Analysis of using innovative cloud technologies for automatization of application tasks in a startup

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FEDERAL STATE EDUCATIONAL INSTITUTION

OF HIGHER EDUCATION

NATIONAL RESEARCH UNIVERSITY

HIGHER SCHOOL OF ECONOMICS

Saint Petersburg School of Economics and Management

Department of Management

Bachelor's thesis

In the field 38.03.02 `Management'

Educational programme `Management'

Analysis of using innovative cloud technologies for automatization of application tasks in a startup

Larionov Dmitriy Igorevich

Supervisor - Senior Lecturer

A.Y. Solomatin

Saint Petersburg 2019

Table of contents

Introduction

1. Literature review

1.1 Basic information about cloud services

1.2 Basic information about startups

1.3 Typology of cloud services

1.4 Lifecycle of startup

1.5 Efficiency in work

1.6 How efficiency influences on startups success

2. Statement of the research question

3. Methodology

4. Results

4.1 Mann-Whitney statistical test

4.2 Spearman correlation matrix

4.3 Kruskal Wallis statistical test

Conclusion

Reference list

Introduction

Different cloud services in modern world are so usual thing, that people often do not think about them: how they work, how they help and etc. Nowadays different services are used in almost every part of people's - both personal and professional. They help to store photos from phone, working with partners in one document at the same time, use utilities without downloading them and etc. In last 10-15 years cloud services transformed from interesting-suspicious novelty into necessary technical base for almost every company . In companies there are no questions about should they use “clouds” or not, but there only question how quickly can be integrated cloud services and how much of processes will be relocated on “cloud” base.

One more thing that actively develops and spread last years is a such type of business project as a “start-up”. Start-ups are usually represented as young, small, often technically oriented projects with limited budget and resources . In last years can be mentioned a lot of companies that started as a small startup end develops in huge companies that rule today's market. As examples can be mentioned Facebook, Google, PayPal, Apple and etc. Such examples can be an expiration for a lot of people to launch their own startup. But, due to statistics mare than 80% of startups failed on the second year after they were launched . Main reasons of fails are “ran out of cash”, “get outcompeted”, “cost issues”. In that case of special state of startups and growing popularity of such type of entrepreneurship there should be developed ways of optimizing of standard work and completing of basic tasks inside the project in order to increase its success rate and neutralize those main reasons of failure. And cloud services can be used in role of “startup problem solver”. In such conditions cloud services with optimization and economy that they provide may become a complete competitive advantage, if cloud services would actually improve start-up's efficiency. Maybe it is already widely used in startups, but there is no actual information about cloud services usage in startups and impact on startup efficiency and success. In this research will be explored which role have cloud services in modern startup industry and it impact on startup results of work. This fact leads to understanding that this thesis will fill the gap in knowledge in this sphere and deepen information that may help new startup to work with less losses. Should be mentioned that it will be the first thesis that explore such question in this exact industry od startups, because all the prior studies researched cloud services independently from business or researched influence of cloud services on classical business projects. Also, can be found different small commercial studies that were done by the company that provide cloud services for business but in this cases were investigated connections in 1 exact company, but picture of whole industry remains unclear.

Basing on all the information above can be formulated a main goal of this thesis: to find out and confirm an existence of correlation between usage of cloud services and startup's activity efficiency rates. On this basis can be identified object and subject of the work. As an object of the work are taken startups themselves and as a subject is the influence of cloud services on startups everyday work. In case if the existence of this connection will be identified it may become an answer for research question of this work: how automatization with cloud services influences on efficiency of completing of startup's practical tasks and cases? In order of actual existing connection could be said that cloud services positively influence on efficiency.

In order to reach the goal of this thesis there were set 5 main tasks:

1. Collect and analyse theoretical foundations about cloud services, startups and other adjacent topics. This will be done for better understanding of way of interaction of projects and cloud services. for preparing guide for next stage of the work and to confirm theoretically possible connections.

2. Interview with people that are involved in start-up industry. In this interview will be gotten inside information about cloud services usage in modern start-ups and subjective opinion about them.

3. Exploration of efficiency phenomenon and preparing of theoretical basis for accurate evaluating and subsequent comparing of this index in different startups considering cloud services impact.

4. Launching a survey that that will be based on information from theoretical part and on the interviews and that will help to collect statistics about cloud services in start-ups and information about actual efficiency in the company. This statistic will become a basis for next step.

5. Comparing of efficiency of start-ups considering cloud services impact on processes inside company with different level of cloud-services usage, basing on the information that were set in stage 3.

