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 - – technology disruption, increasing inequality as vast percentage of new income is going to the top 1%, digital marketing is dominated by two big players Facebook and Google, increasing government debt because of Covid-19 spendings, increasing household debt because of falling income levels, challanges to central banks by blockchain based private currencies, supply chains are disrupted by pandemic ,
geopolitical disruptions, banking and financial system is disrupted by Bitcoin and other crypto currencies, 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 -
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.
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.
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.
Cross disciplinary teams
– Horizontal connected teams at the Supply 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.
Superior customer experience
– The customer experience strategy of Supply Analytics in the segment is based on four key concepts – personalization, simplification of complex needs, prompt response, and continuous engagement.
Successful track record of launching new products
– Supply Analytics has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Supply 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.
Ability to lead change in Technology & Operations field
– Supply 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 Supply Analytics in – penetrating new markets, reaching out to new customers, and providing different value propositions to different customers in the international markets.
Organizational Resilience of Supply Analytics
– The covid-19 pandemic has put organizational resilience at the centre of everthing that Supply Analytics does. Organizational resilience comprises - Financial Resilience, Operational Resilience, Technological Resilience, Organizational Resilience, Business Model Resilience, and Reputation Resilience.
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.
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.
Learning organization
- Supply Analytics 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 Supply Analytics is open place that encourages instructiveness, ideation, open minded discussions, and creativity. Employees and leaders in How to Use Big Data to Drive Your Supply Chain Harvard Business Review case study emphasize – knowledge, initiative, and innovation.
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.
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 -
Need for greater diversity
– Supply 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.
Products dominated business model
– Even though Supply Analytics 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 - How to Use Big Data to Drive Your Supply Chain should strive to include more intangible value offerings along with its core products and services.
Employees’ incomplete understanding of strategy
– From the instances in the HBR case study How to Use Big Data to Drive Your Supply Chain, it seems that the employees of Supply Analytics 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.
Ability to respond to the competition
– As the decision making is very deliberative, highlighted in the case study How to Use Big Data to Drive Your Supply Chain, in the dynamic environment Supply Analytics has struggled to respond to the nimble upstart competition. Supply Analytics has reasonably good record with similar level competitors but it has struggled with new entrants taking away niches of its business.
High bargaining power of channel partners
– Because of the regulatory requirements, Nada Sanders suggests that, Supply Analytics is facing high bargaining power of the channel partners. So far it has not able to streamline the operations to reduce the bargaining power of the value chain partners in the industry.
Low market penetration in new markets
– Outside its home market of Supply Analytics, firm in the HBR case study How to Use Big Data to Drive Your Supply Chain needs to spend more promotional, marketing, and advertising efforts to penetrate international markets.
High dependence on star products
– The top 2 products and services of the firm as mentioned in the How to Use Big Data to Drive Your Supply Chain 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 Supply Analytics has relatively successful track record of launching new products.
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.
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.
No frontier risks strategy
– After analyzing the HBR case study How to Use Big Data to Drive Your Supply Chain, it seems that company is thinking about the frontier risks that can impact Technology & Operations 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 Supply Analytics is dominated by functional specialists. It is not different from other players in the Technology & Operations segment. Supply Analytics needs to de-silo the office environment to harness the true potential of its workforce. Secondly the de-silo will also help Supply Analytics to focus more on services rather than just following the product oriented approach.
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 -
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. Supply Analytics can explore opportunities that can attract volunteers and are consistent with its mission and vision.
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.
Reforming the budgeting process
- By establishing new metrics that will be used to evaluate both existing and potential projects Supply Analytics can not only reduce the costs of the project but also help it in integrating the projects with other processes within the organization.
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.
Harnessing reconfiguration of the global supply chains
– As the trade war between US and China heats up in the coming years, Supply 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, How to Use Big Data to Drive Your Supply Chain, to buy more products closer to the markets, and it can leverage its size and influence to get better deal from the local markets.
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.
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.
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.
Better consumer reach
– The expansion of the 5G network will help Supply Analytics to increase its market reach. Supply 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 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.
Increase in government spending
– As the United States and other governments are increasing social spending and infrastructure spending to build economies post Covid-19, Supply Analytics can use these opportunities to build new business models that can help the communities that Supply Analytics operates in. Secondly it can use opportunities from government spending in Technology & Operations sector.
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.
Building a culture of innovation
– managers at Supply Analytics 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 Technology & Operations segment.
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 -
Shortening product life cycle
– it is one of the major threat that Supply Analytics is facing in Technology & Operations sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, etc.
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.
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.
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.
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.
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.
Barriers of entry lowering
– As technology is more democratized, the barriers to entry in the industry are lowering. It can presents Supply Analytics with greater competitive threats in the near to medium future. Secondly it will also put downward pressure on pricing throughout the sector.
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.
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.
Learning curve for new practices
– As the technology based on artificial intelligence and machine learning platform is getting complex, as highlighted in case study How to Use Big Data to Drive Your Supply Chain, Supply 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 Technology & Operations .
Increasing wage structure of Supply Analytics
– 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 Supply Analytics.
Consumer confidence and its impact on Supply 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.
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.