GROW: Using Artificial Intelligence to Screen Human Intelligence SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
Organizational Development
Strategy / MBA Resources
Case Study SWOT Analysis Solution
Case Study Description of GROW: Using Artificial Intelligence to Screen Human Intelligence
Over 10% of all 2017 university graduates in Japan used GROW, an artificial intelligence platform and mobile app developed by Tokyo-based people analytics startup IGS, to recruit for a job. This case puts participants in the shoes of IGS founder and CEO Masahiro Fukuhara, a first-time entrepreneur, as he considers the varied ways the "big data" he is collecting is being used--and whether some uses promised more meaningful (or less potentially misleading) impact than others. After briefly introducing IGS, Fukuhara, and GROW, the case outlines exactly how GROW works, starting with a mobile app to assess competencies and personalities of candidates and ending with artificial intelligence (machine learning) to produce high-quality recommendations to companies about whom they should hire. The case then articulates precisely how three companies--airline ANA (All-Nippon Airways), global conglomerate Mitsubishi Corporation, and advertising/media company Septeni--use GROW in very different ways to manage talent recruiting, screening, hiring, placement, and development. The case asks students to consider two questions: (1) Which of the three company's approach to using people analytics for talent acquisition and development is most appealing (or most concerning)?; and (2) Should Fukuhara turn on the most advanced part of the artificial intelligence engine, allowing GROW not just to provide recommendations to clients about whom they should hire, but also (based on performance and attribute data of previous hires) to overrule clients' specifications (or biases) about the competencies they should be targeting in their ideal hires? Accompanying the case are the (anonymized) data one of these companies used to make their hiring decision, so that students can experience first-hand the opportunities and challenges of using people analytics in hiring. The case also provides an accessible yet thorough explanation of the key aspects of artificial intelligence (supervised, unsupervised, and reinforcement machine learning). The case is well-suited to courses in Managing Human Capital, People Analytics, Talent Development, Organizational Behavior, or General Management.
Authors :: Ethan S. Bernstein, Paul D. McKinnon, Paul Yarabe
Swot Analysis of "GROW: Using Artificial Intelligence to Screen Human Intelligence" written by Ethan S. Bernstein, Paul D. McKinnon, Paul Yarabe includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Intelligence Artificial facing as an external strategic factors. Some of the topics covered in GROW: Using Artificial Intelligence to Screen Human Intelligence case study are - Strategic Management Strategies, Marketing, Organizational culture, Talent management and Organizational Development.
Some of the macro environment factors that can be used to understand the GROW: Using Artificial Intelligence to Screen Human Intelligence casestudy better are - – digital marketing is dominated by two big players Facebook and Google, increasing energy prices, cloud computing is disrupting traditional business models, central banks are concerned over increasing inflation, there is backlash against globalization, increasing transportation and logistics costs, geopolitical disruptions,
increasing inequality as vast percentage of new income is going to the top 1%, customer relationship management is fast transforming because of increasing concerns over data privacy, etc
Introduction to SWOT Analysis of GROW: Using Artificial Intelligence to Screen Human Intelligence
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in GROW: Using Artificial Intelligence to Screen Human Intelligence case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Intelligence Artificial, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Intelligence Artificial 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 GROW: Using Artificial Intelligence to Screen Human Intelligence can be done for the following purposes –
1. Strategic planning using facts provided in GROW: Using Artificial Intelligence to Screen Human Intelligence case study
2. Improving business portfolio management of Intelligence Artificial
3. Assessing feasibility of the new initiative in Organizational Development field.
4. Making a Organizational Development topic specific business decision
5. Set goals for the organization
6. Organizational restructuring of Intelligence Artificial
Strengths GROW: Using Artificial Intelligence to Screen Human Intelligence | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Intelligence Artificial in GROW: Using Artificial Intelligence to Screen Human Intelligence Harvard Business Review case study are -
Training and development
– Intelligence Artificial has one of the best training and development program in the industry. The effectiveness of the training programs can be measured in GROW: Using Artificial Intelligence to Screen Human Intelligence 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.
Digital Transformation in Organizational Development segment
- digital transformation varies from industry to industry. For Intelligence Artificial digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Intelligence Artificial 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.
High switching costs
– The high switching costs that Intelligence Artificial 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.
High brand equity
– Intelligence Artificial has strong brand awareness and brand recognition among both - the exiting customers and potential new customers. Strong brand equity has enabled Intelligence Artificial to keep acquiring new customers and building profitable relationship with both the new and loyal customers.
