Data Quality Management Plan

Data Quality Management Plan

Introduction

Data quality management is a practice that aims to maintain high-quality information. Data Quality Management begins from data acquisition, implementation of data processes, up to the distribution of data. DQM (Data Quality Management) is crucial to any organization handling data. Research indicates that companies dealing with data are successful based on the quality management of the data they handle. DQM is essential to ensure the data applicable in an organization is accurate, reliable, and without errors. Since data management is critical to any organization, there is a need to formulate a comprehensive plan of compliance to maintain a high quality of data.

Quality data indicates good leads in any company’s activity. For instance, it would be irrational for a firm to create a marketing campaign for an audience that does not exist. Quality customer data leads to better reach. Therefore, better data management schemes such as normalization must be executed to ensure the firm reaches the actual customer.

Studies indicate that if a company has an ineffective data management plan, resources will likely turn into waste for the wrong reasons. If an accurate program is established and executed on data management, then the data won’t lead to poor judgments, and as a result, resources are utilized. Maintaining high-quality data will eventually provide reliable predictions and leads and indicates where funds should be invested.

Ineffective data management strategies delays function in an organization. Through data management, fundamental operations in a firm can be performed within the stipulated period and efficiently. It is crucial to note that different levels of organizations need quality data for better decision making.

Data management involves converting raw data into meaningful data. This shows that the quality of results and information depends on the data management process. If the data is managed efficiently, useful data will be obtained. Conversely, poor data management leads to poor interpretation, which leads to the poor result. Data management is crucial to every organization, especially in the hotel industry, since you are dealing with large numbers of different clients. From a client’s relationship with management to enterprise resource management, the advantages of data quality management have a substantial impact on the performance of an organization. With a pool of data at their disposal, companies can formulate data warehouses to examine trends for future decision making and note the places of improvement.

It is worth noting that quality data management leads to high-quality data. If you aspire to have quality data in terms of interpretation, a quality data management plan must be formulated. Data accuracy, relevance, and completeness can only be realized if there is quality management of data. If an effective strategy to manage data is not established, then there is a high likelihood that the firm won’t meet its objectives.

The quality of data depends on several metrics. These metrics are crucial in assessing a firm’s efforts to increase the quality of information. To determine the quality of data, data managers must look up for accuracy, consistency, completeness, integrity, and timelessness. Efficiency is a crucial metric in the determination of the quality of data. It is achieved by measuring the ratio of data to the present errors. There is no specific or recommended data to error ratio, but the higher the ratio, the better the data gets. Consistency highlights that two data sets obtained from two different data sources shouldn’t have any discrepancies.

Nevertheless, consistency doesn’t always imply accuracy (correctness). Conversely, completeness ensures that the data collected reaches a stipulated threshold to conclude the data set. Data integrity is also referred to as data validation, and it ensures that data complies with all the outlined procedures (implies that the data is not intended so that it can fulfill certain conclusions). Finally, timeliness ensures that the data corresponds with the time limit of when the data is expected and when it is ready for use.

Data Management Plan

A data management plan (DMP) is defined as a written document that highlights the procedures to be followed in data generation, analysis, storage, data sharing, and data management. DMP is a crucial document to any organization regardless of the nature and the size of the data they handle. Research indicates that in a competitive market, a data management plan is a crucial determinant of market dominance.

Formulating a data management plan is a complex process and should be meticulously taken since it has a significant impact on the performance of the firm. Poor establishment of the program leads to poor generation and analysis of data, which leads to poor decision making and a waste of resources.

DMP aids the data manager in planning and organizing the data collected by thinking through the question that will arise during data gathering. DMP usually documents essential phases in the data lifecycle, such as description, preservation, or discovery of data. By establishing a data management blueprint, valuable details such as how the data will be preserved in the long term will be highlighted. Moreover, decisions of data sharing and data computing methods will be established.

Data Management Plan plays a crucial role in reducing instances such as data loss, erroneous data, and unethical uses of data. Previous statistics indicate that an effective data management plan improved the communication and accountability of data.

Any firm needs a plan for everything in order to succeed. Thus, firms need to formulate a data management plan as a risk management tool. There are unseen events that may arise with your data. As a result, it will be too late or expensive to make rush changes. A data management plan reduces/foresees these risks and tries to overcome them during the planning process. Planning is critical in data management since it reduces the occurrence of errors that would have adverse effects on the objectives of the organization. DMP’s create plans based on the previous data. Thus, they can identify loopholes that would have adverse effects on the data. With this information, they can derive measures that would increase the quality of the data.

Data Quality Management Plan for California Carlton Hotel

Hotel Overview

Just like any other hotel, California Carlton handles a enormous quantity of data from both the clients and hotel’s staff. California Carlton is one of the famous and luxurious hotels that have been in the hotel industry for more than three decades in California. This indicates that since establishment, it holds a large quantity of data. The hotel works on a mission of providing genuine care and comfort to the guests. Providing the most exceptional personal service and facilities for the guests to enjoy relaxed ambient is their top priority. Some of the services and amenities offered by the Carlton Hotel include food & beverages, laundry, and dry cleaning, comfortable and affordable rooms, business center access, and printing centers.

The official hotel website provides online information on the reservation systems. Some of the information easily accessed by Customers includes hotel location, room description, room rates, contact information, photo gallery, promotions, and other facilities and activities available at the hotel(“Boutique Hotels Nob Hill San Francisco | Hotel Carlton – Amenities,” 2020). Guests with a reservation are required to fill an online reservation form or request for any special needs to be noted. The structure of the website is well-organized and easy for visitors to navigate through. Sufficient information has been provided on the site and is up-to-date. The website is an excellent example of online hotel booking as it allows for correct information on the hotel.