As for the methods of completing tasks can be listed 4 main methods and instruments. First at all will be done literature review for this theme. In this thesis literature review has a serious role because information from this part will be used as a basis for comparing of companies in the final of the research so can be said that literature review has an influence on final results of the thesis. The second method is an interview and textual analysis of it. Interviews are done in the most comfortable for respondent way and will be analysed in order to get inside information of startup's processes. Then launched survey in google docs. Survey is focused on collecting of statistical data for final analysis. Survey is based on Google Forms application. Final part is statistical analysis of the data that can provide answers for research question and approve or disprove hypothesises.

This thesis contains information about possible way of optimising most of working processes in startups's everyday work that lead to higher competitive position and lower costs for startup during its lifetime. Those facts mean that results of this thesis should be interesting firstly for startup founders - both for those who have already launched startup and for those who want to launch it in future. Secondly this thesis can be interested for cloud service producers, because using information from this thesis they can better understand what tasks and problems should be solved by cloud services in the first place and use this understanding for making their product more suitable for market.

This thesis separated in traditional way for research papers and contain 5 parts except introduction. First part is Literature review and contain basic theoretical information about terms, definitions, descriptions and explanations of main points of thesis. The second part is research statement and it will contain information about detailed research question, hypothesis and justification of chosen methods of research. The third part is methodology and it contains detailed information about each method that is used in research with examples and explorations. The fourth part is description of results and it will contain 2 types of data - firstly collected data after clearing and adaptation. This data will be then analyzed and results of this data will compose second part of this section. Second part contain information of analyzed primary data and this information is used in order to answer research question and research problem. The last part of the thesis is conclusion. Conclusion contain answers for research question and problemб prove or disprove of hypothesis and advices for startup founders and cloud service producers.

1. Literature review

In this part will be overviewed main facts about object and subject of study and described main theoretical research concerning topic of study. Because of the specification on two independent from each other industries, one of which has influence on another and that makes up this research - most of points goes parallelly. All general points that can be referred to both industries will be described in the end of the section. Approximate plan of the section includes next points: cloud technology automatization startup

* Basic information about cloud services. Origins of that type of project, history of development, definitions of terms, biggest players in the market.

* Basic information about startups. History of the industry, features that differ startups from other types of projects, most famous researches about startups.

* Typology of cloud services. Separating of startups in groups based on different characteristics: technical, role, goal and etc.

* Lifecycle of startup. This part contains description of different periods in every startup “life”, characteristics and specialty of each.

* Efficiency in work. Description of efficiency as a phenomenon, fundamental ways of measuring it, explanation of its role in the company.

* How efficiency influences on startups success. Overview of studies that research impact of efficiency on startup's success, if there no specific information about startups, then will be used survey focused on traditional small business success.

1.1 Basic information about cloud services.

Before cloud services appeared in modern view there was a modern computing. The most complex definition and explanation of this term was made by Peter M. Mell and Timothy Grance from National Institute of Standards and Technology in their publication “The NIST Definition of Cloud Computing”. They describe cloud computing as a model enabling comfortable and stable network access with “on-demand” availability to a shared kit of configurable computing resources (different services, servers, networks and etc.). These resources user can rapidly activate and release for its own needs with minimal interaction from provider's side or own managerial resources. This model can be described by 5 main characteristics:

1. On-demand self-service.

A consumer can independently engage computing resources such as server time or data storage without any interaction with providers personal.

2. Broad network access.

Available via Internet. Can be accessed through standard mechanisms that allow to use different client platforms starting with smartphones till the serious computers.

3. Resource pooling.

Provider pool all his resources to serve a bigger number of consumers (with Multi-tenant model). Different types of resources (physical and virtual) are dynamically located and relocated according to consumer demand. It makes the sense of location independency when consumers do not know and do not control where is the exact location of computing resources which he is using. Examples of resources include storage, processing and etc.

4. Rapid elasticity.

Computing resources can rapidly be reserved automatically for operational scaling for consumer's tasks and fastly be realised. From the consumer's point of view available capabilities are looks like unlimited and can be appropriated in any quantity at any time.

