Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
Innovation & Entrepreneurship
Strategy / MBA Resources
Case Study SWOT Analysis Solution
Case Study Description of Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP)
This case examines the intersection of two firms (Cogent Labs-a machine learning software firm in Tokyo; and Google, the technology infrastructure giant) attempting to exploit the benefits of artificial intelligence and machine learning in the financial services sector. The case protagonist, David Malkin, known as the "AI Architect" at Cogent Labs, must decide how best to position his firm for growth. Malkin knew that artificial intelligence had great potential to revolutionize several aspects of the financial services industry, but he also knew that artificial intelligence's greatest achievements to date were in very narrow functions. Malkin further knew that large, sophisticated financial service clients owned a vast array of proprietary datasets that were impossible to replicate. Meanwhile the major "cloud" providers like Google, Amazon, and Microsoft had large-scale computing infrastructures and multi-billion-dollar research and development budgets with which they could (and did) generate innovative artificial intelligence software of their own. Malkin wondered how a small software firm like Cogent Labs without its own proprietary datasets, or a large-scale computing infrastructure, or a multi-billion R&D budget could fit in? Would Cogent Labs' current approach of developing their own proprietary machine learning applications to run on the cloud and sell directly to financial services firms in Tokyo prove to be a sustainable model? Or would Cogent Labs ultimately need to partner/merge with one of the major cloud providers in order to provide the expertise necessary to customize their offerings for financial services clients? Or, was the future even more uncertain; would software firms like Cogent eventually need to create and own new datasets of their own, and build their own infrastructures to host their own new data, in order to avoid being disintermediated in the future if (and when) machine learning expertise became truly commoditized?
Authors :: Lauren H. Cohen, Christopher Malloy, William Powley
Swot Analysis of "Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP)" written by Lauren H. Cohen, Christopher Malloy, William Powley includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Cogent Labs facing as an external strategic factors. Some of the topics covered in Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) case study are - Strategic Management Strategies, Financial management and Innovation & Entrepreneurship.
Some of the macro environment factors that can be used to understand the Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) casestudy better are - – increasing energy prices, there is backlash against globalization, geopolitical disruptions, talent flight as more people leaving formal jobs, there is increasing trade war between United States & China, banking and financial system is disrupted by Bitcoin and other crypto currencies, challanges to central banks by blockchain based private currencies,
increasing government debt because of Covid-19 spendings, increasing inequality as vast percentage of new income is going to the top 1%, etc
Introduction to SWOT Analysis of Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP)
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Cogent Labs, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Cogent Labs 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 Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) can be done for the following purposes –
1. Strategic planning using facts provided in Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) case study
2. Improving business portfolio management of Cogent Labs
3. Assessing feasibility of the new initiative in Innovation & Entrepreneurship field.
4. Making a Innovation & Entrepreneurship topic specific business decision
5. Set goals for the organization
6. Organizational restructuring of Cogent Labs
Strengths Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Cogent Labs in Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) Harvard Business Review case study are -
Operational resilience
– The operational resilience strategy in the Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) 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.
Analytics focus
– Cogent Labs 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 Lauren H. Cohen, Christopher Malloy, William Powley 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.
Cross disciplinary teams
– Horizontal connected teams at the Cogent Labs 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.
Digital Transformation in Innovation & Entrepreneurship segment
- digital transformation varies from industry to industry. For Cogent Labs digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Cogent Labs 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.
Ability to recruit top talent
– Cogent Labs is one of the leading recruiters in the industry. Managers in the Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) are in a position to attract the best talent available. The firm has a robust talent identification program that helps in identifying the brightest.
Successful track record of launching new products
– Cogent Labs has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Cogent Labs 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.
Innovation driven organization
– Cogent Labs is one of the most innovative firm in sector. Manager in Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) Harvard Business Review case study can use Clayton Christensen Disruptive Innovation strategies to further increase the scale of innovtions in the organization.
Diverse revenue streams
– Cogent Labs is present in almost all the verticals within the industry. This has provided firm in Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) 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.
High brand equity
– Cogent Labs has strong brand awareness and brand recognition among both - the exiting customers and potential new customers. Strong brand equity has enabled Cogent Labs to keep acquiring new customers and building profitable relationship with both the new and loyal customers.
Strong track record of project management
– Cogent Labs is known for sticking to its project targets. This enables the firm to manage – time, project costs, and have sustainable margins on the projects.
Sustainable margins compare to other players in Innovation & Entrepreneurship industry
– Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) firm has clearly differentiated products in the market place. This has enabled Cogent Labs to fetch slight price premium compare to the competitors in the Innovation & Entrepreneurship industry. The sustainable margins have also helped Cogent Labs to invest into research and development (R&D) and innovation.
Effective Research and Development (R&D)
– Cogent Labs 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 Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) - staying ahead in the industry in terms of – new product launches, superior customer experience, highly competitive pricing strategies, and great returns to the shareholders.
Weaknesses Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) are -
Products dominated business model
– Even though Cogent Labs 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 - Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) should strive to include more intangible value offerings along with its core products and services.
