Lessons from Becoming a Data-Driven Organization SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
Leadership & Managing People
Strategy / MBA Resources
Case Study SWOT Analysis Solution
Case Study Description of Lessons from Becoming a Data-Driven Organization
This is an MIT Sloan Management Review Article. Organizations across the business spectrum are awakening to the transformative power of data and analytics. They are also coming to grips with the daunting difficulty of the task that lies before them. It's tough enough for many organizations to catalog and categorize the data at their disposal and devise the rules and processes for using it. It's even tougher to translate that data into tangible value. But it's not impossible, and many organizations, in both the private and public sectors, are learning how.
Swot Analysis of "Lessons from Becoming a Data-Driven Organization" written by David Kiron includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Data Organizations facing as an external strategic factors. Some of the topics covered in Lessons from Becoming a Data-Driven Organization case study are - Strategic Management Strategies, and Leadership & Managing People.
Some of the macro environment factors that can be used to understand the Lessons from Becoming a Data-Driven Organization casestudy better are - – central banks are concerned over increasing inflation, increasing energy prices, increasing household debt because of falling income levels, digital marketing is dominated by two big players Facebook and Google, technology disruption, increasing commodity prices, increasing transportation and logistics costs,
talent flight as more people leaving formal jobs, geopolitical disruptions, etc
Introduction to SWOT Analysis of Lessons from Becoming a Data-Driven Organization
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in Lessons from Becoming a Data-Driven Organization case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Data Organizations, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Data Organizations 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 Lessons from Becoming a Data-Driven Organization can be done for the following purposes –
1. Strategic planning using facts provided in Lessons from Becoming a Data-Driven Organization case study
2. Improving business portfolio management of Data Organizations
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 Data Organizations
Strengths Lessons from Becoming a Data-Driven Organization | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Data Organizations in Lessons from Becoming a Data-Driven Organization Harvard Business Review case study are -
Diverse revenue streams
– Data Organizations is present in almost all the verticals within the industry. This has provided firm in Lessons from Becoming a Data-Driven Organization 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.
Innovation driven organization
– Data Organizations is one of the most innovative firm in sector. Manager in Lessons from Becoming a Data-Driven Organization Harvard Business Review case study can use Clayton Christensen Disruptive Innovation strategies to further increase the scale of innovtions in the organization.
Cross disciplinary teams
– Horizontal connected teams at the Data Organizations 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.
Strong track record of project management
– Data Organizations is known for sticking to its project targets. This enables the firm to manage – time, project costs, and have sustainable margins on the projects.
Ability to lead change in Leadership & Managing People field
– Data Organizations 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 Data Organizations in – penetrating new markets, reaching out to new customers, and providing different value propositions to different customers in the international markets.
Operational resilience
– The operational resilience strategy in the Lessons from Becoming a Data-Driven Organization 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.
Low bargaining power of suppliers
– Suppliers of Data Organizations in the sector have low bargaining power. Lessons from Becoming a Data-Driven Organization has further diversified its suppliers portfolio by building a robust supply chain across various countries. This helps Data Organizations to manage not only supply disruptions but also source products at highly competitive prices.
Ability to recruit top talent
– Data Organizations is one of the leading recruiters in the industry. Managers in the Lessons from Becoming a Data-Driven Organization are in a position to attract the best talent available. The firm has a robust talent identification program that helps in identifying the brightest.
High switching costs
– The high switching costs that Data Organizations 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.
Successful track record of launching new products
– Data Organizations has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Data Organizations 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.
Organizational Resilience of Data Organizations
– The covid-19 pandemic has put organizational resilience at the centre of everthing that Data Organizations does. Organizational resilience comprises - Financial Resilience, Operational Resilience, Technological Resilience, Organizational Resilience, Business Model Resilience, and Reputation Resilience.
Effective Research and Development (R&D)
– Data Organizations 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 Lessons from Becoming a Data-Driven Organization - 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 Lessons from Becoming a Data-Driven Organization | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Lessons from Becoming a Data-Driven Organization are -
High bargaining power of channel partners
– Because of the regulatory requirements, David Kiron suggests that, Data Organizations 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 star products
– The top 2 products and services of the firm as mentioned in the Lessons from Becoming a Data-Driven Organization 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 Data Organizations has relatively successful track record of launching new products.
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 Data Organizations supply chain. Even after few cautionary changes mentioned in the HBR case study - Lessons from Becoming a Data-Driven Organization, it is still heavily dependent upon the existing supply chain. The existing supply chain though brings in cost efficiencies but it has left Data Organizations vulnerable to further global disruptions in South East Asia.
Products dominated business model
– Even though Data Organizations 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 - Lessons from Becoming a Data-Driven Organization should strive to include more intangible value offerings along with its core products and services.
Interest costs
– Compare to the competition, Data Organizations 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.
High cash cycle compare to competitors
Data Organizations 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.
