ECON1555 Business Data Analytics Online Tutoring

Background of research

The Australian Government (Department of Industry, Innovation and Science, 2018) emphasise that Australia’s technology future requires Australian businesses to develop capability in several areas including data and digital skills and accessing Australia’s digital infrastructure including Information Technology such as the internet.

Data is considered valuable for businesses because it enables better, more connected services, improved policies and decision making, and the development of new technologies products and services. “Collecting and analysing data is not a new thing, but the tools businesses and consumers use to quickly interact with data from multiple sources are changing rapidly. Seven out of the top 10 companies in the world rely on the data they collect to deliver services and create value” (Australian Bureau of Standard Reports 2019).

In the last few years, through the use of Machine Learning, Artificial Intelligence, and the new growth in the techniques and capabilities within data science, data has become easier to harvest and analyse. This has also increased the incentive for collection of data and led to a more data-driven approach towards business, in the recent years.

All Australian businesses regardless of size and sector they are in need to use data and Information Technology. This is particularly important for SMEs.  Data from the Australian Bureau of Statistics indicates that SMEs in Australia account for most businesses, business employment and value-added contribution to the economy.

Australia also needs to facilitate the start-up and growth of ‘innovative’ SMEs which are generally characterised as having high growth, possessing innovative ideas, and bringing new ideas to the market through commercialisation. They are generally aware of the latest technology trends, are digitally engaged, use the internet for business purposes, and have knowledge and capital resources.

Data usage and digital engagement also appears to strongly correlate with innovative SMEs. Deloitte in a survey of 500 small businesses in Australia measured their level of digital engagement, such as having a website with business information or the use of digital marketing to attract customers. Small businesses making full use of the internet with high digital engagement enjoy better business outcomes, have better growth prospects, more diversified sources of revenue and a bigger customer base. The report’s conclusion is that Australian small businesses must consider online strategies if they are to navigate the digital disruption of coming years (Deloitte 2013).

 

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Objectives of the research

The main objectives of this research include identifying and investigating the presence of different Australian companies and businesses on the internet landscape. The findings of the research should help in identifying the internet and web access that different organizations have and how it affects different functions including the level of innovation. Furthermore, the research findings will focus on looking at the level of internet connectivity, and social media web presence according to the type of industry, level of innovation and size of the organization. The size of the business will also help in identifying the presence of Small and Medium Enterprises on the internet and social media landscape, specifically, giving the client a better idea of how to go about further data collection and research.

 

Research Questions

The main research questions to be answered are the following:

1. What is the current situation for Australian businesses’ online presence, including large businesses and SMEs?
2. What is the current situation for Australian SME’s online presence?

Assessing the situation will include evaluating the amount of business being done online by different size of organizations in Australia. This can be further divided into how much business is being done online by these organization with the suppliers and what proportion of business is being down online with customers. Similarly, the type of industry that a company operates in will also have a relationship with how much of the business is being conducted online, this will tell us about what sectors are benefitting from and using the internet to their advantage, and what sectors can be improved in regards to access to internet.

3. What are the strengths of Australian businesses about online presence for all businesses as well as specifically SMEs?

Finding the answer to this question will help in identifying the strengths that are presence in Australian businesses already and what could be the reason behind these organizations accruing such advantages, while others lag behind. This could offer valuable insight into the steps that different organizations can take to improve their position in the technology landscape.

4. What are areas for improvement for Australian businesses about online presence for all businesses as well as specifically for SMEs?

The common factors in the industries which lack internet access or have not been able to make the most of the internet access, will be identified through the use of data. Through the survey of relevant literature and relevant theoretical works, the reasons behind the lack of optimal use of internet will be identified. Using companies from other countries and Australia, which have been able to increase their internet access and improve their performance, as examples can help in identifying the steps that need to be taken for improvement in internet access.

Methodology

The methodology that will be employed in this report for carrying out research would be quantitative analysis. The methodology is suitable for answering the researching presented in the section above for numerous reasons. Firstly, the methodology is not complicated and helps in drawing out and making sense of relations between different variables that need to be investigated (Kaplan 2004). Secondly, the methodology can be employed in the context of Australia for answering the questions asked above because there is ample amount of relevant evidence and verifiable data available (Kaplan 2004). Due to constraints of time, finance and the limited scope of research, conducting primary research and collecting new data is not viable option, thus the data that is already available shall be used. Lastly, not much qualitative research (of high quality) is available on the use of technology in Australian businesses, and this makes conducting qualitative research, a difficult option to explore (Ratner 2002).

