In this article, I describe the application of advanced analytics techniques to supply chain management. The applications are categorized in terms of descriptive, predictive, and prescriptive analytics and along the supply chain operations reference (SCOR) model domains plan, source, make, deliver, and return. Descriptive analytics applications center on the use of data from global positioning systems (GPSs), radio frequency identification (RFID) chips, and data-visualization tools to provide managers with real-time information regarding location and quantities of goods in the supply chain. Predictive analytics centers on demand forecasting at strategic, tactical, and operational levels, all of which drive the planning process in supply chains in terms of network design, capacity planning, production planning, and inventory management. Finally, prescriptive analytics focuses on the use of mathematical optimization and simulation techniques to provide decision-support tools built upon descriptive and predictive analytics models.
Swot Analysis of "Supply Chain Analytics" written by Gilvan C. Souza includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Analytics Descriptive facing as an external strategic factors. Some of the topics covered in Supply Chain Analytics case study are - Strategic Management Strategies, Forecasting, Supply chain and Leadership & Managing People.
Some of the macro environment factors that can be used to understand the Supply Chain Analytics casestudy better are - – increasing energy prices, banking and financial system is disrupted by Bitcoin and other crypto currencies, there is backlash against globalization, increasing inequality as vast percentage of new income is going to the top 1%, talent flight as more people leaving formal jobs, wage bills are increasing, there is increasing trade war between United States & China,
increasing government debt because of Covid-19 spendings, central banks are concerned over increasing inflation, etc
Introduction to SWOT Analysis of Supply Chain Analytics
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in Supply Chain Analytics case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Analytics Descriptive, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Analytics Descriptive 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 Supply Chain Analytics can be done for the following purposes –
1. Strategic planning using facts provided in Supply Chain Analytics case study
2. Improving business portfolio management of Analytics Descriptive
3. Assessing feasibility of the new initiative in Leadership & Managing People field.
4. Making a Leadership & Managing People topic specific business decision
5. Set goals for the organization
6. Organizational restructuring of Analytics Descriptive
Strengths Supply Chain Analytics | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Analytics Descriptive in Supply Chain Analytics Harvard Business Review case study are -
Training and development
– Analytics Descriptive has one of the best training and development program in the industry. The effectiveness of the training programs can be measured in Supply Chain Analytics 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.
Successful track record of launching new products
– Analytics Descriptive has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Analytics Descriptive 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.
Strong track record of project management
– Analytics Descriptive is known for sticking to its project targets. This enables the firm to manage – time, project costs, and have sustainable margins on the projects.
Effective Research and Development (R&D)
– Analytics Descriptive 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 Supply Chain Analytics - staying ahead in the industry in terms of – new product launches, superior customer experience, highly competitive pricing strategies, and great returns to the shareholders.
Cross disciplinary teams
– Horizontal connected teams at the Analytics Descriptive 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.
Organizational Resilience of Analytics Descriptive
– The covid-19 pandemic has put organizational resilience at the centre of everthing that Analytics Descriptive does. Organizational resilience comprises - Financial Resilience, Operational Resilience, Technological Resilience, Organizational Resilience, Business Model Resilience, and Reputation Resilience.
Low bargaining power of suppliers
– Suppliers of Analytics Descriptive in the sector have low bargaining power. Supply Chain Analytics has further diversified its suppliers portfolio by building a robust supply chain across various countries. This helps Analytics Descriptive to manage not only supply disruptions but also source products at highly competitive prices.
Operational resilience
– The operational resilience strategy in the Supply Chain Analytics 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.
Learning organization
- Analytics Descriptive 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 Analytics Descriptive is open place that encourages instructiveness, ideation, open minded discussions, and creativity. Employees and leaders in Supply Chain Analytics Harvard Business Review case study emphasize – knowledge, initiative, and innovation.
Innovation driven organization
– Analytics Descriptive is one of the most innovative firm in sector. Manager in Supply Chain Analytics Harvard Business Review case study can use Clayton Christensen Disruptive Innovation strategies to further increase the scale of innovtions in the organization.
Ability to recruit top talent
– Analytics Descriptive is one of the leading recruiters in the industry. Managers in the Supply Chain Analytics are in a position to attract the best talent available. The firm has a robust talent identification program that helps in identifying the brightest.
Highly skilled collaborators
– Analytics Descriptive 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 Supply Chain Analytics HBR case study have helped the firm to develop new products and bring them quickly to the marketplace.
Weaknesses Supply Chain Analytics | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Supply Chain Analytics are -
Skills based hiring
– The stress on hiring functional specialists at Analytics Descriptive 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.
Need for greater diversity
– Analytics Descriptive 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.
Increasing silos among functional specialists
– The organizational structure of Analytics Descriptive is dominated by functional specialists. It is not different from other players in the Leadership & Managing People segment. Analytics Descriptive needs to de-silo the office environment to harness the true potential of its workforce. Secondly the de-silo will also help Analytics Descriptive to focus more on services rather than just following the product oriented approach.
Interest costs
– Compare to the competition, Analytics Descriptive 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.
Low market penetration in new markets
– Outside its home market of Analytics Descriptive, firm in the HBR case study Supply Chain Analytics needs to spend more promotional, marketing, and advertising efforts to penetrate international markets.
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 Analytics Descriptive supply chain. Even after few cautionary changes mentioned in the HBR case study - Supply Chain Analytics, it is still heavily dependent upon the existing supply chain. The existing supply chain though brings in cost efficiencies but it has left Analytics Descriptive vulnerable to further global disruptions in South East Asia.