Data Management Plan

It is quite clear that California Carlton Hotel needs a data management plan to accommodate data requirements to address data needs. California Carton Hotel needs the following to address their data needs.

1. Adaptability –Theadaptability requirement for Carlton Hotel includes hire of globally-minded employees with excellent communication skills, have a vast knowledge of the global existence, and dedicated to serve and work with people of different cultures.
2. Skills -The skills requirement includes excellent negotiation skills, knowledgeable, focused, team player, and focused on quality. This skill enhances the competitiveness of the organization in the market set — the improved facilities with a focus on the individual customer help in achieving a competitive edge.
3. Consistency – The consistency of the hotel depends merely on the facts laid for its sustainability. Resource management, through the engagement of the employees in undertaking a similar task, evaluation of the performance helps in the identification of the correct profitable parameters, and maintenance of customer loyalty through consistency in service delivery places the organization in the center of dominating the industry. Momentum can thus be created, helping in the continuous growth of the organization.
4. Extensibility – Extensibility of the business depends on the incorporation of the solutions that complement the functionalities that do exist. Embrace on Information systems and business software vary among customers, posing a significant challenge in its implementation on the business.
5. Risks and uncertainties – However, they are much minimized through extensions done on the enterprises of the business model. The applications used plays an essential role in running the business. They do support a wide range of processes such as order-to-cash.
6. Scalability – Reduced operational costs, revenue growth, and business expansion are the benefits of business scalability. The success of the business and its growth will then depend on a solid foundation, business model, embrace planning, patience, and focusing on the inner strength of the institution. Making adjustments helps to improve scalability. This can be done through a review of the core hotel processes and services offered.
7. Change control demands – In business, change is always inevitable. The need for goods and services keeps on changing, depending on various factors that affect economic stability. Carlton Hotel, like any other business, requires to monitor the customers’ trend over time to be able to compete with its key rivals. By having sufficient data, the hotel would be able to regulate its operations accurately and identify what to offer as per the consumer preferences. In this way, the Carlton hotel would be able to maximize its profitability.
8. Performance – Performance is a crucial measure of the organization’s success. The organization can only measure its performance by having relevant and first-hand information. Since the ultimate goal of Charlton hotel is to make a profit like any other business, evaluating its return is a priority need (Karanikolas&Vassilakopoulos, 2020).
9. Manageability – Proper management is a basic need in the hospitality industry. It enables the management team to determine how the business is performing and areas that need improvement. Proper management provides a clear direction on what should be done to move the business forward.
10. Security – The current advancement in technology calls for tight information security in the organization. The cases of the data breach are becoming rampant with time. In this regard, Charlton hotel must ensure the proper protection of its information system by having the capability of detecting and preventing unauthorized access (Karanikolas&Vassilakopoulos, 2020).
11. Business and organizational policies – Policies act as guidelines that control the stakeholders’ behavior. Since Charlton Hotel recruits employees from different cultural backgrounds, having sufficient data would enable it to come up with unifying policies that regulate the conduct of its employees to embrace the culture of teamwork.

The following plan should aid in addressing the needs of the hotel;

Accuracy

Accuracy is fundamental to data management and the interpretation of information. Given the needs of the hotel, there needs to be a higher degree of precision in data collection, storage, management, and use. The strategies can be used by California Carlton Hotel to improve data accuracy.

Normalizing

Database normalization is defined as the process of organizing the relational database. It is mostly done in standard forms to avoid redundancy and improve data integrity. Moreover, normalization divides larger tables into smaller tables and links their relationship. The primary normal forms include:

1NF: (First Normal Form) has two rules: each table cell should contain a single value, and each record needs to be unique.

2NF :(Second Normal Form) has two rules: database should be in 1NF and must have a single column primary key

3NF: (Third Normal Form) has two rules: database should be in 2NFand it should have no transitive functional dependencies

BCNF: It is an advanced version of 3NF; that’s why it is also referred to as 3.5NF. BCNF is stricter than 3NF

Data governance

Data governance refers to the overall use of data in terms of availability, usability, and integrity. Data governance is crucial to any enterprise since it helps in achieving a common understanding of data resources available. An effective data management plan in terms of data generation, storage, and retrieval to achieve user interface and responsiveness reduces program delivery costs. The technical plan involves control of access and modification of data in the database. The plan is presented in terms of users and the data they can access and modify

The governing body and the governing team should work together to establish standards and policies for governing data and implementation procedures. Since data governance is the critical strategy of data management, firms should focus on the desired outcomes of the data governance program instead of the data itself. Without proper data governance strategies, data inconsistency within several departments in the hotel might create performance problems. For instance, the client’s names might be written differently in the reservations database and the customer service systems. That could result in complications of data integration efforts and create data integrity issues.

Conclusion

For California Carlton Hotel to achieve its objectives, data needs to be handled meticulously. As indicated, the hotel has been in the industry for a long time and has numerous clients. For this reason, quality data management is fundamental since it leads to quality data interpretation and excellent results. Therefore, the management team needs to ensure that data is acquired organized and interpreted accurately. The data management plan assists companies in managing quality data in terms of accuracy, timeliness, completeness, and consistency. The stipulated data management plan should aid the hotel to manage data.