5. Measured service.

cloud systems automatically control and optimise resource usage through scaling of different abstract options. Options vary depending of service type. For example: data storage volume computing powers and etc. Resource usage is monitored and can be reported systemically, and that helps for both the provider and consumer of the utilized service to get the most authentic data. (Mell & Grance, 2011)

But the development of cloud services and cloud computing has continued for years. The idea of an "intergalactic computer network" was introduced in the 1960s by JCR Licklider, who was responsible for the development of the network of advanced research agencies (ARPANET) in 1969(Mohamed, A., 2009). Later this "intergalactic computer network" will be called "Internet". His main idea was to make sure that everyone on the planet was connected to each other through computers and could access information from anywhere. an early predecessor of the cloud, which connected geographically disparate computers, creating a loosely coupled network. This in turn led to the development of utilitarian computing, which is closer to what Licklider originally envisioned(Donnelly, C., 2018, March 23).. The cloud has gained popularity as companies have become more aware of its services and usefulness. In 1999, Salesforce has become a popular example of the successful use of cloud computing. They used it to create the idea of using the Internet to deliver software to end users. The program (or application) can be accessed and downloaded by anyone with Internet access. Businesses can purchase software on demand, in a cost-effective manner, from the comfort of the office(Foote, K. D., 2017, June 22). In 2006, Amazon launched Amazon Web Services, which offers online services to other websites or customers. In the same year, Google launched Google Docs services. Google docs was originally based on two separate products: Google Spreadsheets and written. Google has acquired written, which offers tenants the ability to save documents, edit documents and share them to blogging systems. Google Spreadsheets is an online program that allows users to develop, update, and edit spreadsheets, as well as share data online. In 2007, IBM, Google, and several universities joined forces to develop a server farm for research projects that require both fast processors and huge data sets. The University of Washington was the first to register and use the resources provided by IBM and Google. Carnegie Mellon University, Massachusetts Institute of technology, Stanford University, the University of Maryland and the University of California at Berkeley quickly followed suit. Universities immediately realized that computer experiments could be done faster and for less money if IBM and Google supported their research. In 2011, IBM introduced the IBM SmartCloud infrastructure to support Smarter Planet (cultural thinking project). Apple then launched ICloud, which focuses on storing additional personal information (photos, music, videos, etc.). In addition, during this year, Microsoft began advertising the Cloud on television, informing the public about its ability to store photos or videos with easy access. Oracle introduced Oracle Cloud in 2012, offering three business fundamentals: IaaS (infrastructure as a service), PaaS (platform as a service), and SAAS (software as a service). This can be called the beginning of the modern view of cloud services. In parallel, the development of a start-up type of business may follow.

1.2 Basic information about startups.

Creating a startup is a special form of business. According to the well-known serial entrepreneur from Silicon valley Steve Blank, a startup is "an organization created to search for a repeatable and scalable business model." Based on this concept, European Startup Monitor can participate only in some companies with the following functions:

1. Startups younger than 10 years

2. Startups that use (highly) innovative technologies and / or business models

3. Startups that have or seek significant employee growth and / or sales (Kollmann, T., Stцckmann, C., Hensellek, S., & Kensbock, J., 2016).

A startup is a young company that is just beginning to develop. Startups are usually small and are initially funded and managed by multiple founders or a single individual. These companies offer a product or service that is not currently offered elsewhere in the market, or that the founders believe is offered in the worst form.

There are 5 main differences between a startup and a traditional start-up business:

1) Startups typically operate in relatively new and uncertain industries. Or it could be an industry moving from offline to online. One of the biggest problems of startups in uncertain industries is that they have virtually no references or examples.

A start-up business usually works in an industry that is already more or less defined. Advisors, mentors and potential investors are a little easier to identify because usually your industry already has "stars»

2) Startups should by definition be scalable. That's what makes them financially interesting. They usually work on the basis of technology and can repeat the same "trick" in new cities or countries. Startups aren't usually held back by working capital, manufacturing costs, etc. Variable costs don't increase equally with every new product sold. In other words, because of the (conventional) automation and use of technology, if a startup adds another team member, that person could potentially serve 10,000 new customers (or more).

The start-up business is usually not scales. For example, founders "sell" their watches as consultants. Or they sell a product that is subject to serious variable (production) costs. If you produce 1 more product, you will incur additional costs of X euros. Or say you run a gym with a personal workout. If you add 1 employee, he can help 8 people a day. So you can add people and grow and grow and become huge, but that's not the definition of scalability. You always need to add resources before you can become more.

This can be a great success for the founder, but has its limits. Which makes a good bridge to the next point.

3) As a startup, in the beginning you fell hard. Construction technology is expensive and time-consuming. Finding customers can be even more than that.

Start-up business is a separate story. Usually you need to make certain investments before starting your company.

4) As a startup you should experiment. Product, business model, revenue model, customer groups. If I had to write a 40-page business plan every time I made a change to our proposal, I would do it full-time and still not finish it.

