Create a Robust Data Quality Management Strategy For Your Company Using These Tips

 Currently, Big Data is inundating companies with more data than they can handle; the total enterprise data volume globally touched 2.02 Petabytes in 2022, seeing a CAGR of 42.2% from 2020 to that year. 

Create a Robust Data Quality Management Strategy For Your Company

Sifting through it all to get the important information is the challenge, especially with many data quality issues in tow. You need appropriate and timely data quality management to gain the high-quality data your company needs. Doing that includes a multitude of functions to filter out unwanted data components, thus rendering raw, unusable data into a valuable, intelligible, and actionable asset. 

But, as with all other aspects of business, you need to have a well-thought-out strategy to make the most of your data. This is easier said than done due to the complex nature of data management and other related factors. In case you’re wondering how to go about creating such a strategy, then this guide will provide you with the tips you need. Also, read on to learn how outsourcing data quality management services can offer more benefits to your company. 

How To Create The Best Data Quality Strategy for Your Company

    1. Consolidate Your Business Objectives

    Having a target to aim towards helps provide the clarity needed to take the correct actions to reach it. With business, the target is your set of objectives. You should first define what your business intends to do and how you want to go about it. Once that is set, you can carry on with creating a blueprint for your data management, checking along the way to see if it helps accomplish the goals. 

    2. Set A Budget

    The complexity and length of data quality management can take a toll on your company’s finances. Thus, it's important that you allocate a certain sum towards this endeavor that doesn’t cut down on your profitability. Determine the scale of the operation and other vital parameters that determine your costs, along with the charges for any data management tools. Allocate the budget accordingly, with some left for untoward expenses. 

    3. Scrutinize Your Data Sources

    Prevention is always better than cure, be it for human health or enterprise data quality. Your choice of sources determines the quality of your data right from the start. For an enterprise, there will be multiple data sources to choose from, but not all of them deliver an acceptable quality of raw data. Hence, you should evaluate your data sources options and eliminate those that are found to produce very poor-quality output. This helps you save time and cost as you won't have to deal with added data issues. 

    4. Ascertain The Stakeholders

    Data is a valuable asset that is best used by the appropriate personnel at the opportune time. This keeps your company’s data management in check by eliminating the introduction of unwanted people and operations on it. And the fewer the number of people and software accessing your enterprise data, the less likely it is to undergo unintentional or intentional loss of quality. 

    Hence, you should decide who the stakeholders will be for what portion of your enterprise data. There must also be a time limit on access to the data as a precaution against misuse. This not only helps maintain your data quality but also your data security. 

    5. Select Important Data Quality KPIs

    How do you know whether your data is of the desired quality or not? You’d need to have fixed factors that you can refer to for determining that. These key performance indicators can be ascertained in conjunction with the related stakeholders in your organization.

    They should indicate the key data quality factors that have the most impact on your output and your business at large. Some of the important ones to track include the total quantity of data, number of errors per data segment, number of each type of error, frequency of occurrence of each type of error, and time taken to clean a data segment. 

    6. Determine Data Quality Standards

    A data quality operation needs to have a standard it can adhere to if you want it to succeed. Otherwise, the output will vary drastically with each iteration on various data quality parameters. The standard you opt for should be a combination of prevailing regulatory ones and custom standards you use across your company. 

    Determining such data quality standards yields reliable results. It makes you more aware of how to use your data and helps you determine the best course of action. 

    7. Have a Regular Review Schedule

    No matter how good your data quality strategy may be, it will get outdated with time due to changing market and intra-company dynamics. So, you should rework the data quality management strategy at regular intervals to keep the data quality high. Decide upon a frequency that doesn’t have a long gap period between consecutive reviews while not overdoing it either. Remember that it shouldn't stretch your budget beyond limits. 

    Benefits Of Outsourcing Data Quality Management Services

    1. Cost Reduction

    Attaining high data quality is no small feat, entailing multiple sophisticated and technically-intensive operations to be performed. And with the complexity and scale of operations comes high costs. By choosing to go in-house, you open the door to running over your budget for the project as you’ll have to pay the salaries and hiring/termination costs of employees. You also have to consider the equipment and software tools necessary, and those can also run into high figures. 

