Putting Artificial Intelligence to Work SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
Strategy & Execution
Strategy / MBA Resources
Case Study SWOT Analysis Solution
Case Study Description of Putting Artificial Intelligence to Work
Despite the increase in AI-enabled applications, significant adoption of AI in business remains low: According to a survey by the Boston Consulting Group, only 1 in 20 companies has extensively incorporated AI. Nevertheless, every industry includes companies that are ahead of the pack. The authors-all senior BCG consultants-present a wide variety of uses, from marketing to operations to support functions, that demonstrate just how effective AI can be in creating value.
Authors :: Philipp Gerbert, Martin Hecker, Sebastian Steinhauser
Swot Analysis of "Putting Artificial Intelligence to Work" written by Philipp Gerbert, Martin Hecker, Sebastian Steinhauser includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Ai Bcg facing as an external strategic factors. Some of the topics covered in Putting Artificial Intelligence to Work case study are - Strategic Management Strategies, Technology and Strategy & Execution.
Some of the macro environment factors that can be used to understand the Putting Artificial Intelligence to Work casestudy better are - – competitive advantages are harder to sustain because of technology dispersion, increasing energy prices, banking and financial system is disrupted by Bitcoin and other crypto currencies, increasing commodity prices, increasing government debt because of Covid-19 spendings, there is backlash against globalization, central banks are concerned over increasing inflation,
digital marketing is dominated by two big players Facebook and Google, cloud computing is disrupting traditional business models, etc
Introduction to SWOT Analysis of Putting Artificial Intelligence to Work
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in Putting Artificial Intelligence to Work case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Ai Bcg, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Ai Bcg 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 Putting Artificial Intelligence to Work can be done for the following purposes –
1. Strategic planning using facts provided in Putting Artificial Intelligence to Work case study
2. Improving business portfolio management of Ai Bcg
3. Assessing feasibility of the new initiative in Strategy & Execution field.
4. Making a Strategy & Execution topic specific business decision
5. Set goals for the organization
6. Organizational restructuring of Ai Bcg
Strengths Putting Artificial Intelligence to Work | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Ai Bcg in Putting Artificial Intelligence to Work Harvard Business Review case study are -
Operational resilience
– The operational resilience strategy in the Putting Artificial Intelligence to Work 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.
Innovation driven organization
– Ai Bcg is one of the most innovative firm in sector. Manager in Putting Artificial Intelligence to Work Harvard Business Review case study can use Clayton Christensen Disruptive Innovation strategies to further increase the scale of innovtions in the organization.
Successful track record of launching new products
– Ai Bcg has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Ai Bcg 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
– Ai Bcg is one of the leading recruiters in the industry. Managers in the Putting Artificial Intelligence to Work are in a position to attract the best talent available. The firm has a robust talent identification program that helps in identifying the brightest.
Organizational Resilience of Ai Bcg
– The covid-19 pandemic has put organizational resilience at the centre of everthing that Ai Bcg 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 Ai Bcg 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.
Training and development
– Ai Bcg has one of the best training and development program in the industry. The effectiveness of the training programs can be measured in Putting Artificial Intelligence to Work 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.
Highly skilled collaborators
– Ai Bcg 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 Putting Artificial Intelligence to Work HBR case study have helped the firm to develop new products and bring them quickly to the marketplace.
Cross disciplinary teams
– Horizontal connected teams at the Ai Bcg 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.
Ability to lead change in Strategy & Execution field
– Ai Bcg 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 Ai Bcg in – penetrating new markets, reaching out to new customers, and providing different value propositions to different customers in the international markets.
Strong track record of project management
– Ai Bcg is known for sticking to its project targets. This enables the firm to manage – time, project costs, and have sustainable margins on the projects.
Diverse revenue streams
– Ai Bcg is present in almost all the verticals within the industry. This has provided firm in Putting Artificial Intelligence to Work 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.
Weaknesses Putting Artificial Intelligence to Work | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Putting Artificial Intelligence to Work are -
Employees’ incomplete understanding of strategy
– From the instances in the HBR case study Putting Artificial Intelligence to Work, it seems that the employees of Ai Bcg 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.
Increasing silos among functional specialists
– The organizational structure of Ai Bcg is dominated by functional specialists. It is not different from other players in the Strategy & Execution segment. Ai Bcg needs to de-silo the office environment to harness the true potential of its workforce. Secondly the de-silo will also help Ai Bcg to focus more on services rather than just following the product oriented approach.
Need for greater diversity
– Ai Bcg 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.
High cash cycle compare to competitors
Ai Bcg 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.
Capital Spending Reduction
– Even during the low interest decade, Ai Bcg 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, Philipp Gerbert, Martin Hecker, Sebastian Steinhauser suggests that, Ai Bcg 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.
