How to Plan Your Annual Data Management Budget

Eyal Katz
Content Manager | Aggua
March 27, 2023

Over the past few years, the implementation of data management strategies has skyrocketed as a critical approach to achieving success. Consequently, the cost of storing and managing data will only keep rising as your business grows.
To add another challenge to the mix, there's the tricky task of controlling your data management budget.

There is no doubt that without effective budgeting, your productivity and bottom line will take a hit. According to the USGS, companies can experience a loss of up to 25% of their operating budget due to poor data quality, redundant data, and lost data.

In this post, we'll discover the key considerations when planning your annual data management budget, the best practices, and how these tips help your organization gain a competitive edge.

First Steps in Data Management Planning

There are several crucial initial steps for developing a quality budget plan, such as understanding the benefits of data management and identifying the real price you have to pay in cases of poor data management.

Effective data management grants an organization with accuracy, completeness, consistency, and security of data and makes it highly available to authorized personnel when required. A 10% improvement in data usability can increase the revenue of an average Fortune 1000 company by more than $2 billion, according to a recent study by the University of Texas. Even if your business is not an international powerhouse, you can still gain a solid competitive advantage from data analytics, as 62% of retailers agree. With this in mind, a data management plan is undoubtedly worth the investment.

[Uncovering the Hidden Insights of Data Management Statistics 2023 | Source: Gitnux]

Cause, Effect, and Consequences of Poor Planning

Poor data management can be a fatal blow to a company's efficiency, reliability, and finances if not strategically handled. Incomplete and inaccurate data often causes your business-related decisions to be erroneous. Also, data being unavailable when needed has a direct impact on productivity.

Eventually, it will lead to the following:
Lack of agility and flexibility: Missing out on significant business opportunities in the competitive industry.
Poor data governance: Making your company vulnerable to security breaches, data loss, and cyber-attacks.
Ineffective resource allocation: Causing your projects to go over budget or waste money.

Data Management for All Business Roles and Functions

Data management operates through multiple roles in a company to make specific tasks less time-sensitive and more straightforward. Formulating the best strategy really depends on your organization.

Here are a few tips to help you get started:
● Recognize the business objectives and define the data management requirements around them.
● Identify competitors and market challenges and create robust data processes.
● Find the correct technologies and the right people.
● Execute, monitor, and continually adapt.

A proper data management strategy eliminates the risks mentioned in the above section and provides your company with visibility, security, reliability, and scalability boosts.

Prioritization is a Never-Ending Challenge

Half-baked planning will only result in a lack of resources and is bound to cause trouble in the future. A proper budget plan encourages your organization to plan for the future and formulate strategies to handle unseen potential challenges and costs it may come across.
When planning data management budget allocations, it becomes easier over time to identify and prioritize data-related initiatives and to allocate resources based on your strategic priorities. For example, an on-premise data management plan could incur extra costs such as hardware and infrastructure. Think that sounds expensive? You're probably right, which is why more and more organizations are turning to cloud-based data management platforms that provide an all-in-one view of data, analytics, resources, BI tools, and more.

Hurdles To Adoption, Success, and Budgeting

Data is abundant, and it's also easy to let costs run away with you. Companies often consider data management expenses to be “costly,” but the reality is that poor visibility over where your data comes from is the real expense. From data storage to the impact of transformation of data in your organization, your data costs come from a wide array of factors, and proper data management is the only way to control them.

Here are some other costly challenges you might be facing:
Growth in data: As a business expands, the data is bound to increase. This situation can be challenging without tracking and reporting on granular costs, as it will gradually increase the expense of data storage and processing.
Security and compliance: Investing in security technology, compliance, and governance requirements can amount to additional expenses unless you choose a data management solution that can help.
Outdated and redundant data: It can be challenging to keep an eye out for outdated and redundant data, particularly in organizations that handle large quantities of data. Therefore, there may be instances where processing time and storage costs may increase.

Step By Step Guide to Budgeting For Data Management

Several factors contribute to a proper data management budget for a business. There are diverse methods to generate a budget, but most of the time, they involve the company's resources, services, and policies.

1. Consider Your Business Size and Data Generation

You can use data comparison ratios and identify the size and amount of your organization as the first step. For example, you can either calculate the total number of bytes generated per day or the average file size per day.

2. Take the Type of Data and Complexity into Consideration

For instance, more complex data may require more resources, and the processing power and storage size also differ based on the data. Therefore, it is crucial to care about the data type and complexity (the transformation, cleaning, and processing of your data).

3. Break Down Data Management Costs into Sub-groups For Ease

You can categorize costs into data gathering, data architecture, data governance, and data consumption. In each group, address costs including, short-term, long-term, external/internal, equipment/services, overhead, time, and human resources. It’s a long list, but it ensures you don’t miss anything.

4. Remember Your Business’s Growth Goals

Remember the business' objectives, KPIs, and growth goals: Your data management needs will exponentially increase with data size as your company grows. So, it is essential to take note of this potential growth when preparing the budget.

5. Prioritize Improvement  

If you currently have data management processes and tools in place, be stringent and identify the areas that need improvement (in alignment with your overall business goals, e.g., scalability). Even after you’ve set your budget, you can monitor and adjust it to stay on track continuously.

6. Establish Clear and Concise Data Governance Policies

You can avoid unnecessary operational costs caused by a lack of efficiency and slow decision-making by ensuring your organization has clear policies regarding data collection, processing, storage, and disposal.

7. Allocate a Contingency Budget

It’s a good idea to allocate a contingency budget for data auditing and performance monitoring, which will give you the flexibility to follow up with necessary changes to your data management strategy for a short and long-term budget.

Start Saving on Your Data Costs with Aggua »

With a proper data management strategy and a well-thought-out budget plan that supports it, your organization can realize the maximum benefits of in-context, up-to-date, and accessible data that enables you to make real-time data-backed decisions and secure that all-important competitive advantage. With a collaborative data management platform like Aggua, you can track and report on granular costs to stay on top of your spending in real-time.

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