Start-up business and its business plan. You've probably spent weeks and weeks writing it, calculating profits, improving your marketing structure, and searching for sales channels. That's normal. Because chances are you have specific examples from competitors or even templates or proven formulas from your franchise. You may have to make changes to your plan or offer in the future, but they won't be weekly or even monthly

5) Startups are inherently risky. For all the above reasons. They work in uncertain industries, they have to experiment constantly, they bring little profit and take years to start making profits. Thus, startups are financed based on future potential and scalability.

Start-up business is most often suitable for Bank financing or more traditional investment institutions. There are proven examples of successful businesses, investments are often lower than for a startup, and short-term returns are more likely. With a reasonable plan, it will be easier for a starting business to attract capital. If the startup company is already going a little further and making a profit, investors will look at the books and apply some more traditional valuation mechanisms and look at the books of past years(Maastricht University., 2017, June 22).

1.3 Typology of cloud services.

There are different dimensions to classify cloud computing, two commonly used categories: service boundary and service type.

* In terms of service boundary, cloud computing can be classified as public cloud, private cloud and hybrid cloud. Public cloud refers to services provided to third parties. Businesses build and operate a private cloud for themselves. The Hy-brid cloud distributes resources between the public cloud and the private cloud through a secure network. Virtual Private Cloud (VPC) services released by Google and Amazon are examples of a hybrid cloud.

* In terms of service type, cloud computing can be classified as infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS).If the startup company is already going a little further and making a profit, investors will look at the books and apply some more traditional valuation mechanisms and look at the books of past years(Qian, L., Luo, Z., Du, Y., & Guo, L., 2009, December).

Cloud services are based on the cloud computing system and can be divided to 3 main (Mell & Grance, 2011):

1. Software as a Service (SaaS)

Main idea is to provide to consumer opportunity to use provider's application existing on a cloud infrastructure. In other words client has no control of this cloud infrastructure including network, servers, operating systems and etc. and do not need to serve it, but in any moment customer can access application from various devices even from web-browser.

2. Platform as a Service (PaaS).

Consumer has an opportunity of deploying onto the cloud infrastructure own-created or based on any programming language, libraries, services and tools that is supported by provider. In this case consumer is also has no control over infrastructure, but can configure work of application and may be can set application-hosting environment.

3. Infrastructure as a Service (IaaS).

This type of service provide an opportunity to store, launch, support any type of software, which can include operating systems and applications. Customer has no control over infrastructure also, but is able to control operating system, storage and application(Mell, P., & Grance, T., 2011).

Another way to differentiate a cloud service is based on the service architecture. There are 3 main types.

Amazon cloud computing is based on server virtualization technology. Amazon released Xen Elastic Compute Cloud (EC2), an object storage service (S3), and a structural data storage service (SimpleDB) during 2006-2007 Called Amazon Web Service (AWS) . On demand and at a lower cost, AWS is becoming a pioneer in infrastructure as a service provider (IaaS).

Google's style is based on a special sandbox. Google has published several research papers from 2003 to 2006 that describe a kind of cloud computing Platform as Service (PaaS). The platform, called Google App Engine (GAE), was released for public access as a service in 2008.

Microsoft Azure was released in October 2008 and uses Windows Az-ure Hypervisor (WAH) as the underlying cloud infrastructure and .NET as the application container. Azure also offers services such as BLOB object storage and SQL service(Qian, L., Luo, Z., Du, Y., & Guo, L., 2009, December).

And the last typology is based on tasks that solve service. Originally this part can be interpreted as an extended version of service typology that has already been mentioned earlier(SaaS, PaaS, IaaS), but if these three types can be named traditional and basic, all the other appears later and provide wider and different range of applications so was decided to form them into separate list:

C. Infrastructure as a service (IaaS) IaaSdelivers hardware resources such as processor, disk space, or network components as a service. These resources are typically provided by the virtualization provider as a virtualization platform and can be accessed by the client over the Internet. The client has full control over the virtualized platform and is not responsible for managing the underlying infrastructure.

D. Storage as a service Storage as a service (STaaS) is a business model in which a large service provider leases space in its storage infrastructure on a subscription basis. Economies of scale in service provider infrastructure allow them to provide storage much more cost-effectively than most individuals or corporations that can provide their own storage, given the total cost of ownership. Storage as a service is often used for off-site backup tasks. Criticism of storage as a service indicates the large amount of network bandwidth required to store data using an Internet service.

E. Security as a service Security as a service (SECaaS) is a business model in which a major service provider integrates its security services into an enterprise infrastructure on a subscription basis at a lower cost than most individuals or corporations can provide on their own when the total cost of ownership is considered. These security services often include authentication, antivirus protection, malware / spyware protection, intrusion detection, and security event management.

