From Overwhelmed to Organized: Fixing the Data Bottleneck in Business

Did you understand what bottlenecks are?

These are typically points in a process or project where the flow of work slows down or gets hampered, resulting in delays and reduced efficiency.

Now, analyze where your workflow turns sluggish. Did you ever focus on why it happens?

Well, this situation arises when your resources are limited, and the demand is overwhelming. In the case of data processing, a bottleneck can be seen when the volume of incoming data to process, organize, and use exceeds the capacity of internal teams. This situation leads to delayed decisions, poor data quality, missed opportunities, and overworked staff.

So, how can any businesses make a shift from being overwhelmed to being organized?

Let’s answer it in this post.

The Growing Data Pressure

The horizon of data is rapidly expanding. Considering IDC’s Global DataSphere report, the creation and consumption of data are likely to reach 175 zettabytes by 2025. It’s astounding to notice this leap from 64.2 zettabytes in 2020, which is nearly thrice the amount of this data in just five years.

This much growth prediction clearly indicates that the pressure on the internal operations team is going to be immense. Businesses are observed struggling to efficiently handle the constant flow of raw, unstructured, and unprocessed data. But it requires cleaning, sorting, enrichment, and standardization before its analysis.

Let’s consider the case of employees that don’t like to invest many hours on CRM or Excel data entry. On the flip side, skilled staff employ tools to meticulously process repetitive data entry tasks. This practice certainly affects its morale, which gets sufficient time on higher-value tasks like strategy-making, analyzing, and innovating new things.

The Human Cost of Data Bottlenecks

Now, let’s calculate the cost of data bottlenecks for businesses. Well, the first impact can be seen on humans or the workforce, but not on operations.

Always remember that overburdened employees feel strained and exhausted. This juggling with overwhelming tasks often leads to burnout, which increases error rates. The deadline is exceeded, and reputation is damaged. A study by Zapier reveals that data entry drains productivity, 76% of knowledge workers trust that their productivity sucks if they are aligned most on repetitive tasks. And 73% of them wish to automate most of their tasks.

Here, the noteworthy thing is that automation cannot fully satisfy, especially when the data is complex and unstructured. Let’s consider the case of OCR tools and automation platforms. These alternatives may misunderstand and even incorrectly classify or recognize data. Moreover, AI-driven processes cannot be blindly trusted. They require human verification and correction. That’s why a hybrid strategy is suggested where human experts work with AI.

Fixing the Flow: Delegate Data Input Solutions

The most effective strategy to eliminate any bottlenecks from the data-based workflow is to delegate data input solutions. The dedicated service providers onboard skilled professionals that can strategically handle incoming data promptly and accurately without much internal disruption.

Want to know how the delegated tasks help fix the bottleneck? Let’s share it.

1. Improved Efficiency

Outsourcing experts specialize in deploying strategies to handle massive volumes of data for processing like a piece of cake. The trained experts and their expertise speed up the streamlining process. Their quality measures can manage data entry faster and more efficiently than overloaded in-house teams.

2. Scalable Resources

The scalable business records an increasing flow of data. An external professional provides flexibility to ramp up or down data processing requirements without thinking twice about hiring or laying off internal staff. McKinsey automation research supports this by highlighting operational efficiency boosts from task delegation.

3. Cost-Effectiveness

Onboarding and firing an in-house data entry team can be expensive. Outsourcing resolves this problem by offering an alternative to pay for the volume of work done. This is how the enclosed overhead costs are minimal.

4. Reduced Errors & Better Accuracy

Premium data quality speaks louder about the standards being maintained. Outsourcing teams harness the double-check method, which includes leveraging error-tracking tools and manual checkups. It results in greater accuracy and hygienic data, which helps in creating an insightful report with fewer downstream issues.

5. Faster Decision-Making

Up-to-date and accurate data guides analysts and business strategists with real-time insights. They wait no longer to clean up an Excel or spreadsheet before initiating a campaign for marketing or pitching a proposal.

When to Consider Delegating Data Input

Are you still confused about when to hire an outsourcer? This confusion is obvious. Let’s help you to discover when it is right to delegate data input:

• Compute whether your team spends less than 30% of its time on non-core tasks. If it exceeds, outsourcing data entry can be considered.
• Analyze whether your data logs are delaying or hampering reporting timelines.
• Find out if errors can lead to severe compliance risks or customer dissatisfaction.
• Insufficient in-house expertise can also be a prime reason to manage data by a third party, especially when the data is in complex formats (PDFs, images, handwritten forms).

Let’s take the case of eCommerce businesses. They often require scalable catalogue entry services, which cannot be done without enough data specialists. Here, outsourcing support can prevent expenses associated with recruiting e-commerce product data entry specialists and quality experts for precise and accurate entries. Above this, it costs economical.

The Future: Organized, Not Overwhelmed

A data-driven business does not necessarily require in-house teams to manage and process it. In fact, the smartest of all businesses quickly assess when to delegate non-core responsibility to a third-party professional. This readiness shows a future-ready approach.

Offloading data bottlenecks to experts or professionals can result in boosting operational efficiency. Alongside this, this practice allows internal teams to focus on their core expertise areas, which can be evolving new products, strategizing production, growth strategies, etc.

And if your team does not confess its inability to handle scalable data for processing, quickly align it to an expert. It will prevent losses and inefficiencies.