Why All Companies Need a Data Experience Designer SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
Innovation & Entrepreneurship
Strategy / MBA Resources
Case Study SWOT Analysis Solution
Case Study Description of Why All Companies Need a Data Experience Designer
Pundits have dubbed personal data "the new oil" of the 21st century. Yet for all the hype surrounding big data, people complain they have less meaning and are frustrated with how poorly brands leverage their information. That's because many companies still mine data with the end goal of streamlining business processes, largely neglecting an essential piece in the data economy puzzle: the person. This article summarizes the findings of a global research project into the values and behavior of data "prosumers" -- individuals who are both producers and consumers of data, and who expect their personal data to be used to deliver new and better experiences. The authors define the core elements of a new design mind-set that companies must adopt as they create new data-rich products and services. In the emerging Personal Data Economy, firms will reap value to the extent that they enable, empower and meet future needs, rather than merely analyzing past behavior. They envisage a new organizational figure -- the data experience designer -- to take the process forward.
Swot Analysis of "Why All Companies Need a Data Experience Designer" written by Abby Margolis, Evgeny Kaganer includes – strengths weakness that are internal strategic factors of the organization, and opportunities and threats that Data Designer facing as an external strategic factors. Some of the topics covered in Why All Companies Need a Data Experience Designer case study are - Strategic Management Strategies, IT and Innovation & Entrepreneurship.
Some of the macro environment factors that can be used to understand the Why All Companies Need a Data Experience Designer casestudy better are - – geopolitical disruptions, there is backlash against globalization, supply chains are disrupted by pandemic , increasing commodity prices, there is increasing trade war between United States & China, technology disruption, digital marketing is dominated by two big players Facebook and Google,
banking and financial system is disrupted by Bitcoin and other crypto currencies, increasing household debt because of falling income levels, etc
Introduction to SWOT Analysis of Why All Companies Need a Data Experience Designer
SWOT stands for an organization’s Strengths, Weaknesses, Opportunities and Threats . At Oak Spring University , we believe that protagonist in Why All Companies Need a Data Experience Designer case study can use SWOT analysis as a strategic management tool to assess the current internal strengths and weaknesses of the Data Designer, and to figure out the opportunities and threats in the macro environment – technological, environmental, political, economic, social, demographic, etc in which Data Designer 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 Why All Companies Need a Data Experience Designer can be done for the following purposes –
1. Strategic planning using facts provided in Why All Companies Need a Data Experience Designer case study
2. Improving business portfolio management of Data Designer
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 Data Designer
Strengths Why All Companies Need a Data Experience Designer | Internal Strategic Factors
What are Strengths in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The strengths of Data Designer in Why All Companies Need a Data Experience Designer Harvard Business Review case study are -
Strong track record of project management
– Data Designer is known for sticking to its project targets. This enables the firm to manage – time, project costs, and have sustainable margins on the projects.
Effective Research and Development (R&D)
– Data Designer 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 Why All Companies Need a Data Experience Designer - staying ahead in the industry in terms of – new product launches, superior customer experience, highly competitive pricing strategies, and great returns to the shareholders.
Cross disciplinary teams
– Horizontal connected teams at the Data Designer 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.
Low bargaining power of suppliers
– Suppliers of Data Designer in the sector have low bargaining power. Why All Companies Need a Data Experience Designer has further diversified its suppliers portfolio by building a robust supply chain across various countries. This helps Data Designer to manage not only supply disruptions but also source products at highly competitive prices.
Successful track record of launching new products
– Data Designer has launched numerous new products in last few years, keeping in mind evolving customer preferences and competitive pressures. Data Designer 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.
Training and development
– Data Designer has one of the best training and development program in the industry. The effectiveness of the training programs can be measured in Why All Companies Need a Data Experience Designer 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.
Operational resilience
– The operational resilience strategy in the Why All Companies Need a Data Experience Designer 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.
Diverse revenue streams
– Data Designer is present in almost all the verticals within the industry. This has provided firm in Why All Companies Need a Data Experience Designer 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.
Learning organization
- Data Designer is a learning organization. It has inculcated three key characters of learning organization in its processes and operations – exploration, creativity, and expansiveness. The work place at Data Designer is open place that encourages instructiveness, ideation, open minded discussions, and creativity. Employees and leaders in Why All Companies Need a Data Experience Designer Harvard Business Review case study emphasize – knowledge, initiative, and innovation.
Highly skilled collaborators
– Data Designer 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 Why All Companies Need a Data Experience Designer HBR case study have helped the firm to develop new products and bring them quickly to the marketplace.
Ability to recruit top talent
– Data Designer is one of the leading recruiters in the industry. Managers in the Why All Companies Need a Data Experience Designer are in a position to attract the best talent available. The firm has a robust talent identification program that helps in identifying the brightest.
Digital Transformation in Innovation & Entrepreneurship segment
- digital transformation varies from industry to industry. For Data Designer digital transformation journey comprises differing goals based on market maturity, customer technology acceptance, and organizational culture. Data Designer 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.
