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Operational Data

Data is a precious thing and will last longer than the systems themselves." 

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Operational Data

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Data is a precious thing and will last longer than the systems themselves."

- Tim Berners-Lee, Inventor of the World Wide Web

How is data benefiting the operations of a company? What is it exactly and what are its types? How is it calculated? How is it changing the way companies compete and operate? These are some of the important questions to consider. So, let's find out.

Operational data is a form of strategic data that captures information on the internal functions and processes of a business.

Types of operational data

There are three types of operational data:

  1. Business operational data: is data that describes organizational processes and user experience.

  2. IT operational data: is data that is linked to technology and digital services which facilitate managers in looking at the insights of their business.

  3. Integrated business-IT operational data: this is a mixture of both business and IT operational data. This type of data offers insights and assists in making business decisions about where to invest the organization's resources.

Transactional vs. operational data

Transactional data is data that is captured from business-related transactions and has the potential to explain certain events.

An organization has a huge amount of transactional data. Some typical activities that produce transactional data are purchasing products from suppliers, sale of products, location of sale, delivery of items to customer sites, recruitment of employees, etc. hence, transactional data is produced frequently.

The knowledge and understanding of these types of operational data can improve operations and assist in the identification of risks. Thus, in order to make full use of operational data, it is essential to make sure that the data is reliable and of the best quality.

Data-driven business operational processes

When a business implements a data-driven approach, it means that it makes strategic decisions on the basis of data analysis and its interpretation. This approach allows businesses to assess and systematise their data with the aim to better serve their customers. By utilising data to direct its actions, a business can customise its relationships with its customers in order to have an approach that is more customer-centric.

For the success of data-driven operations, the organization will require data. In particular, it will require a wide range of main performance indicators.

Performance indicators are used to measure and evaluate how successful a business is at achieving its goals.

For example, recently, warehousing businesses are escalating their investment funds for automation and the management of data. Innovations based on data have an important effect on the operational strategy of the business.

Data modifies the warehouses from within. The data generated by sensors, machinery, robots, etc. have the capability to enhance the business's operations strategy due to the useful insights they provide to management.

These data-driven operational strategies which improve the efficiency of internal business processes may enable an increase in the financial performance of the business.

Calculation of operations data

Now let's take a look at some examples of important operations data that businesses should take into consideration.

laboratory productivity

Labour productivity is a measure of the output per employee in a certain time period. It is calculated as:

Labor Productivity =Output per periodNumber of employees working during the period

If 10 workers produce 400 units of output in a week, then labour productivity is 40 units per employee/week (400 ÷ 10 = 40).

The rise in labour productivity can benefit an organisation by allowing it to:

  • Boost output without changing costs. With the example mentioned above, if labour productivity per week rises from 40 units/worker to 50 units/worker, then the 10 workers could boost total production from 400 units/week to 500 units (10x50) per week.

  • Lower costs without changing output. Based on the above rise in labour productivity, the organization could have less workforce and still produce 400 units per week. With labour productivity of 50 units per week, only 8 workers will be needed to achieve 400 units of output.

The rise in labour productivity can be obtained in different ways. Some of the examples are as follows:

  • Introduction of new technology that will accelerate the production process.

  • Adjusting the production system so that it works more efficiently.

  • Recruitment of new workers with higher skills, experience, and qualifications.

  • Offering training and motivation to the workers.

While enhancements to labour productivity are attractive, an organization should be careful due to the following reasons:

  • Costs associated with boosting labour productivity: the above-mentioned ways incur additional expenditure, so the organization should only apply them if the enhanced labour productivity produces sufficient revenue to pay for the modifications.

  • Conflict with other objectives: if the workers focus only on increasing output other operational issues might be left unaddressed. For example, the quality of production.

Unit costs (average costs)

Unit costs can be calculated with the following formula:

Unit Cost = Total costUnits of output

The unit cost is also called the average cost.

If an organisation produces 150 units of output at a total cost of £6000, then the unit cost is £40 (6000 ÷ 150 = 40).

Figure 1. Monthly costs and output of a newspaper producer

Units of output (000s)

Fixed costs (£000s)

Total variable costs (£000)

Total costs (£000s)

Unit cost

0

20

0

20

-

10

20

10

30

3

20

20

20

40

2

30

20

30

50

1.67

40

20

40

60

1.50

50*

20

50

70

1.40

*Suppose that 50,000 units are the capacity

In this example, the highest efficiency level of output is 50,000 as this is the output at which the unit cost is the lowest (£ 1.40 per unit).

