By Mashum Mollah
Data-driven strategies help business leaders make informed decisions that better serve customers’ needs. At least that’s often the goal companies have when collecting first- and third-party information.
But collecting and using data for the sake of doing it can lead to poor results. You need clear reasons for gathering information and streamlined sources and management processes. Otherwise, the data you have will become overcomplicated, inaccessible, and irrelevant.
Simplifying and taking control of your data starts with planning. A detailed information strategy must form the foundation of any data-driven business. You need to first define your goals and the types of answers you’re looking for. Then you can figure out what data to collect and how to manage, share, and use it.
Assess Where You’re at and Identify Objectives
Your company may already have information stored in different systems and databases. Perhaps you don’t know what all that data is or how long it’s been there. You may not know where it came from or whether it’s accurate or even viable. Some of the information could overlap or duplicate itself.
Data catalogs and data quality tools often require granular, manual work and often focus on addressing known or expected issues. Data observability tools and applications can be used to monitor a broader range of data risks, reduce manual effort through automation, and achieve greater precision through machine learning.
These apps scan the data across your entire organization identifying troubling data. A good data observability application will help your company implement data governance at scale by providing automatic data classification and tagging, automatic data quality recommendations, and key visibility into metrics and violations.
Understanding the current state of your data will help shape your goals. You may have to eliminate certain data sources or merge information. You’ll also want to define what questions your company needs to answer. Outline why your business needs to gather data and how information can align with the successful accomplishment of your objectives.
Create Streamlined Processes
After you determine your purposes for gathering data, you can take a deeper dive into how you’re getting it. Do you have client information from sales that gets put into your customer relationship management system? Is that same information coming from surveys the marketing department sends out? Does your billing department maintain a separate set of data about the same customers on a different platform?
With this one scenario, you can see where a company’s processes can create data overlaps, conflicts, and silos. A single platform shared between departments could eliminate most of this disarray. But so could using APIs and syncing the separate applications each department uses. Determining what your optimal data processes should look like will largely be driven by your operational needs and limitations.
Another component of creating streamlined processes is figuring out what data is coming from internal and external sources. When employees talk to clients and get information from them directly, that’s an internal source. External sources can be third-party research or data that comes from customer focus groups led by an outside partner.
Without a process for merging and sharing data between internal and external sources, that information can become isolated. The billing department may rely on one set of information while marketing uses a completely different set. Although there may be similarities in the data, chances are there are discrepancies and gaps that can produce disparate conclusions. These, in turn, can cause a lack of cohesion in decision-making and strategic direction.
Get Key Decision-Makers Involved
To determine how and where to collect information, you’ll need to consult the departments’ leaders that gather and use data. By involving key decision-makers, you’ll discover the diverse ways departments are using information. You’ll find out the types of data they need to accomplish their roles and begin to draw connections between them.
Each person has insights that can reveal data-sharing practices that aren’t as efficient as they could be. Inefficiencies and gaps can exist within platform capabilities. A formal procedure or an unspoken way of doing things may be creating roadblocks. Leaders within separate company functions can lack awareness of how others gather and use data.
Creating a cohesive, company-wide data strategy starts with varied input. But it ends with figuring out how to make that input accessible and usable to all that need it. It also requires finding ways to make the information consistent so decision-makers from different functions are seeing the same things.
Measure and Assess Results
Recognize that data strategy and process changes are fluid. You can come up with a viable idea that everyone agrees on but find out later that it’s not working. Maybe that new information source isn’t really revealing answers to your questions. Perhaps a tweaked process is creating inefficiencies and exacerbating the problem it was supposed to fix. Periodically, you’ll want to look at the results of your data strategy and circle back with key decision-makers.
You may need to redefine your goals, upgrade an application, or get rid of certain data sets altogether. Data-driven decision-making depends on data that is accurate, complete, and relevant. Maybe your data isn’t as clean as it needs to be.
Besides relying on internal audits of your information strategy, soliciting the knowledge of vendors can give you a fresh perspective. There may be something you’ve overlooked or weren’t aware of that external data analysts can identify. That’s especially true when it comes to overseeing the organization and accuracy of your information.
When assessing results, consider the feedback source and weigh its importance and relevance. Listen to all voices when reshaping your objectives but realize the results will need to drive modifications. Appeasing everyone’s wishes without reaching a common ground can put you back into a cycle of creating complexity and silos.
Conclusion
Disorganized and confusing approaches to gathering and analyzing data happen when organizations lack clear goals behind processes. When different departments and employees aren’t on the same page, information can get scattered, duplicated, and isolated.
Face the problem head-on by getting those who collect and use data to agree on the same objectives. Come up with streamlined processes that serve all company functions. Then continually assess how your strategy is working. These steps will help make your information more accessible and truly supportive of data-driven decisions.
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