Post Menu and Details.
- Prevent information gaps
- What are information gaps?
- How information gaps could harm your enterprise
- Understand the difference between information and data
- Remove silos to data
- Ensure data is accessible to all your teams
- Raise the quality of data
- Create a data-driven enterprise culture
- Don’t let information gaps undermine your data capabilities
Reading time: ~4 minutes
Prevent information gaps
Today, every enterprise strives to be “data-driven,” basing their major business decisions on insights and information that’s grounded in real-time, reliable data about markets, target audiences, and the business itself.
You want to use data to spot and seize opportunities, identify and mitigate risks, find ways to cut costs, understand your audience, offer customized products and marketing, optimize supply chains, and more. The companies that can access the fastest, most up-to-date insights are the ones with the competitive edge over their rivals.
But these goals can be hard to attain. Nielsen reports that only 24% of companies have succeeded in building data-driven cultures, even though 96% of them achieve isolated successful outcomes.
The pitfalls are many, but one of the main obstacles that trip up enterprises on their route to data-driven nirvana is that of information gaps, which handicap your data analysis and ability to apply insights.
Information gaps occur when something breaks down in your analytics system, which is responsible for turning data, the raw material for information, into meaningful and actionable insights.
Ideally, data flows into your organization where it’s integrated into a single repository and cleaned, processed, and crunched before flowing out again as insights and information. But as is well known, data is big, huge, and disparate. It’s easy to become overwhelmed with enormous, fragmented datasets that leave you drowning in facts with no way to understand them.
When information gaps proliferate, some or all of your business teams are left without the information they need. You’re flying blind, without reliable insights into your business, market, or target audience. As a result, you end up basing critical business decisions on gut instinct, or the opinions of whoever shouts loudest.
Even worse, you might find yourself embracing “alternative facts” because you aren’t aware of your limited vision. When data analytics isn’t performed correctly, what appears to be information can actually be half-baked or even raw data that’s received some perfunctory analysis. You think you’re making data-driven decisions, but the insights on which you rely are actually opinions dressed up as facts.
The fallout from information gaps can include:
- Inability to predict trends among your customers, so you won’t know which products to invest in next
- A lack of awareness about which loan applicants are at greatest risk of defaulting on repayments
- Not being able to identify the VIP customers who should be invited to your next exclusive, members-only event
- Failure to measure and track your progress against critical business KPIs
- Not knowing who is your biggest or closest competitor, or what could be causing their competitive edge
Fortunately, information gaps don’t have to triumph. There are ways to close information gaps and restore your understanding of your business landscape.
Very often, information gaps arise because key stakeholders mistake data for information. They collect as much data as possible, but the more they amass, the more the confusion grows. As a result, they don’t realize how far they are from insights.
Educate your stakeholders in the differences between data and information, share content about the value of meaningful insights, and make sure your data processing pipelines are visible to all..
Data silos are one of the biggest culprits of information gaps, and fortunately also among the easiest to solve. Upgrade your data gathering and storage processes to include data lakes, which can unite data from every source and format it into a single data repository.
At the same time, implement a cloud data warehouse, which is excellent for all kinds of traditional analytics and advanced online analytical processing. Data warehouses employ columnar storage, which is faster and easier to read, so they can deliver swift and reliable answers even to complex queries. Cloud data warehouses add the ability to store immense datasets, so you can be sure your analytics can access the full picture.
Removing barriers to access for data-based insights for all teams across the organization is crucial for bridging information gaps and preventing them from arising. Employ intuitive, easy-to-use business intelligence (BI) and advanced analytics tools that have intuitive interfaces, so that even your non-techie teams can help themselves to insights.
You don’t want data scientists to turn into gatekeepers, as that easily leads to bottlenecks (not to mention resentment from your DS people). If your employees have to wait too long for answers to their queries, there’s a risk they’ll decide that an educated guess is good enough, or else try it themselves and fail to reach the answers they need.
Every investment you make into automated data preprocessing is money and time well spent. Automating and streamlining data pipelines helps you verify data authenticity and ensure that datasets aren’t duplicated, as well as thoroughly cleaning data and preparing it for analysis.
The best tools and processes in the world won’t be of much use in preventing information gaps if your employees don’t know how to use them correctly. It’s vital to take the time to educate all your workers in data literacy so that they can handle your intuitive information tools and understand the importance of data processing.
You want to be sure that all your teams know to work from the same data repositories, don’t silo themselves away from the rest of the organization by creating their own sources of truth, and are able to manage self-serve data portals independently to answer their own common questions.
Although information gaps can arise in even the best of organizations, there are steps you can take to prevent them from taking root. By promoting a data-driven culture where data is freely accessible to tools and insights are easily accessed by teams, and acting to improve your data quality, your enterprise can leverage data-based decision-making to surge ahead.
Thank you for reading!