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 household debt because of falling income levels, supply chains are disrupted by pandemic , geopolitical disruptions, cloud computing is disrupting traditional business models, there is backlash against globalization, technology disruption, talent flight as more people leaving formal jobs,
increasing government debt because of Covid-19 spendings, central banks are concerned over increasing inflation, 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 -
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.
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.
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.
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.
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.
Effective Research and Development (R&D)
– Supply Analytics has innovation driven culture where significant part of the revenues are spent on the research and development activities. This has resulted in, as mentioned in case study How to Use Big Data to Drive Your Supply Chain - staying ahead in the industry in terms of – new product launches, superior customer experience, highly competitive pricing strategies, and great returns to the shareholders.
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.
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 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.
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.
Low bargaining power of suppliers
– Suppliers of Supply Analytics in the sector have low bargaining power. How to Use Big Data to Drive Your Supply Chain has further diversified its suppliers portfolio by building a robust supply chain across various countries. This helps Supply Analytics to manage not only supply disruptions but also source products at highly competitive prices.
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.
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 -
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.
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.
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.
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 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.
Skills based hiring
– The stress on hiring functional specialists at Supply 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.
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.
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.
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.
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.
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.
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 -
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Loyalty marketing
– Supply Analytics 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.
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.
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 -
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.
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.
Increasing international competition and downward pressure on margins
– Apart from technology driven competitive advantage dilution, Supply Analytics can face downward pressure on margins from increasing competition from international players. The international players have stable revenue in their home market and can use those resources to penetrate prominent markets illustrated in HBR case study How to Use Big Data to Drive Your Supply Chain .
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 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.
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 Supply Analytics.
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.
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.
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.
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.
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.
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.
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.