    By outsourcing the project, however, you ensure that you don’t have to take on the burden of these aspects of data quality management. The mass of experts and projects at the agency means you get the benefits of economies of scale, reducing the overall price of your project. 

    If the data quality management company is based out of a developing country like India, then you also get cost savings in the form of advantageous currency exchange values. The hourly rate in such countries is far lower than in a developed one, making your data quality strategy development a profitable one, or at least, not a burden on your finances. 

    2. Quick Turnaround Times

    Strategy development for a complex aspect like data quality can be a drawn-out and tedious affair as every crucial component of it must be scrutinized meticulously. This means it takes time, which may be in short supply if you’re looking to compete in a tough market. Your in-house team may not be able to deliver the desired outcome on schedule due to a host of factors like inadequate skills, poor operational setup, etc. 

    An outsourcing company, on the other hand, has all it takes to deliver the results you need in your timeline. The major contributing factors to this quick turnaround times are the company’s sheer number of experts, their years of experience, efficient operational measures, on-hand equipment for the task, and constant communication with stakeholders, among others. This swiftness ensures that you won’t lag behind on your time-to-market goals since the high-quality data you need will be in storage for when your teams need it. 

    3. Instant Access To Expertise

    It takes a lot of effort to create an expert in the field of data quality management services due to the complexity of the work. Thus, it won’t be easy to find one for your in-house team, which increases costs and delays, contributing to losses. On the other hand, if you outsource it, you get instant access to the experts present in the agency. 

    They could even guide you on your strategy development by means of a collaborative approach, thus ensuring the strategy is clearly understood by all parties involved and that you get the best possible one without shortcomings. 

    4. Access To The Latest Tools

    Building a strategy of any sort requires a deep and thorough analysis of available data and metadata. This type of analysis is only possible using the best tools for the job. Your in-house team may falter at delivering a competent data quality strategy due to a lack of awareness and usage of respective technological tools for the project. This is especially true if your company isn’t associated with the tech industry. 

    Outsource data quality management services to prevent this mishap by gaining your strategy development the tools it needs. They are always in contention with others in their industry, thrusting them to use the best available resources to maintain their competitive edge. Thus, by outsourcing your strategy development to them, your data points will be analyzed with a high degree of accuracy. 

    5. Enhanced Data Security

    Data breaches exposed 15 million data records globally in the third quarter of 2022 alone. Such is the intensity and frequency of data security attacks today. All forms of enterprise data are vulnerable to the variety of attacks that occur, from simple leaks to complete system destruction. While it may be impossible to be 100% secure, you could still make it very hard for cyber criminals to get your data. One of the means to ensure such security is through outsourcing. 

    As a routine manager of projects belonging to multiple companies, including some high-profile ones, a quality outsourcing agency will have in place all of the necessary data security and privacy measures. These include security software like the latest antivirus, virtual authorization walls, Multi-factor authentication, etc. They will also have operational protocols in place that enhance the data security and privacy of their clients, such as limited access to data via the principle of least privilege. 

    Therefore, by hiring a data quality management company for data quality strategy development and other related functions, you give your data the protection it needs. The measures they adopt help keep your data away from the prying eyes and hands of your competition and other nefarious entities. They can even work with your preferred cloud operator for this purpose to make the data security and privacy setup of your entire data warehousing seamless. 

    6. Lower Attrition Rate

    When data is a vital resource for every kind of operation in a company, it stands to reason that the development of a viable data strategy will involve input from all types of employees. They may be asked to get involved in a much deeper manner than anticipated, leading to them working out of the purview of their job description. There arise many problems with this: 

    The quality of their output at their core function goes down due to this distraction.