Ability to lead change in Organizational Development field
– Intelligence Artificial 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 Intelligence Artificial in – penetrating new markets, reaching out to new customers, and providing different value propositions to different customers in the international markets.
Effective Research and Development (R&D)
– Intelligence Artificial 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 GROW: Using Artificial Intelligence to Screen Human Intelligence - staying ahead in the industry in terms of – new product launches, superior customer experience, highly competitive pricing strategies, and great returns to the shareholders.
Low bargaining power of suppliers
– Suppliers of Intelligence Artificial in the sector have low bargaining power. GROW: Using Artificial Intelligence to Screen Human Intelligence has further diversified its suppliers portfolio by building a robust supply chain across various countries. This helps Intelligence Artificial to manage not only supply disruptions but also source products at highly competitive prices.
Strong track record of project management
– Intelligence Artificial is known for sticking to its project targets. This enables the firm to manage – time, project costs, and have sustainable margins on the projects.
Analytics focus
– Intelligence Artificial 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 Ethan S. Bernstein, Paul D. McKinnon, Paul Yarabe 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.
Organizational Resilience of Intelligence Artificial
– The covid-19 pandemic has put organizational resilience at the centre of everthing that Intelligence Artificial does. Organizational resilience comprises - Financial Resilience, Operational Resilience, Technological Resilience, Organizational Resilience, Business Model Resilience, and Reputation Resilience.
Operational resilience
– The operational resilience strategy in the GROW: Using Artificial Intelligence to Screen Human Intelligence 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.
Superior customer experience
– The customer experience strategy of Intelligence Artificial in the segment is based on four key concepts – personalization, simplification of complex needs, prompt response, and continuous engagement.
Weaknesses GROW: Using Artificial Intelligence to Screen Human Intelligence | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of GROW: Using Artificial Intelligence to Screen Human Intelligence are -
Skills based hiring
– The stress on hiring functional specialists at Intelligence Artificial 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.
Compensation and incentives
– The revenue per employee as mentioned in the HBR case study GROW: Using Artificial Intelligence to Screen Human Intelligence, is just above the industry average. Intelligence Artificial 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.
Low market penetration in new markets
– Outside its home market of Intelligence Artificial, firm in the HBR case study GROW: Using Artificial Intelligence to Screen Human Intelligence needs to spend more promotional, marketing, and advertising efforts to penetrate international markets.
Ability to respond to the competition
– As the decision making is very deliberative, highlighted in the case study GROW: Using Artificial Intelligence to Screen Human Intelligence, in the dynamic environment Intelligence Artificial has struggled to respond to the nimble upstart competition. Intelligence Artificial has reasonably good record with similar level competitors but it has struggled with new entrants taking away niches of its business.
Aligning sales with marketing
– It come across in the case study GROW: Using Artificial Intelligence to Screen Human Intelligence 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 GROW: Using Artificial Intelligence to Screen Human Intelligence can leverage the sales team experience to cultivate customer relationships as Intelligence Artificial is planning to shift buying processes online.
Products dominated business model
– Even though Intelligence Artificial 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 - GROW: Using Artificial Intelligence to Screen Human Intelligence should strive to include more intangible value offerings along with its core products and services.
Capital Spending Reduction
– Even during the low interest decade, Intelligence Artificial 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 bargaining power of channel partners
– Because of the regulatory requirements, Ethan S. Bernstein, Paul D. McKinnon, Paul Yarabe suggests that, Intelligence Artificial 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.
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 Intelligence Artificial supply chain. Even after few cautionary changes mentioned in the HBR case study - GROW: Using Artificial Intelligence to Screen Human Intelligence, it is still heavily dependent upon the existing supply chain. The existing supply chain though brings in cost efficiencies but it has left Intelligence Artificial vulnerable to further global disruptions in South East Asia.
High operating costs
– Compare to the competitors, firm in the HBR case study GROW: Using Artificial Intelligence to Screen Human Intelligence 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 Intelligence Artificial 's lucrative customers.
High cash cycle compare to competitors
Intelligence Artificial 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.
Opportunities GROW: Using Artificial Intelligence to Screen Human Intelligence | 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 GROW: Using Artificial Intelligence to Screen Human Intelligence are -
Better consumer reach
– The expansion of the 5G network will help Intelligence Artificial to increase its market reach. Intelligence Artificial 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.
Manufacturing automation
– Intelligence Artificial can use the latest technology developments to improve its manufacturing and designing process in Organizational Development segment. It can use CAD and 3D printing to build a quick prototype and pilot testing products. It can leverage automation using machine learning and artificial intelligence to do faster production at lowers costs, and it can leverage the growth in satellite and tracking technologies to improve inventory management, transportation, and shipping.
