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Gain Incremental Efficiencies with Automated Data Collection

Gartner projects investments in RPA to swell up in the coming years. With automated data collection, businesses can increase their bottom-line efficiencies and increase profits.

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The Shift from Manual to Automation: Automated Data Collection is the New Business Imperative

COVID-19 just took a few months to sweep through the globe, leaving organizations to reevaluate their business approach. Many shut offices and others decided to embrace the new normal of the work environment. Businesses are still slowly yet steadily adapting to the changes amid this massive take on digital transformation. The past year has added global pandemic fallout, budget cuts, and much more to the ever-changing marketplace. Having said that, data has become more important than ever for organizations to resume operations in the ‘new normal.’

While companies have no shortage of data at their disposal, manually accessing it and compiling it into reports without trading off employee productivity is the actual poser. Be it CX data from consumers to real-time data streams from IoT/e-commerce platforms—automation lends the much-needed helping hand.

Investing in RPA and AI-enabled smart solutions for overarching processes such as data collection, data cleansing, data append, etc., helps businesses enhance their bottom line efficiency. This also results in faster turnaround times, reduced operational expenses, and increased accuracy.

RPA for Increased Efficiency

Robotic process automation helps you execute mundane, repetitive, and time-consuming activities, taking some burden off the human resources to allow them to concentrate more on high-value tasks. The key to striving in the cutthroat competition is keeping a dynamic presence in the customer’s life. Employees must focus on their core competencies to gain an edge in the industry as the ancillary tasks can be left to robots—thus paving way for automated data collection.

But first, it is important to know – what is automated data collection? Take the case in point: how RPA works for e-commerce retailers. RPA bots collect data through customer’s online touchpoints including their buying patterns, spending habits, shopping preferences, and so on. The digital workforce can efficiently analyze the data, link data sources, build reports, and compare it to the store’s inventory to assist their marketing and sales teams.

Automation is one fine way to make the touchpoints with fewer people at reduced capital expenses. Likewise, you can automate data collection from websites and get accurate data in real-time. Companies can gain benefits such as:

  • Accessibility – If the set of pre-defined rules are well-thought-out, the virtual workforce makes sure that the data is accessible to everyone within the organization.
  • Accuracy – RPA is rule and process-driven, meaning that it is designed to deliver accurate results. The data entry outcomes are precise and correct.
  • Consistency – The digital labor captures the data in the same format as per the set rules time and again. It captures values within the acceptable ranges.

In other words, data mustn’t be limited to a culture of analytics that facilitates decision making, but the type of tools used to collect and analyze it also plays an important role. With RPA, companies can expedite their digital optimization initiatives—and this is one of the major reasons businesses are readily adopting RPA in spite of the COVD-19 financial crisis. You might find it surprising that the RPA market is expected to grow at double-digit rates through 2024, as stated by Gartner.

Overcoming the Challenges of Manual Data Collection

Sifting through volumes of data when it is stored in different locations and analyzing is often taxing when performed manually. Consequently, the delayed access to insights slows down the decision-making process. There are numerous other challenges related to manual handling of data collection processes, some of which are listed below:

web-based data collection

1. Human Errors

Processes such as data collection, processing, and analyzing are resource-intensive and time-consuming. With an increasing business size, data sets also get larger and complex, with numerous variables at play. These processes, therefore, get prone to human errors. However, the virtual workforce is designed to understand such complexities and analyze big datasets much quickly.

2. Compliance Issues

Data-related laws such as GDPR, PII, CCPA, etc., must be followed by organizations to avoid any legal penalties and ensure data privacy. But with automated data collection systems in place, stakeholders can avoid the hassles of ensuring that datasets are up to the set industry standards. Also, businesses can determine what data is subject to which legislation and therefore provide prompt responses.

3. Limited Productivity

When employees manually collect and process data stored in different locations, they sacrifice a significant chunk of their time, leading to lower productivity for other critical tasks. But by automating repetitive and less consultative tasks, businesses can better concentrate on their customer-centric processes as well as map out strategies that boost profits, productivity, and growth.

The Bottom Line

The pandemic and ensuing recession have created interest in automated data collection for big as well as small enterprises. It has shown businesses the cost of falling behind and the only way out of this is future-proofing. Using a trusted automated data collection solution can help businesses stay relevant in the changing times and achieve and exceed their data collection and processing goals. In a nutshell, boarding the RPA bandwagon helps growth-focused industry leaders easily sail through the fallout!

Source: Gain Incremental Efficiencies with Automated Data Collection

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