The data set that will be used for the analysis will be acquired from Australian Bureau of Statistics’ website. The dataset is titled Business Characteristics Survey (BCS) is done once in two years, the last survey was conducted in 2018-19 and this survey, from 2018-19 is being used for analysis in this report. BCS is mainly concerned with estimating the use of information technology in businesses and gauging the level of innovation (and categorizing firms according to level of innovation). The data is available free of cost on the website of the Australian Bureau of Statistics. The data is reliable and has well-documented and widely accepted careful data collection procedures and techniques. Specifically, the data collected about the business use of information technology will be used for analysis.

 

Methodology of data collection

The BCS data is collected through an extensive survey which is conducted over a random sample of approximately 7000 businesses. These surveys are filled using online forms or questionnaires are mailed-out to specific businesses, to ensure the participation of businesses that do not have access to internet. The facts regarding the businesses are up till 30 June 2019, and annual financial data is from the financial year that ends on 30 September 2019.

 

Limitations

The limitations of quantitative research and data should also be kept in mind while making recommendations and drawing conclusions. These limitations include the lack of nuance in the data; nuance is often not captured in the quantitative data as it is designed for convenient collection and data analysis (Kaplan 2004). Thus, recommendations should be made in the light of findings but with necessary cautions.

Interpretation of relevant terms

Before moving on with the analysis of the data set, it is important to clarify the usage of certain terms in the report. The term ‘innovation’ is used to mean the introduction of a new good or service, or a drastic change in a particular good or service, through a change in the manufacturing or managerial process. An organisation that is involved in innovative activity is also classified as an innovative organization – an innovative activity is an activity that is self-classified by the business as an activity that aims to bring innovation. Innovation is further divided in sub-categories along different metrics; first one is the measure of business innovation, which classifies businesses as either innovation-active businesses or non-innovation-active businesses. Innovation-active businesses are those which have introduced an innovation in the reference period, which non-innovation-active businesses are those which have not introduced such an innovation. There are two types of innovation within an organization: goods or services innovation and process innovation. As the name implies, good or services innovations are innovations in a good or service, that replace or alter a product or (the delivery of a) service. Process innovations are those which aim to change a business processes that may or may not change the product; these include changes in the marketing, costing, or production strategies and processes (Devanport 1993).

Web presence of a company is determined by looking at whether a company has its own website, or if it has a presence on a website hosted by another organization, however, the business should have sufficient control over content related to products or services on the host website, e.g. if an organization has its products for sale on Amazon, it is considered to have presence on web. Social media presence is included as a distinct variable, however, a business having social media presence is considered to have online presence as well (Chakrabarti & Scholnick 2002).

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Analysis of data sets

The dataset presents information on various aspects of the businesses in focus, these aspects will be discussed one by one, where different characteristics of the businesses will be presented in different combinations, to make better sense of the data. Graphs will be used for better presentation and analysis of the data and regression analysis will also be done where needed.

 

Innovation, business size and internet income

In the two graphs below, business size and internet income as a proportion of total income earned from the sale goods and services are shown below, for innovative and non-innovative businesses. It is important to remember that income here means revenue, not net income (the internet proportion of which might be higher, as the cost of selling products and services on internet is usually lower than the cost of selling products and services in physical buildings).

Almost one fourth of all sorts of businesses regardless of size and whether they are innovative or not, have less than one percent of their income coming through internet. The only exception in this regard are the non-innovative businesses employing 0-4 people – only approximately 17% of which have less than 1% of their income coming from the internet. It is more useful to look at the percentage of businesses that are earning more than 10% of their income from the internet. This data shows that almost 70% of the non-innovative businesses employing 0-4 people, earn more than 10% of their income through internet, followed by innovative businesses employing 0-4 people, 64.1% of  which earn more than 10% of their income from the internet. On the other hand, innovative-active businesses, that employ between 20-199 people and more than 199 people have the lowest percentage of business that earn more than 50% of their income from the internet, at 55.2% and 55.6%, respectively. Around 68% of all the innovation-active businesses earn less than 50% of their income from the internet, while 65% of the non-innovation-active business earn less than 50% of their income from the internet.

 

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