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The collection and organization of high-quality data is foundational to the success of any Market and Competitive Intelligence (M/CI) effort. Without data, organizations cannot perform analysis to guide their decision making, and will effectively be stumbling around in a dark room, blind to valuable insights and information that could help them improve their products, services, and business models. 

As the amount of data available to organizations continues to grow rapidly, it’s becoming increasingly difficult to effectively manage competitive intelligence data. There are two distinct approaches that organizations can take: manually collecting data from individual sources, or using technology to automatically monitor multiple sources simultaneously.

It used to be the case that competitive intelligence teams would manually source, collect, tag, and analyze all of their data, using a librarian-style approach focused on efficiently managing taxonomies. But as new technologies like Artificial Intelligence (AI) and Natural Language Processing (NLP) have emerged, increasing numbers of organizations are turning to automated monitoring solutions. 

Both approaches have benefits and drawbacks, which we’ll explore in this article. But first, let’s begin with a definition––and some examples––of what we mean by manual data collection and automated monitoring. 

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Manual Data Collection: A Definition

What is Manual Data Collection?

Manual data collection occurs when people, in this instance competitive intelligence analysts, seek out data sources, download datasets, and manually upload files to whatever competitive intelligence or data analysis platform they use. In some cases, this could be as simple as going to a website, downloading an Excel file with data, and uploading it to a shared workspace. 

Many organizations still rely on manual data collection: in a recent survey Cipher completed in partnership with Forrester Research, 94% of competitive intelligence professionals said they believed their organizations spent too much time collecting data

Automated Monitoring: A Definition

What is Automated Monitoring?

Organizations that conduct automated monitoring use software tools with built-in integrations to all the data sources they need. As new data is added to each source, it automatically flows through to the software platform, meaning that competitive intelligence teams can effectively run their data collection process on autopilot.

Recent advancements in technology have seen automated monitoring platforms become more sophisticated than ever. Platforms like Knowledge360Ⓡ organize data programmatically, automatically sorting every piece of data into predefined categories to help intelligence analysts easily identify important datasets for analysis.

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Manual Data Collection vs. Automated Monitoring: Which Approach is Best?

While manual data collection does have merits in some specific applications, it’s clear that automated monitoring is the superior approach to collecting data for competitive intelligence. It often makes sense to use automated monitoring wherever possible, and to use manual data collection techniques in cases where automated monitoring does not work well: examples include field intelligence collected from an industry conference, or primary data from market research

Attempting to manually gather this data will handicap any competitive intelligence efforts before any analysis even begins.

The amount of data available to competitive intelligence teams continues to grow exponentially. Attempting to manually gather this data will handicap any competitive intelligence efforts before any analysis even begins. Competitive intelligence analysts don’t come cheap, with an average salary of $82,000/yr in the U.S, and organizations should be putting these talented professionals to work on higher-value tasks than manually collecting data. 

But it’s not just a question of cost. When it comes to collecting and organizing large datasets, automated monitoring tools dramatically outperform humans. Advanced platforms like Knowledge360 use NLP-powered automated tagging to source and present the most relevant data in real-time, ensuring competitive intelligence teams never miss critical data points.

By embracing automated monitoring solutions, competitive intelligence teams can give themselves as much as 45% more time to spend on analysis.

By embracing automated monitoring solutions, competitive intelligence teams can give themselves as much as 45% more time to spend on analysis, which is where the real value is driven from competitive intelligence efforts. And many organizations are embracing this, with 81% of competitive intelligence teams in the life sciences industry planning to increase their investment in these tools over the next twelve months. 

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Preventing the CI Cycle of Death

All too often, we see failed market and competitive intelligence efforts. A team gets spun up reactively, usually in response to some unexpected event that caught the organization’s leadership off-guard, and is tasked with undertaking competitive intelligence. 

The newly-formed M/CI team goes out and sources a wide range of data, and almost immediately becomes overwhelmed. Soon enough, leadership realizes that the new M/CI team has failed to deliver any valuable insights, and the entire effort is disbanded.

We refer to this as the CI Cycle of Death. The cure is relatively straightforward: employ an automated monitoring tool that acts as a competitive intelligence hub for your entire organization, gathering and processing data algorithmically so that CI professionals can spend the bulk of their time on high-value analysis work.

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Manual data collection is just one example of the type of low-value work that kills the effectiveness of competitive intelligence efforts, but it’s perhaps the one issue that’s easiest for organizations to solve. The continuing technological advances in artificial intelligence foreshadow a brighter future for M/CI teams, and organizations that embrace these technologies will be well-positioned to outstrip their competitors. 

Organizations that embrace automated monitoring technologies will be well-positioned to outstrip their competitors. 

Automated monitoring is just one element of a comprehensive M/CI tool. Others, like the ability to create real-time dashboards and foster collaboration between stakeholders across the organization, can help supercharge an organization’s competitive intelligence efforts. In turn, this enables leaders to make higher-quality decisions backed by robust insights, helping organizations to outperform their competitors. 

If you’d like to learn more about Knowledge360, Cipher’s M/CI Platform, you can schedule a demo with the team today

Still deciding which tool is right for your organization? Check out our Guide to Selecting a Market and Competitive Intelligence Software Tool for a full breakdown of all available options.