Did you know that data-driven organizations are 23-times more likely to acquire customers and 6-times more likely to retain customers? They’re also 19-times more likely to be profitable. Those statistics come from McKinsey Global Institute and they illustrate just how important data is to business success today.

According to Gartner, “data and analytics will drive modern business operations” in the future. The world businesses operate in today is already ruled by data and information has never been more powerful. It’s a data-driven business world that’s been referred to as the Fourth Industrial Revolution (after steam and railroads, electricity, and the internet). Companies that have jumped on board the data-driven transformation are poised for long-term success, while the rest will be left behind.

Why is data considered the holy grail of business today?

Information is power, and when a company has access to the right data, it can use that data to drive modern business operations (as Gartner says) rather than simply using data to report and reflect the company’s performance in real-time.

That’s why data is transformative.

Here are six key parts of an effective data strategy that your company should understand to begin its own data-driven transformation.

1. Adopt a Data-Driven Company Culture

The first step to harnessing the power of data is recognizing that your company needs to invest money in order to build data as a strategic asset. Data strategy should be owned by the company’s leadership and spread to all employees through a data-driven company culture.

Once all employees buy into the culture of making decisions based on data, you’re on the road to a successful data-driven transformation. However, you’ll need to invest in technology, talent, training, and possibly external data sources to do it.

2. Develop and Commit to a Data Strategy

Anyone can say their company prioritizes data, and many executives believe they’re companies are data-drive. However, the reality is quite different.

Looking at the Dell Data Maturity Model (DDMM), there are four stages that a company goes through when it comes to developing, implementing, and committing to a data strategy:

  • Data Aware: At this early stage, data is unstructured and manually compiled. There are no centralized data repositories or tools for company-wide reporting and analysis.
  • Data Proficient: Data is often unreliable, efforts are duplicated, and processes are slow as organizations become data proficient. In addition, a lot of data is still not structured effectively. Most companies stay in the data proficient stage for the longest period of time.
  • Data Savvy: At the data savvy stage, data is plentiful and reliable and processes are in place to analyze that data and make decisions based on it.
  • Data Driven: Data is at the core of every process and decision when an organization reaches the data driven stage. In fact, no decisions are made without data.

Each stage of the DDMM has a specific goal. To move from data aware to data proficient, companies must develop standardized reporting, and to move from data proficient to data savvy, they must track key performance indicators (KPIs) using a business intelligence platform. To move from data savvy to data driven, companies need to be able to make decisions related to critical initiatives using data. Finally, the goal at the data driven stage is to add scale and reduce costs.

According to a study by Forrester Research, companies only analyze 12% of the data they have, which means 88% of data is wasted. In other words, most businesses have a long way to go to become data driven, which means developing and committing to a data strategy is essential.

Bottom-line, you’re not data-driven if you’re only analyzing 12% of your data.

3. Identify Your Data Sources

Where will your employees get the data they need to make business decisions, identify opportunities, and be proactive rather than reactive? First, determine how you want to use data (i.e., your goals) and what type of data you need to reach your objectives.

Some data can be collected internally, so be prepared to invest the money and time to develop the architecture required to collect and store that data. In addition, some data might have to come from external sources. Again, commit to investing the money necessary to get the information you need to be successful.

4. Determine How You’ll Use the Data You Collect or Access

How will you take the data that you’ve gathered or have access to through an external source and turn it into actionable insights that can guide decision-making and help your business reach its strategic objectives? Do you have the talent on staff to analyze and use your data? Do you need to hire or outsource specific job functions in order to allow your data to drive the best results?

A critical part of using data effectively to guide business decisions is to analyze it and find opportunities (or threats) from it, so you can exploit (or mitigate) those opportunities (or threats) to improve sales, operations, and value for the organization. Therefore, you need to be sure you have the necessary resources to effectively use your data.

5. Democratize Your Data

Data is powerful, but if only one or two people or departments in your company have access to it, then its potential is limited. For data to be transformative to a business, it must be accessible across the organization for daily decision-making.

Data can aid and streamline processes for the marketing, finance, sales, customer service, legal, operations, and other teams across the organization. When decisions are made based on data, they’re typically better and lead to greater success. Therefore, to the extent possible (and allowed by law of course), make sure the decision-makers have access to the right data to make the best decisions.

6. Develop Data Accuracy and Governance Processes

Data accuracy is always important, but as more people in your company begin to rely on data to make decisions, the risk of loss from decisions made with bad data grows exponentially. With that in mind, it’s essential that processes and policies are put in place to ensure everyone is using accurate data. For example, a data accuracy policy should require vetting of external data sources to ensure only reliable data providers are used.

When your employees use data on a daily basis, it’s critical that your company has a data governance policy and related procedures in place to keep data private and secure. This includes both internal and external data to prevent illegal data-sharing and other data-related practices that could be illegal or unethical.

Key Takeaways to Leverage Data for Business Growth

Whether you operate a cannabis business or an ancillary business, you need to prioritize data in order for your company to gain and keep a competitive advantage that translates into long-term growth. Get started now by integrate data into your company’s DNA, developing a data strategy, identifying your data sources, making your data accessible to the employees who need it, using it effectively, and ensuring it’s accurate.

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Originally published 2/28/19. Updated 8/30/19.