ecosystem as suggested in the How to Use Big Data to Drive Your Supply Chain case study. Supply Analytics can build new products and services such as - data insight services, data privacy related products, data based consulting services, etc.
Buying journey improvements
– Supply Analytics can improve the customer journey of consumers in the industry by using analytics and artificial intelligence. How to Use Big Data to Drive Your Supply Chain 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.
Manufacturing automation
– Supply Analytics can use the latest technology developments to improve its manufacturing and designing process in Technology & Operations segment. It can use CAD and 3D printing to build a quick prototype and pilot testing products. It can leverage automation using machine learning and artificial intelligence to do faster production at lowers costs, and it can leverage the growth in satellite and tracking technologies to improve inventory management, transportation, and shipping.
Changes in consumer behavior post Covid-19
– Consumer behavior has changed in the Technology & Operations industry because of Covid-19 restrictions. Some of this behavior will stay once things get back to normal. Supply Analytics can take advantage of these changes in consumer behavior to build a far more efficient business model. For example consumer regular ordering of products can reduce both last mile delivery costs and market penetration costs. Supply Analytics can further use this consumer data to build better customer loyalty, provide better products and service collection, and improve the value proposition in inflationary times.
Redefining models of collaboration and team work
– As explained in the weaknesses section, Supply Analytics is facing challenges because of the dominance of functional experts in the organization. How to Use Big Data to Drive Your Supply Chain 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.
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 Supply Analytics in the consumer business. Now Supply Analytics can target international markets with far fewer capital restrictions requirements than the existing system.
Remote work and new talent hiring opportunities
– The widespread usage of remote working technologies during Covid-19 has opened opportunities for Supply Analytics 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 Supply Analytics to hire the very best people irrespective of their geographical location.
Learning at scale
– Online learning technologies has now opened space for Supply 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.
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 Supply 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.
Using analytics as competitive advantage
– Supply Analytics 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 How to Use Big Data to Drive Your Supply Chain - to build a competitive advantage using analytics. The analytics driven competitive advantage can help Supply Analytics to build faster Go To Market strategies, better consumer insights, developing relevant product features, and building a highly efficient supply chain.
Lowering marketing communication costs
– 5G expansion will open new opportunities for Supply 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 Technology & Operations segment, and it will provide faster access to the consumers.
Low interest rates
– Even though inflation is raising its head in most developed economies, Supply 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 How to Use Big Data to Drive Your Supply Chain External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats mentioned in the HBR case study How to Use Big Data to Drive Your Supply Chain are -
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.
Trade war between China and United States
– The trade war between two of the biggest economies can hugely impact the opportunities for Supply Analytics 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.
Environmental challenges
– Supply 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. Supply Analytics can take advantage of this fund but it will also bring new competitors in the Technology & Operations industry.
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 Supply Analytics business can come under increasing regulations regarding data privacy, data security, etc.
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 Supply Analytics in the Technology & Operations sector and impact the bottomline of the organization.
High dependence on third party suppliers
– Supply 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.
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. Supply Analytics can utilize it by borrowing at lower rates and invest it into research and development, capital expenditure to fortify its core competitive advantage.
Stagnating economy with rate increase
– Supply Analytics 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.
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. Supply 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.
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.
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. Supply Analytics needs to understand the core reasons impacting the Technology & Operations industry. This will help it in building a better workplace.
Technology acceleration in Forth Industrial Revolution
– Supply Analytics has witnessed rapid integration of technology during Covid-19 in the Technology & Operations industry. As one of the leading players in the industry, Supply Analytics 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.
Regulatory challenges
– Supply 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 Technology & Operations industry regulations.
Weighted SWOT Analysis of How to Use Big Data to Drive Your Supply Chain 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 How to Use Big Data to Drive Your Supply Chain 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 How to Use Big Data to Drive Your Supply Chain 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 How to Use Big Data to Drive Your Supply Chain 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 How to Use Big Data to Drive Your Supply Chain 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 Supply Analytics needs to make to build a sustainable competitive advantage.