Lack of clear differentiation of Data Organizations products
– To increase the profitability and margins on the products, Data Organizations needs to provide more differentiated products than what it is currently offering in the marketplace.
Low market penetration in new markets
– Outside its home market of Data Organizations, firm in the HBR case study Lessons from Becoming a Data-Driven Organization needs to spend more promotional, marketing, and advertising efforts to penetrate international markets.
Slow decision making process
– As mentioned earlier in the report, Data Organizations 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. Data Organizations 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.
Employees’ incomplete understanding of strategy
– From the instances in the HBR case study Lessons from Becoming a Data-Driven Organization, it seems that the employees of Data Organizations 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.
No frontier risks strategy
– After analyzing the HBR case study Lessons from Becoming a Data-Driven Organization, 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.
Opportunities Lessons from Becoming a Data-Driven Organization | 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 Lessons from Becoming a Data-Driven Organization are -
Low interest rates
– Even though inflation is raising its head in most developed economies, Data Organizations 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.
Remote work and new talent hiring opportunities
– The widespread usage of remote working technologies during Covid-19 has opened opportunities for Data Organizations 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 Data Organizations to hire the very best people irrespective of their geographical location.
Developing new processes and practices
– Data Organizations can develop new processes and procedures in Leadership & Managing People 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.
Harnessing reconfiguration of the global supply chains
– As the trade war between US and China heats up in the coming years, Data Organizations can build a diversified supply chain model across various countries in - South East Asia, India, and other parts of the world. This reconfiguration of global supply chain can help, as suggested in case study, Lessons from Becoming a Data-Driven Organization, to buy more products closer to the markets, and it can leverage its size and influence to get better deal from the local markets.
Building a culture of innovation
– managers at Data Organizations 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.
Increase in government spending
– As the United States and other governments are increasing social spending and infrastructure spending to build economies post Covid-19, Data Organizations can use these opportunities to build new business models that can help the communities that Data Organizations operates in. Secondly it can use opportunities from government spending in Leadership & Managing People sector.
Loyalty marketing
– Data Organizations 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.
Using analytics as competitive advantage
– Data Organizations 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 Lessons from Becoming a Data-Driven Organization - to build a competitive advantage using analytics. The analytics driven competitive advantage can help Data Organizations to build faster Go To Market strategies, better consumer insights, developing relevant product features, and building a highly efficient supply chain.
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 Data Organizations 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.
Reforming the budgeting process
- By establishing new metrics that will be used to evaluate both existing and potential projects Data Organizations can not only reduce the costs of the project but also help it in integrating the projects with other processes within the organization.
Learning at scale
– Online learning technologies has now opened space for Data Organizations 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.
Better consumer reach
– The expansion of the 5G network will help Data Organizations to increase its market reach. Data Organizations 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.
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. Data Organizations can tie-up with other value chain partners to explore new opportunities regarding meeting customer demands and building a rewarding and engaging relationship.
Threats Lessons from Becoming a Data-Driven Organization External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats mentioned in the HBR case study Lessons from Becoming a Data-Driven Organization are -
Increasing international competition and downward pressure on margins
– Apart from technology driven competitive advantage dilution, Data Organizations 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 Lessons from Becoming a Data-Driven Organization .
Barriers of entry lowering
– As technology is more democratized, the barriers to entry in the industry are lowering. It can presents Data Organizations with greater competitive threats in the near to medium future. Secondly it will also put downward pressure on pricing throughout the sector.
Environmental challenges
– Data Organizations 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. Data Organizations can take advantage of this fund but it will also bring new competitors in the Leadership & Managing People industry.
Increasing wage structure of Data Organizations
– 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 Data Organizations.
Stagnating economy with rate increase
– Data Organizations 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.
Trade war between China and United States
– The trade war between two of the biggest economies can hugely impact the opportunities for Data Organizations in the Leadership & Managing People industry. The Leadership & Managing People 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.
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. Data Organizations needs to understand the core reasons impacting the Leadership & Managing People industry. This will help it in building a better workplace.
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.
Technology acceleration in Forth Industrial Revolution
– Data Organizations has witnessed rapid integration of technology during Covid-19 in the Leadership & Managing People industry. As one of the leading players in the industry, Data Organizations 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.
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 Data Organizations in the Leadership & Managing People sector and impact the bottomline of the organization.
High dependence on third party suppliers
– Data Organizations 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.
Learning curve for new practices
– As the technology based on artificial intelligence and machine learning platform is getting complex, as highlighted in case study Lessons from Becoming a Data-Driven Organization, Data Organizations 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 .
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. Data Organizations 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.
Weighted SWOT Analysis of Lessons from Becoming a Data-Driven Organization 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 Lessons from Becoming a Data-Driven Organization 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 Lessons from Becoming a Data-Driven Organization 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 Lessons from Becoming a Data-Driven Organization 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 Lessons from Becoming a Data-Driven Organization 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 Data Organizations needs to make to build a sustainable competitive advantage.