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, increasing energy prices, banking and financial system is disrupted by Bitcoin and other crypto currencies, central banks are concerned over increasing inflation, talent flight as more people leaving formal jobs, increasing transportation and logistics costs, technology disruption,
supply chains are disrupted by pandemic , wage bills are increasing, 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 -
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.
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.
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.
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.
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 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.
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.
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.
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.
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.
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.
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.
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 -
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.
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.
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.
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.
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.
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.
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.
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.
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 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 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.
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 -
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.
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.
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.
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.
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.
Developing new processes and practices
– Supply Analytics can develop new processes and procedures in Technology & Operations industry using technology such as automation using artificial intelligence, real time transportation and products tracking, 3D modeling for concept development and new products pilot testing etc.
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.
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.
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.
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.
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.
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 -
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 .
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.
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.