F. Data as a service Data as a service, or DaaS, is the cousin of software as a service. Like all members of the as a service (aaS) family, DaaS is based on the concept that the product, in this case the data, can be provided to the user upon request, regardless of the geographical or organizational separation of the supplier and the consumer. In addition, the advent of service-oriented architecture (SOA) has made the platform on which the data is located also irrelevant. This development has enabled the recent emergence of a relatively new Daas concept. The data provided as a service was primarily used in web-based hybrid applications at first, but is now increasingly used for both commercial purposes and less frequently in organizations such as the UN.

G. Test environment as a service Test environment as a service (TEaaS), sometimes referred to as an "on-demand test environment", is a delivery model of a test environment in which the software and associated data are hosted centrally (usually in ) and are generally available to users using a thin client, typically using a web browser over the Internet.

H. Backend as a service Backend as a service (BaaS), also known as "mobile backend as a service" (MBaaS), is a model that allows web and mobile app developers to link their apps to backend cloud storage, and provides features such as user management, push notifications, and integration with social media services. These services are provided using custom software development kits (SDKs) and application programming interfaces (APIs). BaaS is a relatively recent development in cloud computing, with most Baas startups starting in 2011 or later. The global Baas market in 2012 was estimated at 216.5 million dollars(Sareen, P., 2013).

1.4 Lifecycle of startup

1. Initial preparation stage: at this very early stage, the entrepreneur himself initiates a series of activities aimed at transforming his idea into a profitable business. However, he / she considers a higher level of risk or even uncertainty, continues to work on a new venture idea, creates a team, uses personal funds and asks family members and friends to invest in an idea. Bootstrapping, sometimes defined as highly creative ways of acquiring resource utilization without borrowing (Freear et al., 2002), is considered one of the areas of entrepreneurship research that needs to be addressed most (Ebben & Johnson, 2006). The purpose of this stage is to position the company for growth, demonstrating the feasibility of the product, money management capabilities, team building and management, as well as customer acceptance (Brush et. El. 2006,). Moreover, angel investors are more likely to invest at this stage. In general, as Harrison et al. (2004) state: “Bootstrapping is a lifestyle in entrepreneurial companies.” This argument shows why most start-up theories are borrowed from entrepreneurship theories (see start-up-oriented entrepreneurship theories).

2. Seed stage: after the initial loading stage, the founder enters a new stage, which is the seed stage1. This stage is characterized by teamwork, development of prototypes, market entry, enterprise valuation, search for support mechanisms, such as accelerators and incubators, and medium investment for growth of a startup. Honestly, for most startups at the seed stage, this is a mess and is considered as very uncertain (Salamzade 2015). The initial stage is characterized by the initial capital that is used to create the product and / or service (Manchanda & Muralidharan, 2014). Thus, the founder is looking for support mechanisms, such as boosters, incubators, small business development centers, and incubators to speed up the process. At this stage, many startups fail. Since they could not find support mechanisms and, at best, they would turn to low-profit companies with a low success rate. On the other hand, those who manage to get support will be more likely to become profitable companies. It goes without saying that the evaluation is usually performed at the end of this stage.

3. At the stage of creation: the stage of creation occurs when a company sells its products to the market and hires its first employees (Salamzade, 2015). Some scholars believe that entrepreneurship stops when the creation phase ends (Ogorelc, 1999). This confirms the argument that most of the theories that embrace startups are borrowed from theories of entrepreneurship, and not from theories of management and organization (see theories of entrepreneurship oriented to startups). At the end of this stage, an organization / firm is formed and corporate financing is considered as the main choice for financing the firm. Venture capital could facilitate the stage of creation, financing the company. (Salamzadeh, A., & Kawamorita Kesim, H., 2015)

1.5 Efficiency in work

Efficiency: the relationship between effort (or resources) and results or outcomes. It is measured in terms of resources used or costs per unit of output or result. The concept of using resources, also with the lowest cost, which is associated with maximizing the results at the lowest cost or using minimal resources(Pennypacker, J. S., 2005)

Although efficiency is also defined in terms of comparing the two components (inputs and outputs), the highest level of performance for each input level is recognized as an effective situation. Coelli, RAO and Battese (1998) also suggest that efficiency reflects the firm's ability to get the most out of a given set of resources. If a firm gets the most out of a set of resources, it is considered an efficient firm (Rogers 1998).