Slow to harness new channels of communication
– Even though competitors are using new communication channels such as Instagram, Tiktok, and Snap, Analytics Descriptive is slow explore the new channels of communication. These new channels of communication mentioned in marketing section of case study Supply Chain Analytics can help to provide better information regarding products and services. It can also build an online community to further reach out to potential customers.
Products dominated business model
– Even though Analytics Descriptive 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 - Supply Chain Analytics should strive to include more intangible value offerings along with its core products and services.
No frontier risks strategy
– After analyzing the HBR case study Supply Chain Analytics, it seems that company is thinking about the frontier risks that can impact Leadership & Managing People 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.
Slow to strategic competitive environment developments
– As Supply Chain Analytics HBR case study mentions - Analytics Descriptive takes time to assess the upcoming competitions. This has led to missing out on atleast 2-3 big opportunities in the industry in last five years.
High dependence on star products
– The top 2 products and services of the firm as mentioned in the Supply Chain Analytics 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 Analytics Descriptive has relatively successful track record of launching new products.
Opportunities Supply Chain Analytics | 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 Supply Chain Analytics 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. Analytics Descriptive can explore opportunities that can attract volunteers and are consistent with its mission and vision.
Leveraging digital technologies
– Analytics Descriptive 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.
Building a culture of innovation
– managers at Analytics Descriptive 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 Leadership & Managing People segment.
Use of Bitcoin and other crypto currencies for transactions
– The popularity of Bitcoin and other crypto currencies as asset class and medium of transaction has opened new opportunities for Analytics Descriptive in the consumer business. Now Analytics Descriptive can target international markets with far fewer capital restrictions requirements than the existing system.
Learning at scale
– Online learning technologies has now opened space for Analytics Descriptive 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.
Creating value in data economy
– The success of analytics program of Analytics Descriptive has opened avenues for new revenue streams for the organization in the industry. This can help Analytics Descriptive to build a more holistic ecosystem as suggested in the Supply Chain Analytics case study. Analytics Descriptive can build new products and services such as - data insight services, data privacy related products, data based consulting services, etc.
Remote work and new talent hiring opportunities
– The widespread usage of remote working technologies during Covid-19 has opened opportunities for Analytics Descriptive 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 Analytics Descriptive to hire the very best people irrespective of their geographical location.
Loyalty marketing
– Analytics Descriptive 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.
Reforming the budgeting process
- By establishing new metrics that will be used to evaluate both existing and potential projects Analytics Descriptive can not only reduce the costs of the project but also help it in integrating the projects with other processes within the organization.
Increase in government spending
– As the United States and other governments are increasing social spending and infrastructure spending to build economies post Covid-19, Analytics Descriptive can use these opportunities to build new business models that can help the communities that Analytics Descriptive operates in. Secondly it can use opportunities from government spending in Leadership & Managing People sector.
Finding new ways to collaborate
– Covid-19 has not only transformed business models of companies in Leadership & Managing People industry, but it has also influenced the consumer preferences. Analytics Descriptive can tie-up with other value chain partners to explore new opportunities regarding meeting customer demands and building a rewarding and engaging relationship.
Manufacturing automation
– Analytics Descriptive can use the latest technology developments to improve its manufacturing and designing process in Leadership & Managing People 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.
Using analytics as competitive advantage
– Analytics Descriptive 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 Supply Chain Analytics - to build a competitive advantage using analytics. The analytics driven competitive advantage can help Analytics Descriptive to build faster Go To Market strategies, better consumer insights, developing relevant product features, and building a highly efficient supply chain.
Threats Supply Chain Analytics External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats mentioned in the HBR case study Supply Chain Analytics are -
Increasing international competition and downward pressure on margins
– Apart from technology driven competitive advantage dilution, Analytics Descriptive 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 Supply Chain Analytics .
Regulatory challenges
– Analytics Descriptive 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 Leadership & Managing People industry regulations.
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 Analytics Descriptive.
Technology acceleration in Forth Industrial Revolution
– Analytics Descriptive has witnessed rapid integration of technology during Covid-19 in the Leadership & Managing People industry. As one of the leading players in the industry, Analytics Descriptive needs to keep up with the evolution of technology in the Leadership & Managing People 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.
Shortening product life cycle
– it is one of the major threat that Analytics Descriptive is facing in Leadership & Managing People sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, etc.
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. Analytics Descriptive 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.
Easy access to finance
– Easy access to finance in Leadership & Managing People field will also reduce the barriers to entry in the industry, thus putting downward pressure on the prices because of increasing competition. Analytics Descriptive can utilize it by borrowing at lower rates and invest it into research and development, capital expenditure to fortify its core competitive advantage.
Learning curve for new practices
– As the technology based on artificial intelligence and machine learning platform is getting complex, as highlighted in case study Supply Chain Analytics, Analytics Descriptive may face longer learning curve for training and development of existing employees. This can open space for more nimble competitors in the field of Leadership & Managing People .
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 Analytics Descriptive in the Leadership & Managing People sector and impact the bottomline of the organization.
Increasing wage structure of Analytics Descriptive
– 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 Analytics Descriptive.
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.
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.
Stagnating economy with rate increase
– Analytics Descriptive 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.
Weighted SWOT Analysis of Supply Chain Analytics 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 Supply Chain Analytics 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 Supply Chain Analytics 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 Supply Chain Analytics 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 Supply Chain Analytics 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 Analytics Descriptive needs to make to build a sustainable competitive advantage.