    The added burden could lead to burnout due to the added stress

    The overall morale could go down, reducing engagement

    There will be a lack of efficiency, leading to reduced productivity

    Sustained existence of the above factors leads to high attrition rates

    With high attrition rate comes a positive feedback loop of the above-mentioned events. It introduces high losses that are best avoided to maintain good profit margins. Outsourcing data quality management services do just that. You let professionals handle the strategy development aspect, leaving minimal input requirements from your employees. The reduced responsibilities on them lead to better focus on their core tasks and improve engagement. With that comes better productivity and a lower attrition rate. 

    7. Better Database Management

    One of the main benefits of having a robust data quality strategy is better management of the company’s database. The strategy includes the number and type of errors that will be present in your raw data and what the expected size of the cleaned data will be. You can decide on the IT infrastructure based on that estimate, leading to a leaner setup. Another reason your database becomes better is because of categorization. Data gets assigned into various types and other classifications before getting stored as a part of quality enhancement. Thus, the user will know where exactly to look when they want to use a certain data segment. 

    Due to these factors, the whole database gets organized better, and its management becomes easy and efficient. The standards used to define the categories can be a part of the data quality strategy, providing a great reference point for experts and other sixers to maintain data hygiene. 

    8. Improved Situational Awareness

    Keeping track of the various things happening in a company can be a tough job, especially if the scale is large. Monitoring a crucial but non-core function like data quality strategy development, and its implementation makes things more difficult in such an environment. Yet, this is vital for any operation to ensure it’s running within budget and efficiently. 

    Outsourcing data quality management services come to the rescue here with its additional services. The agency handling your data quality strategy development can monitor the progress of its creation and implementation for you. It can generate periodic reports detailing the important performance markers in a format that’s digestible to you and your teams. 

    This gives you improved awareness of the status of your company and at least one of its operations. The deeper insight into your operations will enable you to adjust your decision-making process for better outcomes. 

    9. Easier Scaling/Expansion

    Scaling is an activity that every business owner both looks and doesn’t look forward to. On the one hand, it indicates that the business is doing well while on the other, it signifies the need to take risks that may not return the investment. With the scaling of the business comes an increase in data consumption and generation. The additional data can catch an in-house team off-guard, especially if it occurs suddenly. Their preparation for such an event may be insufficient or non-existent altogether. 

    But an external data quality management services provider can act as a thrust that propels your scaling forward. Their expertise and efficiency, along with staff strength, can handle any amount of data that comes their way without a drop in delivery times and output quality. This factor makes scaling your company easier as you know there is a reliable business partner who can handle surges in data, including sudden ones. 

    10. Better Decision-Making

    While data and its quality level are important, they are not likely to constitute the core aspects of most businesses. That means every time an owner of such a business doesn’t outsource data quality management services, they are taking on an additional burden of managing that task, along with their regular work. This causes them to lose focus and may result in poor decision-making for the business. 

    You can prevent this by doing the opposite. By having onboard data quality management professionals from a different agency, you get to remove a lot of your additional burden. This frees up time in your schedule that you can use to work on other core functions of your business. 

    The reduced stress, coupled with the better awareness granted by high-quality data, lets you make productive decisions for your company. You can take those quickly too, since you know the strategy developed for maintaining data quality always gives you the best results post-processing. 


    The growth of a company is intrinsically tied to its data management capabilities, specifically on how well you can transform the raw data into something valuable at scale. The strategy employed for this transformation makes all the difference between having a successful company and a struggling one. By outsourcing data quality management services for strategy development and other related functions, you open the door to experiencing operational reliability and efficiency without facing any hassle. 

    Author Bio 

    Gracie Ben is a data analyst currently working at DataEntryIndia.in, a leading data entry services company providing enrichment & data mining, web research, data quality management services & other data-related solutions. For more than ten years, she has actively contributed to the growth of many enterprises & businesses (startups, SMEs, and big companies) by guiding them to utilize their data assets. Having a keen interest in data science, Gracie keeps herself up-to-date on all the latest data trends and technologies shaping the industry and transforming businesses. She has written over 1600 articles and informative blogs so far covering various topics, including data entry, data management, data mining, web research, and more.

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