Lack of clear differentiation of Ai Bcg products
– To increase the profitability and margins on the products, Ai Bcg needs to provide more differentiated products than what it is currently offering in the marketplace.
Aligning sales with marketing
– It come across in the case study Putting Artificial Intelligence to Work 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 Putting Artificial Intelligence to Work can leverage the sales team experience to cultivate customer relationships as Ai Bcg is planning to shift buying processes online.
Skills based hiring
– The stress on hiring functional specialists at Ai Bcg 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.
Workers concerns about automation
– As automation is fast increasing in the segment, Ai Bcg needs to come up with a strategy to reduce the workers concern regarding automation. Without a clear strategy, it could lead to disruption and uncertainty within the organization.
Compensation and incentives
– The revenue per employee as mentioned in the HBR case study Putting Artificial Intelligence to Work, is just above the industry average. Ai Bcg 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.
Opportunities Putting Artificial Intelligence to Work | 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 Putting Artificial Intelligence to Work are -
Using analytics as competitive advantage
– Ai Bcg 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 Putting Artificial Intelligence to Work - to build a competitive advantage using analytics. The analytics driven competitive advantage can help Ai Bcg to build faster Go To Market strategies, better consumer insights, developing relevant product features, and building a highly efficient supply chain.
Leveraging digital technologies
– Ai Bcg 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.
Developing new processes and practices
– Ai Bcg can develop new processes and procedures in Strategy & Execution 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.
Finding new ways to collaborate
– Covid-19 has not only transformed business models of companies in Strategy & Execution industry, but it has also influenced the consumer preferences. Ai Bcg can tie-up with other value chain partners to explore new opportunities regarding meeting customer demands and building a rewarding and engaging relationship.
Increase in government spending
– As the United States and other governments are increasing social spending and infrastructure spending to build economies post Covid-19, Ai Bcg can use these opportunities to build new business models that can help the communities that Ai Bcg operates in. Secondly it can use opportunities from government spending in Strategy & Execution sector.
Low interest rates
– Even though inflation is raising its head in most developed economies, Ai Bcg 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.
Learning at scale
– Online learning technologies has now opened space for Ai Bcg 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.
Lowering marketing communication costs
– 5G expansion will open new opportunities for Ai Bcg in the field of marketing communication. It will bring down the cost of doing business, provide technology platform to build new products in the Strategy & Execution segment, and it will provide faster access to the consumers.
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 Ai Bcg 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.
Loyalty marketing
– Ai Bcg 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 Ai Bcg can not only reduce the costs of the project but also help it in integrating the projects with other processes within the organization.
Creating value in data economy
– The success of analytics program of Ai Bcg has opened avenues for new revenue streams for the organization in the industry. This can help Ai Bcg to build a more holistic ecosystem as suggested in the Putting Artificial Intelligence to Work case study. Ai Bcg can build new products and services such as - data insight services, data privacy related products, data based consulting services, 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. Ai Bcg can explore opportunities that can attract volunteers and are consistent with its mission and vision.
Threats Putting Artificial Intelligence to Work External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats mentioned in the HBR case study Putting Artificial Intelligence to Work are -
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 Ai Bcg.
Increasing wage structure of Ai Bcg
– 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 Ai Bcg.
Increasing international competition and downward pressure on margins
– Apart from technology driven competitive advantage dilution, Ai Bcg 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 Putting Artificial Intelligence to Work .
Shortening product life cycle
– it is one of the major threat that Ai Bcg is facing in Strategy & Execution sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, 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.
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. Ai Bcg needs to understand the core reasons impacting the Strategy & Execution industry. This will help it in building a better workplace.
Learning curve for new practices
– As the technology based on artificial intelligence and machine learning platform is getting complex, as highlighted in case study Putting Artificial Intelligence to Work, Ai Bcg may face longer learning curve for training and development of existing employees. This can open space for more nimble competitors in the field of Strategy & Execution .
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 Ai Bcg business can come under increasing regulations regarding data privacy, data security, etc.
Consumer confidence and its impact on Ai Bcg 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.
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.
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 Ai Bcg in the Strategy & Execution sector and impact the bottomline of the organization.
Easy access to finance
– Easy access to finance in Strategy & Execution field will also reduce the barriers to entry in the industry, thus putting downward pressure on the prices because of increasing competition. Ai Bcg can utilize it by borrowing at lower rates and invest it into research and development, capital expenditure to fortify its core competitive advantage.
Stagnating economy with rate increase
– Ai Bcg 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 Putting Artificial Intelligence to Work 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 Putting Artificial Intelligence to Work 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 Putting Artificial Intelligence to Work 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 Putting Artificial Intelligence to Work 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 Putting Artificial Intelligence to Work 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 Ai Bcg needs to make to build a sustainable competitive advantage.
