Few companies realize the extent to which their business strategies depend on data — until it’s too late.

Think about it like a road trip. The business strategy tells you where to start, which route to take, and the destination. The data strategy tells you the condition of your vehicle, how much gas you have, and where the gas stations are along the route. Sure, you could successfully make it to your destination if you ignore the data, but your success is much more likely if you view the whole picture.

Company leaders put a lot of emphasis on business strategy and not enough on data strategy. Even when leaders track key metrics, they often measure the wrong ones when they lack data strategy behind their decisions.

Mistakes occur because businesses operate in a culture that is not driven by data. Too many executives only appreciate the value of data strategy after they try to use their data; then, they forget the lessons they learned when they plan their next move. Without proper data governance, companies cannot generate the intelligence they need to design and execute successful business strategies.

Execution at the Cost of Data Governance

Executives like to get things done. They worry less about processes and technology than they do about results. Unfortunately, that mindset hinders their ability to deliver on the expectations they set for themselves, their teams, and their companies.

Some companies, like Amazon, have freed themselves from this limited mindset. They no longer see data as a checkbox on a list but as a valuable asset. When a user adds a movie to the shopping cart, for example, Amazon’s data says that person is more likely to buy another movie in the same transaction, so the website shows comparable products on the next screen. These types of insights alone boost Amazon’s revenue by more than 30 percent every year.

Beyond the shopping experience, Amazon’s anticipatory shipping model predicts when and where people are most likely to buy products; then, it uses supply chain automation to keep those products in warehouses nearby. Amazon also uses data to set prices, combining information on demand, competitor pricing, and multiple other factors to decide when to discount and what to feature.

Retail giants like Amazon are ahead of the game because they constantly interact with customers. If they don’t innovate or if their data strategy is misinformed, they suffer major financial consequences. Soon, even businesses that rarely interact directly with customers will face the same choice: create a better data strategy or perish. To put data strategy at the core of your business strategy, there are a few tips to keep in mind:

1. Establish Stronger Data Governance

When no one agrees on the definitions of data elements, the pool of data becomes untrustworthy.

One of my customers in healthcare wanted to figure out the optimal treatment for a specific kind of tissue injury. When this client began its research, it realized that some physicians categorized this type of mass as a lesion, while others called it a mass. Different terminology made it impossible to compare the efficacy of different procedures on the same problem.

To create common definitions, put together a committee of leaders who understand the technology and importance of the data to the operation. This data governance committee should go through important KPIs and name the factors contributing to them so the company can measure everything the same way.

Data governance must always keep business goals at the forefront of the process. Data for data’s sake helps no one, but data aligned with concrete objectives improves the odds that the company will achieve its goals.

Struggling to agree on the best approach to data governance? Turn to a tool, like Informatica Axon or EnterpriseData Catalogue, or consult a third-party service.

2. Scrutinize Data Quality

Old or inconsistent data indicates that an organization lacks a solid data strategy. For B2B sectors, bad data is especially troublesome. Rates of data decay in these industries can reach 70 percent per year, and research indicates that the average sales team loses around $32,000 annually in pursuit of faulty prospect data.

Avoid bad data by evaluating the database for things that look unusual. If a doctor’s office normally sees 20 patients but shows 30 entries, that office should look at common factors like appointment times and medications prescribed to weed out the bad entries.

The most permanent solution to this problem is automation technology. Several tools empower companies in various industries to audit their databases and scrub bad entries. Current leading solutions in this area include Informatica Data Quality, Melissa DATA, SAP Data Services, Oceanos, and Listware.

3. Implement Master Data Management

Without a master record, data becomes fragmented. Companies spend unnecessary time to log and track multiple records when they could save themselves the headache through master data management.

Say, for example, a hospital is doing a marketing campaign. Contacts have first, middle, and last names. One employee can’t find an intended target, so he makes a new entry that includes a middle name when his original target was in the system without one. Now, the company has duplicate records for the same person, and workers will continue to log data in multiple places until someone corrects the issue.

Master data management arises from proper data governance. The data governance team comes together to determine policies, people, and processes and then selects one record to be the “golden record” to believe when two records disagree.

The best tool to assist companies in this area today is Informatica MDM. Thanks to its modular approach to master data management, Informatica MDM can scale with the company’s data, ensuring information remains accurate.

Business strategy should not precede data strategy. The two should work in harmony, with business strategy determining what data to collect and with data strategy using that data to inform the business strategy.

Remember, successful business plans are like road trips. You could take off without a destination or neglect to check your gas gauge, but it would be better if you used all your resources to ensure your success. Follow these tips to put data strategy at the heart of your business strategy to make more informed, successful plans.

3 Critical Pieces of Data Groundwork for Modern Business Strategy