Efficiency consists of two main components; technical efficiency and resource allocation efficiency (Coelli, Rao et al. 1998). Generally, the term efficiency refers to technical efficiency. As discussed in the previous section, technical efficiency arises when a firm gets the most out of a set of resources. Distributive efficiency arises when a firm chooses the optimal combination of resources, taking into account the level of prices and production technology (Coelli, Rao et al. 1998; Rogers 1998). When a firm fails to select the optimal combination of resources at a given price level, it is said to be inefficient in terms of distribution, although it may be technically efficient (Coelli, Rao et al. 1998). Technical efficiency and allocative efficiency combine to provide overall efficiency (Coelli, Rao et al. 1998). When a firm achieves the maximum return on a certain level of cost while using the lowest cost, it is considered an overall efficient firm(Jayamaha, A., & Mula, J. M., 2011).

To make this thesis more practical in measuring efficiency, it was decided to rely on practical articles from blogs and trainings on business efficiency instead of scientific and theoretical articles. This was done because these blogs and articles may contain some tips and life hacks that greatly simplify the process of evaluating the effectiveness of the company. The main reason for this decision is that many companies do not have the conditions for a sterling audit, and respondents to my survey or interview should easily assess their performance and the effectiveness of internal processes on their own.

There are many metrics that can be calculated if an employee's workload is broken down into tasks. The following metrics are among the most important to measure the overall performance of your business:

1. Average time to complete tasks in a workflow per worker or overall

2. Number of tasks assigned to each employee

3. Cost of the task per employee

4. The response time for a task(Lopez, G., 2018, March 20)

To stay objective and better develop the issue, a number of different metrics from different resources will be listed here. So the other method is based on KPI. KPI is an indicator that evaluates how a company implements its strategic vision. The term "strategic vision" refers to how the Interactive1 strategy is integrated into the company's strategy as a whole(Warren, J., 2011).

Average task execution time

If you want to look at the efficiency of a project in a more practical than financial way, this KPI is ideal.

Average task execution speed = total task execution time (within a specified time period) / number of operations performed.

It will inform you about the effectiveness of your team and help you understand how long it will take to perform various aspects of the project.

Measuring productivity quantitatively

The quantitative method measures productivity by the number of parts or products that employees produce in a given period of time, such as an hour, a day, or a month.

This method works very well for small businesses, but even if you manage large groups, this kind of performance measurement is simple and time-saving.

Performance can be quickly calculated using productivity software or based on spreadsheets showing the number of products an employee produces or participates in a given time period. These numbers are then averaged to show an increase or decrease in performance over time.

Output can be measured either by the volume or quantity of products created or by the financial value of the product or service.

First, create a baseline - the average number of working hours, days, or weeks required to create this part or product under normal working conditions, when the employee is working at the optimal level. Each worker on the production line is then compared to this ideal (but realistic) level of productivity.

This type of measurement should also take into account the amount of time employees spend on activities such as on-the-job training, time spent waiting for materials to arrive or repairing broken equipment, and other factors beyond their control.

Finally, there are 3 different ways to measure performance from different resources and theories. This information is necessary for analysis, integration and processing into one suitable concept. This collected concept of performance measurement becomes the basis for the study.

1.6 How efficiency influences on startups success

This part of literature review contains information about existing correlation between project efficiency and success of the project. Should be mentioned that data and findings that are represented here do not based on startups because there are no adequate researches on this theme that are fucosed on startups, so it can be established as a gap in knowledge. Generally, as the basis is taken research “The Relationship Between Project Success and Project Efficiency” of Pedro Serrador and Rodney Turner( Serrador, P., & Turner, R., 2015).. In project boundaries were collected data about 1368 different projects from 859 persons that have to fill a questionnaire. Each person have to answer questions about 2 projects - one more successful and another less successful in their meaning. Questionnaire contains 3 sections: Overall project success rating; Project success as perceived by four groups of stakeholders: the sponsor, the project team, the client, and the end users; Performance against the three components of project efficiency: time, cost. Also by this survey was collected additional demographic data about the nature of the project. Projects that got part in the survey have to be surely ended in order of objectiveness of perceptions of result. Survey was based on different system of scales, respondents were found via different ways and from different countries to avoid mono-source bias. Additionally can be added that in order to make this research on a combination of the success dimensions defined by Mьller and Turner (2007b) and Shenhar and Dvir (2007)For simplifying of further analyses the success measures were grouped into three measures of success. These were the measures of project success used throughout the analysis:

Efficiency measure = mean of the following three responses as a sum-mated scale:

1. Project success: meeting timeline goals

2. Project success: meeting budget goals

3. Project success: meeting scope and requirements goals

As project success is best judged by the stakeholders, especially the primary sponsor (Turner & Zolin, 2012), we will use the following project success mea-sure:

Project Success measure = mean of the following four responses as a sum-mated scale:

1. Project success rating: sponsor assess-ment

2. Project success rating: project team assessment

3. Project success rating: client assess-ment

4. Project success rating: end-user assess-ment

In addition, we will compare these measures to the single overall project success rating given by respondents. Although these measures were based on the findings of previous researchers, a confirmatory factor analysis was also completed

And as a conclusion of this research was can be declared that project efficiency is correlated with overall project success. Through a survey of 1,386 projects we found that project efficiency is 60% cor-related with project success; this falls to 51% if efficiency is defined as time and budget only. For my research this part has the biggest meaning, because it justify that factors that can influence efficiency of the project can indirectly effect on project success(Serrador, P., & Turner, R., 2015)

In conclusion of this section of research should be said that were successfully reviewed all basic phenomena connected with the main topic and basic list of terminology that is needed for better operating in boundaries of the theme of the thesis. Some parts of this literature review contain information that will be used in next parts as an example or basis for actions. One more role of this literature review is confirmation of assumption and concepts that have direct impact on objectivity and authenticity of thesis, especially important is confirmation of existing theories that helps to narrow of research area of study and pay more attention to other points of research. All these facts can be regarded as confirmation of utility of prepared materials. As a results can be taken: explanations of main terms and constructs of thesis, measures of efficiency that will be used in practical part, narrowing of research area with confirmation of connection between success of project and its efficiency, understanding of main types and characteristics of cloud services, marking of problematic areas of startups.

2. Statement of the research question

After the literature review can be claimed that startup is unique type of business project with specific conditions and characteristics. It leads to understanding that general researches that are based on other types of businesses cannot be used as a source of reliable information in questions concerning startups. In addition, during literature review became clear that on this moment number of researches that explore precisely startups and startup processes is not enough for deep understanding of all aspects of this type of projects. This lack of researches and authentic information about startups is also actual for question of cloud services impact on the work of project, because if the positive influence of cloud services on traditional business is claimed - it cannot be said concerning startups. By the reason of such lack of information was formulated a main theme of this thesis - research of modern cloud services and how does usage of these services influence on of completing of practical tasks of startups and does it have an impact on total efficiency of startup? Taking in attention all the facts that are mentioned earlier can be composed a research gap, which is sounds like “lack of researches and information about influence that have cloud services on startup efficiency in completing of regular tasks” and main purpose of this research is to fill this gap. In other words filling of this gap can be explained as to find out and confirm an existence of correlation between usage of cloud services and startup's activity efficiency rates and this wording can be set as a main goal of research. In order to reach goal of this thesis should be found and based an answer for research question that can be formulated as “how automatization with cloud services influences on efficiency of completing of startup's practical tasks and cases?”. Answering for this question is separated in 5 coherent parts that have already been listed in introduction part and described in details in methodology part. In literature review was collected information about main concepts, constructions and features, but by the reason of lack of researches on this theme in same conditions results of this thesis cannot been forecasted with precision. So researches from adjacent spheres and already researched characteristics of main definitions allow to formulate a number of hypothesizes, verification of which can help on reaching of research goal. First at all should be set a null hypothesis of this thesis. As a null hypothesis can be taken an assumption that cloud services that are used in specific startup do not influences on efficiency of completing of regular tasks in startup work. To sum up and shorten description of null hypothesis can be used formulation that sounds like “there are no any type of correlation between usage of cloud services in conditions of startup project and efficiency of completing of basic everyday tasks in startup work”. But in the same moment should be formulated alternative hypothesis that asserts an idea that cloud services that are used in specific startup is a significant factor that influences on efficiency of completing of regular tasks in startup work. And also, this description of alternative hypothesis can be shorten with formulation which is sounds like “there are clear correlation between usage of cloud services in conditions of startup project and efficiency of completing of basic everyday tasks in startup work”. For more accurate and clarifying answer for research question and reaching a research goal there are also can be formed one more hypothesis in addition to already existing ones. This hypothesis in short statement sounds like “correlation between usage of cloud services in conditions of startup project and efficiency of completing of basic everyday tasks in startup work is positive”. And the last hypothesis that can be useful in this research has a next formulation: in case of correlation between cloud services usage and efficiency of completing of basic everyday tasks in startup work will be also correct statement that more active usage of cloud services leads to more efficient way of completing of regular tasks in startup. To sum up all the above all the hypothesizes are listed consistently.

1. There is clear correlation between usage of cloud services in conditions of startup project and efficiency of completing of basic everyday tasks in startup work

2. Correlation between usage of cloud services in conditions of startup project and efficiency of completing of basic everyday tasks in startup work is positive

3. In case of correlation between cloud services usage and efficiency of completing of basic everyday tasks in startup work will be also correct statement that more active usage of cloud services leads to more efficient way of completing of regular tasks in startup.