Changes in consumer behavior post Covid-19
– Consumer behavior has changed in the Organizational Development industry because of Covid-19 restrictions. Some of this behavior will stay once things get back to normal. Intelligence Artificial 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. Intelligence Artificial 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.
Leveraging digital technologies
– Intelligence Artificial 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.
Redefining models of collaboration and team work
– As explained in the weaknesses section, Intelligence Artificial is facing challenges because of the dominance of functional experts in the organization. GROW: Using Artificial Intelligence to Screen Human Intelligence 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.
Building a culture of innovation
– managers at Intelligence Artificial 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 Organizational Development segment.
Learning at scale
– Online learning technologies has now opened space for Intelligence Artificial 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 Intelligence Artificial has opened avenues for new revenue streams for the organization in the industry. This can help Intelligence Artificial to build a more holistic ecosystem as suggested in the GROW: Using Artificial Intelligence to Screen Human Intelligence case study. Intelligence Artificial can build new products and services such as - data insight services, data privacy related products, data based consulting services, etc.
Reforming the budgeting process
- By establishing new metrics that will be used to evaluate both existing and potential projects Intelligence Artificial can not only reduce the costs of the project but also help it in integrating the projects with other processes within the organization.
Low interest rates
– Even though inflation is raising its head in most developed economies, Intelligence Artificial 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.
Buying journey improvements
– Intelligence Artificial can improve the customer journey of consumers in the industry by using analytics and artificial intelligence. GROW: Using Artificial Intelligence to Screen Human Intelligence 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.
Finding new ways to collaborate
– Covid-19 has not only transformed business models of companies in Organizational Development industry, but it has also influenced the consumer preferences. Intelligence Artificial can tie-up with other value chain partners to explore new opportunities regarding meeting customer demands and building a rewarding and engaging relationship.
Developing new processes and practices
– Intelligence Artificial can develop new processes and procedures in Organizational Development 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.
Threats GROW: Using Artificial Intelligence to Screen Human Intelligence External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats mentioned in the HBR case study GROW: Using Artificial Intelligence to Screen Human Intelligence are -
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 Intelligence Artificial in the Organizational Development sector and impact the bottomline of the organization.
Consumer confidence and its impact on Intelligence Artificial 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
– Intelligence Artificial 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.
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. Intelligence Artificial 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.
Environmental challenges
– Intelligence Artificial 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. Intelligence Artificial can take advantage of this fund but it will also bring new competitors in the Organizational Development industry.
Trade war between China and United States
– The trade war between two of the biggest economies can hugely impact the opportunities for Intelligence Artificial in the Organizational Development industry. The Organizational Development 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.
Increasing international competition and downward pressure on margins
– Apart from technology driven competitive advantage dilution, Intelligence Artificial 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 GROW: Using Artificial Intelligence to Screen Human Intelligence .
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 Intelligence Artificial business can come under increasing regulations regarding data privacy, data security, etc.
Technology acceleration in Forth Industrial Revolution
– Intelligence Artificial has witnessed rapid integration of technology during Covid-19 in the Organizational Development industry. As one of the leading players in the industry, Intelligence Artificial needs to keep up with the evolution of technology in the Organizational Development 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.
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 Intelligence Artificial.
Learning curve for new practices
– As the technology based on artificial intelligence and machine learning platform is getting complex, as highlighted in case study GROW: Using Artificial Intelligence to Screen Human Intelligence, Intelligence Artificial may face longer learning curve for training and development of existing employees. This can open space for more nimble competitors in the field of Organizational Development .
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. Intelligence Artificial needs to understand the core reasons impacting the Organizational Development industry. This will help it in building a better workplace.
Barriers of entry lowering
– As technology is more democratized, the barriers to entry in the industry are lowering. It can presents Intelligence Artificial with greater competitive threats in the near to medium future. Secondly it will also put downward pressure on pricing throughout the sector.
Weighted SWOT Analysis of GROW: Using Artificial Intelligence to Screen Human Intelligence 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 GROW: Using Artificial Intelligence to Screen Human Intelligence 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 GROW: Using Artificial Intelligence to Screen Human Intelligence 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 GROW: Using Artificial Intelligence to Screen Human Intelligence 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 GROW: Using Artificial Intelligence to Screen Human Intelligence 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 Intelligence Artificial needs to make to build a sustainable competitive advantage.