Interest costs
– Compare to the competition, Cogent Labs 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.
Slow to harness new channels of communication
– Even though competitors are using new communication channels such as Instagram, Tiktok, and Snap, Cogent Labs is slow explore the new channels of communication. These new channels of communication mentioned in marketing section of case study Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) can help to provide better information regarding products and services. It can also build an online community to further reach out to potential customers.
Lack of clear differentiation of Cogent Labs products
– To increase the profitability and margins on the products, Cogent Labs needs to provide more differentiated products than what it is currently offering in the marketplace.
Workers concerns about automation
– As automation is fast increasing in the segment, Cogent Labs 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.
Need for greater diversity
– Cogent Labs 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.
Slow decision making process
– As mentioned earlier in the report, Cogent Labs 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. Cogent Labs 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.
High cash cycle compare to competitors
Cogent Labs 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.
High operating costs
– Compare to the competitors, firm in the HBR case study Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) 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 Cogent Labs 's lucrative customers.
High bargaining power of channel partners
– Because of the regulatory requirements, Lauren H. Cohen, Christopher Malloy, William Powley suggests that, Cogent Labs 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.
No frontier risks strategy
– After analyzing the HBR case study Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP), it seems that company is thinking about the frontier risks that can impact Innovation & Entrepreneurship 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.
Opportunities Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) | 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 Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) are -
Low interest rates
– Even though inflation is raising its head in most developed economies, Cogent Labs 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.
Increase in government spending
– As the United States and other governments are increasing social spending and infrastructure spending to build economies post Covid-19, Cogent Labs can use these opportunities to build new business models that can help the communities that Cogent Labs operates in. Secondly it can use opportunities from government spending in Innovation & Entrepreneurship sector.
Learning at scale
– Online learning technologies has now opened space for Cogent Labs 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.
Reforming the budgeting process
- By establishing new metrics that will be used to evaluate both existing and potential projects Cogent Labs can not only reduce the costs of the project but also help it in integrating the projects with other processes within the organization.
Lowering marketing communication costs
– 5G expansion will open new opportunities for Cogent Labs in the field of marketing communication. It will bring down the cost of doing business, provide technology platform to build new products in the Innovation & Entrepreneurship segment, and it will provide faster access to the consumers.
Loyalty marketing
– Cogent Labs 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.
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 Cogent Labs 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.
Building a culture of innovation
– managers at Cogent Labs 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 Innovation & Entrepreneurship segment.
Using analytics as competitive advantage
– Cogent Labs 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 Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) - to build a competitive advantage using analytics. The analytics driven competitive advantage can help Cogent Labs to build faster Go To Market strategies, better consumer insights, developing relevant product features, and building a highly efficient supply chain.
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. Cogent Labs 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 Innovation & Entrepreneurship industry because of Covid-19 restrictions. Some of this behavior will stay once things get back to normal. Cogent Labs 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. Cogent Labs 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.
Buying journey improvements
– Cogent Labs can improve the customer journey of consumers in the industry by using analytics and artificial intelligence. Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) 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.
Developing new processes and practices
– Cogent Labs can develop new processes and procedures in Innovation & Entrepreneurship 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 Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats mentioned in the HBR case study Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) are -
Stagnating economy with rate increase
– Cogent Labs 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 Cogent Labs in the Innovation & Entrepreneurship sector and impact the bottomline of the organization.
Shortening product life cycle
– it is one of the major threat that Cogent Labs is facing in Innovation & Entrepreneurship sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, etc.
Consumer confidence and its impact on Cogent Labs 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 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. Cogent Labs needs to understand the core reasons impacting the Innovation & Entrepreneurship industry. This will help it in building a better workplace.
Trade war between China and United States
– The trade war between two of the biggest economies can hugely impact the opportunities for Cogent Labs in the Innovation & Entrepreneurship industry. The Innovation & Entrepreneurship 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.
Learning curve for new practices
– As the technology based on artificial intelligence and machine learning platform is getting complex, as highlighted in case study Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP), Cogent Labs may face longer learning curve for training and development of existing employees. This can open space for more nimble competitors in the field of Innovation & Entrepreneurship .
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. Cogent Labs 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.
Technology acceleration in Forth Industrial Revolution
– Cogent Labs has witnessed rapid integration of technology during Covid-19 in the Innovation & Entrepreneurship industry. As one of the leading players in the industry, Cogent Labs needs to keep up with the evolution of technology in the Innovation & Entrepreneurship 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 Cogent Labs.
Easy access to finance
– Easy access to finance in Innovation & Entrepreneurship field will also reduce the barriers to entry in the industry, thus putting downward pressure on the prices because of increasing competition. Cogent Labs can utilize it by borrowing at lower rates and invest it into research and development, capital expenditure to fortify its core competitive advantage.
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.
Barriers of entry lowering
– As technology is more democratized, the barriers to entry in the industry are lowering. It can presents Cogent Labs 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 Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) 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 Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) 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 Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) 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 Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) 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 Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) 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 Cogent Labs needs to make to build a sustainable competitive advantage.
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