Unless you’re a cobbler in a medieval village, by now you know the success of any business these days greatly depends on how well its decision-makers use data about its products, end users and markets. Running a data-driven organization, you’ve no doubt heard, can help you discover performance gaps, seize opportunities, enhance your business strategy, improve your products and mitigate risks.
Less well understood, however, are the reasons why many organizations fail when they try to make the most of the data they have. This is not only about technology, but the data-driven culture you build in your company. Below are some of the common struggles organizations face when they attempt to harness the power of their data initiatives:
Data literacy is key. Business leaders often are not fluent in the data they have and how it can help them. What data do you want to analyze, and why? What might your team do differently if they had the right data insights? Start by interviewing the people who collect, manage and use your firm’s existing data. Consider everything: Customer data, sales figures, web and social media stats, call center interactions, staff activity, etc. The more fluent your team becomes in the language of your data, the easier it is to develop use cases and extract insights.
Which datasets do you begin analyzing? Don’t bite off more data analytics than your organization can chew. Focus on data management that reveals progress against your firm’s key performance indicators (KPIs) or operational key results (OKRs). Other use cases will evolve over time. Deciding on a narrow scope and sticking with it for the duration of the analysis helps to build trust in the data. This also keeps your business processes on time and within budget.
Legacy data is usually stored in a variety of formats and structures, which are often difficult to integrate. Being able to access big data from disparate sources in a common format allows you to track more solitary and intersecting data points. What’s needed is a comprehensive business intelligence and migration plan.
Note: It’s not always necessary, or even advisable, to abandon legacy databases. The data needs to be visible using a common format in a centralized data platform.
Learn more about how to build a data science engine in your organization.
Having reliable data quality is critical to viewing accurate results and making trustworthy business decisions. But legacy data can be incomplete, incorrect and inconsistently or improperly formatted, which makes it difficult to organize and analyze. Strict standards for data hygiene, structure and governance are the solution to becoming a data-driven business.
Ensuring the confidentiality and integrity of data containing personally identifiable information or other sensitive details is critical, not to mention legally necessary. Too many enterprises, sadly, fail to give data security the attention it needs, posing huge risks to the organization. Any data-driven company should form a group tasked with ensuring the right new technology, protocols and legal guidance are in place to truly protect privacy and security.
We wish we had a penny for every executive who asked their team for a “data dashboard” without specifying how they planned to use it. Let’s admit it, data visualizations too often fail to deliver reliable, actionable insights. Charts, graphs, tables (and, yes, dashboards) are indeed critical components of your data strategy, so long as they’re as simple and meaningful as possible. Each should describe the status of a KPI, OKR, or some other insightful metric, providing a clean, crisp interpretation of the relevant data.
Learn more about the importance of data to personalize the user experience for customers.
We hope you keep these potential pitfalls in mind as you work to optimize your organization’s data maturity. We’re happy to help you in your journey to becoming data-driven. Please, reach out to us if you have any questions. We can help you realize better decisions and significant returns on your investment.