The very first hypothesis was tested using Mann-Whitney statistical test for 2 independent samples, that allows to check if the usage of cloud services provides statistically significant difference in contribution of efficiency indexes. Descriptive part of this test in pair with correlation matrix of Spearman that is constructed with two-tail criteria that shows level of correlation and level of significance, which can be used for estimation direction of influence and its significance was used for testing of the second hypothesis.

For the third hypothesis will be used Kruskal Wallis statistical test for K-independent samples for significance of differences in indicators of efficiency between groups of cloud services usage level.

More information about hypothesis testing and methods of goal reaching are presented in next section of the thesis.

3. Methodology

In the beginning of this section should be firstly reminded basic concepts of this thesis. The goal of this research paper is to find out and confirm an existence of connections between usage of cloud services and startup's activity efficiency and that this connection has a positive influence on startup's success. This goal is closely connected with research question of the work, because achievement of the goal can be used as an answer for the research question. Research question sounds like: how automatization with cloud services influences on efficiency of completing of startup's practical tasks and cases?

In order to get answers that were mentioned above and to reach research goals were set 5 main tasks:

1. Collect and analyse theoretical foundations about cloud services, startups and other adjacent topics. This will be done for better understanding of way of interaction of different businesses and cloud services and prepare guide for next stage of the work/

2. Interview with people that are involved in start-up industry. In this interview will be gotten inside information about cloud services usage in modern start-ups and subjective opinion about them.

3. Exploration of efficiency phenomenon and preparing of theoretical basis for accurate evaluating and subsequent comparing of this index in different startups considering cloud services impact.

4. Launching a survey that that will be based on information from theoretical part and on the interviews and that will help to collect statistics about cloud services in start-ups and information about actual efficiency in the company. This statistic will become a basis for next step.

5. Comparing of efficiency of start-ups considering cloud services impact on processes inside company with different level of cloud-services usage, basing on the information that were set in stage 3.

Further in this section will be overviewed in details completing of these tasks, features of sample and methods.

In the very beginning should be clarified basic frames of sample in this study. In previous parts of this thesis was mentioned that because of specification of the thesis all the theoretical data should be separated in two parallel streams - one related to cloud services and another related to startup industry. In this section this separation is also actual. It means that in this thesis two different frames for sample are set - one for the startups and another for cloud services. Should be mentioned that in this part primary meaning has startup sample - it is taken as the basis, because startup is an object of this work and it is more correct to set a sample of startups that are interesting for the thesis and after it to set cloud services that have impact on these startups. On the one hand there are limitations for startups and the first limitations is startup's specification/orientation - IT and technical oriented startups are in the priority, because those types of startups usually use more modern technologies and better understand all the advantages of modern technologies usage. It leads to idea that members of technically oriented startups are better understand impact that has cloud services on their project. So possibility to use wide range of technologies in work automatically increase probability of appearance of cloud services, that is the most important factor. The second limitation is not so strict as the first one, but its implementation is quite useful - this limitation relates to stage of development of startup. “Life” of each startup can be divided in 3 parts (Salamzadeh, A., & Kawamorita Kesim, H., 2015), as it was mentioned in theoretical foundation part, and in case of this thesis the most important and most interesting part is the first one. In this part of lifecycle startup has the biggest rate of failure (Mansfield, M.,2019, March 28)., it has the biggest number of problem and tasks related to optimizing and setting working process. Additional tasks as partners finding, marketing and etc. do not allow to spend enough time on basic processes in company. All these factors provide a good background for cloud service using as an instrument of optimizing and reliefing of workdays. On later stages of lifecycle of startups cloud services become less influencing, because of establishing of all working processes in project. That was 2 main limitations for startups in this thesis. On the other hand, there are limitations for cloud services, but there are no preliminary limitations because sample of cloud services consists of applications and other offers that are got during interviews and survey. So, can be said that sample of cloud services has a secondary role. Should be added that mainly this thesis is focused on types of services, but not the specific single application. It is made in order to avoid meaningless differences in interview answers or statistics, when respondent use identical service but from the different producers. But in case if the principal choice of service producer will be underlined and justified because of great difference in service quality or dramatically different functional - can be made a list of exact applications with comments and recommendations to each of them. Finally, can be added that as a main base of startups for this research become a list of winners of GoTech Exhibition 2018( GoTech.,2018).. More details about this exhibition contain description of interview part of the study and can be read below.

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