Figure 2. The unit cost of four organizations

units of output

Fixed cost (£)

Total variable costs (£)

Total cost (£)

Unit cost

(£)

Company A

30

100

150

250

8.33

Company B

60

200

250

450

7.50

Company C

100

400

500

900

9.00

Company D

130

500

625

1125

8.65

In this example, the most efficient company is B. In this company, the unit costs are £7.50/unit, the lowest out of all four companies. Whereas the least efficient company is C, as the unit costs are £9/unit, the highest out of all companies.

Capacity

Capacity is the maximum amount a business can produce in a certain period with its available resources.

The ultimate capacity can depend on various factors:

  • The level of demand for the product

  • Flexibility in production

  • Seasonality of the output and demand

  • Opportunities for outsourced production

Capacity utilization

Capacity utilization measures the level to which the maximum potential output is being reached.

Capacity Utilization =Actual OutputMaximum Possible Output

Capacity utilization can be measured on a daily, weekly, monthly, etc basis.

An organization is capable of producing 4000 units, however, currently, it is only producing 2500 units. Therefore, it is working at 62.5% capacity.

Capacity Utilization = 2500 ÷ 4000 = 0.625 = 62.5%

The connection between capacity utilization and other operational targets

Even though capacity utilization in itself is a target, it is essential as it has an effect on other operational targets.

Capacity utilization and labour productivity: in the case of low-capacity utilization, a lot of machinery will not be employed productively in the business. This will result in less work done by the workers as they rely on machinery. Therefore, output per worker will decrease and labour productivity will also decrease. For more flexibility, the number of workers can be reduced if production levels decrease.

Capacity utilization and unit cost: the greater the level of capacity utilization, the more effectively the company is using its resources. It is important to note, however, that a company will have fixed costs regardless of its level of output.

Big data changing the way businesses compete and operate

Big data is defined as a dynamic, big and distinct volume of data generated by people, tools, and machines. It needs modern and innovative technologies to gather, host and actively process the huge amount of data collected to generate real-time insights for the organisation that may link to customers, performance, risk, productivity, and improved value for shareholders.

Big Data has primarily changed the way companies compete and function. Companies that invest in and effectively generate value from their data will have a definite benefit over their rivals. A performance gap will constantly increase as more significant data is produced. Evolving technologies and digital pathways provide better mechanisms for acquisition and delivery. Below are some of the ways big data has changed the way businesses operate:

Improved business intelligence

Tools like business intelligence were developed to assist in analyzing the company. Business intelligence and big data work together when it comes to managing operations. The bigger the reach of BI, the more improved the insights for the company are.

Improved target marketing

Targeted marketing has supported companies in accomplishing their long-term objectives with great outcomes. Due to increased accuracy, resulting from Big Data, companies are able to fulfil the demands of their customers and create marketing strategies more efficiently.

Satisfied customers

Big Data helps anticipate customer needs in advance and works accordingly to improve customer service and eventually customer satisfaction.

Operations Data - Key takeaways

  • Operational data is a form of strategic data that captures information on the internal functions and processes of a business.
  • Different types of operational data include business operational data, IT operational data and Integrated business-IT operational data.
  • Implementation of a data-driven approach implies that the business makes strategic decisions on the basis of data analysis and its interpretation.
  • For the success of the data-driven operations, the organization will require a lot of data.
  • Data-driven operations will require a wide range of performance indicators.
  • Transactional data is the data that explains business events.
  • Labour productivity is a measure of the output per employee in a certain time period.
  • The ultimate capacity depends on factors such as demand level of product, flexibility in production, seasonality of the output and demand, etc.
  • Capacity utilization measures the level to which the maximum potential output is being reached.
  • Big data is defined as dynamic, big, and distinct volumes of data generated by people, tools, and machines.

Frequently Asked Questions about Operational Data

Unit cost is an example of operational data
Unit cost = Total cost/ Units of output

Through an operational data system, data can be defined, altered, and retrieved in real-time. 

Operational data is important because it gives information about the internal functions and processes of a business. 

Organizational data is related to the structure of a business and operational data is related to the internal functions and processes of a business. 

Operational data gives information on the internal functions and processes and non-operational data is used in research and reference. 

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