Weaknesses Why All Companies Need a Data Experience Designer | Internal Strategic Factors
What are Weaknesses in SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The weaknesses of Why All Companies Need a Data Experience Designer are -
Products dominated business model
– Even though Data Designer 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 - Why All Companies Need a Data Experience Designer should strive to include more intangible value offerings along with its core products and services.
Compensation and incentives
– The revenue per employee as mentioned in the HBR case study Why All Companies Need a Data Experience Designer, is just above the industry average. Data Designer 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.
Employees’ incomplete understanding of strategy
– From the instances in the HBR case study Why All Companies Need a Data Experience Designer, it seems that the employees of Data Designer 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 Data Designer is dominated by functional specialists. It is not different from other players in the Innovation & Entrepreneurship segment. Data Designer needs to de-silo the office environment to harness the true potential of its workforce. Secondly the de-silo will also help Data Designer to focus more on services rather than just following the product oriented approach.
Slow decision making process
– As mentioned earlier in the report, Data Designer 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 Designer 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.
Interest costs
– Compare to the competition, Data Designer 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.
Capital Spending Reduction
– Even during the low interest decade, Data Designer 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.
Aligning sales with marketing
– It come across in the case study Why All Companies Need a Data Experience Designer 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 Why All Companies Need a Data Experience Designer can leverage the sales team experience to cultivate customer relationships as Data Designer is planning to shift buying processes online.
No frontier risks strategy
– After analyzing the HBR case study Why All Companies Need a Data Experience Designer, 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.
Need for greater diversity
– Data Designer 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.
Skills based hiring
– The stress on hiring functional specialists at Data Designer 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.
Opportunities Why All Companies Need a Data Experience Designer | 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 Why All Companies Need a Data Experience Designer are -
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 Designer can use these opportunities to build new business models that can help the communities that Data Designer operates in. Secondly it can use opportunities from government spending in Innovation & Entrepreneurship sector.
Reforming the budgeting process
- By establishing new metrics that will be used to evaluate both existing and potential projects Data Designer 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 Data Designer has opened avenues for new revenue streams for the organization in the industry. This can help Data Designer to build a more holistic ecosystem as suggested in the Why All Companies Need a Data Experience Designer case study. Data Designer can build new products and services such as - data insight services, data privacy related products, data based consulting services, etc.
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. Data Designer 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. Data Designer 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
– Data Designer can improve the customer journey of consumers in the industry by using analytics and artificial intelligence. Why All Companies Need a Data Experience Designer 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.
Redefining models of collaboration and team work
– As explained in the weaknesses section, Data Designer is facing challenges because of the dominance of functional experts in the organization. Why All Companies Need a Data Experience Designer 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.
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 Designer 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.
Manufacturing automation
– Data Designer can use the latest technology developments to improve its manufacturing and designing process in Innovation & Entrepreneurship 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.
Building a culture of innovation
– managers at Data Designer 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.
Low interest rates
– Even though inflation is raising its head in most developed economies, Data Designer 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.
Developing new processes and practices
– Data Designer 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.
Using analytics as competitive advantage
– Data Designer 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 Why All Companies Need a Data Experience Designer - to build a competitive advantage using analytics. The analytics driven competitive advantage can help Data Designer to build faster Go To Market strategies, better consumer insights, developing relevant product features, and building a highly efficient supply chain.
Lowering marketing communication costs
– 5G expansion will open new opportunities for Data Designer 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.
Threats Why All Companies Need a Data Experience Designer External Strategic Factors
What are Threats in the SWOT Analysis / TOWS Matrix / Weighted SWOT Analysis
The threats mentioned in the HBR case study Why All Companies Need a Data Experience Designer are -
Increasing wage structure of Data Designer
– 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 Designer.
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 Designer needs to understand the core reasons impacting the Innovation & Entrepreneurship 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 Why All Companies Need a Data Experience Designer, Data Designer 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 .
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 Data Designer business can come under increasing regulations regarding data privacy, data security, etc.
Consumer confidence and its impact on Data Designer 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.
Environmental challenges
– Data Designer 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 Designer can take advantage of this fund but it will also bring new competitors in the Innovation & Entrepreneurship industry.
High dependence on third party suppliers
– Data Designer 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. Data Designer 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.
Shortening product life cycle
– it is one of the major threat that Data Designer is facing in Innovation & Entrepreneurship sector. It can lead to higher research and development costs, higher marketing expenses, lower customer loyalty, etc.
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. Data Designer can utilize it by borrowing at lower rates and invest it into research and development, capital expenditure to fortify its core competitive advantage.
Trade war between China and United States
– The trade war between two of the biggest economies can hugely impact the opportunities for Data Designer 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.
Barriers of entry lowering
– As technology is more democratized, the barriers to entry in the industry are lowering. It can presents Data Designer with greater competitive threats in the near to medium future. Secondly it will also put downward pressure on pricing throughout the sector.
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.
Weighted SWOT Analysis of Why All Companies Need a Data Experience Designer 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 Why All Companies Need a Data Experience Designer 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 Why All Companies Need a Data Experience Designer 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 Why All Companies Need a Data Experience Designer 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 Why All Companies Need a Data Experience Designer 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 Designer needs to make to build a sustainable competitive advantage.
