Tips for Creating an Enterprise-Wide Data Strategy

A business’ performance and competitive capacity depends largely on how successful they are in managing their data. Having a data strategy which encompasses how data is handled at each and every point of interaction helps to provide assurance that all data being used to make important business decisions is accurate, relevant and up-to-date. So - what exactly is a data strategy? Simply put, it’s a plan created to improve all the ways data is directed, through how it is acquired, stored, managed, shared and ultimately how it is used to make decisions.

Having an organized process to regulate and ensure compliance of standards at each point of the data journey is crucial in evading errors and keeping essential data organized and easily accessible for decision making. An enterprise-wide data strategy is not only great for these organizational purposes but also in creating consistency in decisions being made across the company. There is research further confirming that data-driven businesses are significantly more successful than those not utilizing data to its fullest potential.  McKinsey Global Institute found that data-driven organizations are “23 times more likely to acquire customers, six times as likely to retain those customers, and 19 times as likely to be profitable as a result” so, spending the efforts to craft a detailed data strategy will surely benefit your company’s short-term goals and overall business success in the long-run.

Ask Yourself These Questions:

Keeping your company's overall business strategy in mind is pivotal while crafting your data strategy. Make sure your companies objectives align with that of the data strategy. This is a great starting point while determining what business questions you hope to answer through data. A lot goes into building a comprehensive, successful data strategy. So, before piecing it together, start by asking yourself a few of the following questions:

What is your overall goal for your data? How do you plan on using this data?

Having distinct goals in mind for your data strategy can make the influx in data seem less overwhelming and more organized. Whether your goal is to find where upsell opportunities are present, which promotions are most successful or even information regarding maintaining inventory or pricing solutions, having an end goal in mind for your data will help you solve the questions you seek to answer as well as lead you to other opportunities to improve using these actionable insights.

What kinds of data do you plan on gathering? How do you plan on acquiring this data and storing it?

Deciding on what type of data you need is one of the first steps in creating a data strategy. Knowing whether your goals can be answered using solely internal data or whether external data needs to be collected is important to know upfront. Is structured or unstructured data required? How fast do you need to access the data, real-time, weekly, monthly? Do you have the resources and skills to collect your own data or do you need a third-party tool to assist in ingesting and analyzing data? Knowing exactly what you need and how to get it is a key component in designing a successful data strategy. This is where a data architecture plan would be helpful because, by determining a crystal clear set of rules, policies, and standards to control and define the types of data being collected, how it is stored, integrated, and put in database systems, you are able to avoid being overwhelmed by the massive amounts of data that may be coming in while also minimizing potential issues that could arise.  

In addition to knowing what kind of data will best meet your needs, and creating an organized data architecture plan, it is important to be aware of different regulations that may affect your data storage plans. While some data can be archived or even deleted within a month of its inception, some data needs to be retained for up to seven years after the conclusion of an audit as a record.

Who is responsible for implementing the data strategy, and validating the accuracy of the data?

Having a dedicated team or person ensuring that all data being used and collected is 100% accurate, up-to-date and relevant is essential in keeping data tidy while avoiding any possible distorted analytics reports that could have a detrimental impact on business decisions. When choosing a team or a person to be responsible for implementing and monitoring incoming data, make sure they speak the language of data better known as ‘data literacy’. Not only should these few understand the ‘lingo’ of data but everyone within your enterprise should have some sort of working knowledge on data. Knowing how to understand, analyze and implement decisions based on your data is an essential skill in today's data-driven world. Without it, data could be meaningless. Check out this blog post for more information on how to spread data literacy across your enterprise.

Lastly, when choosing your team, it is important that they not only understand the value of data in decision making but also know the organization’s technological capabilities and limitations. Having unrealistic expectations when it comes to what the company's technological capabilities are, is a great way to ensure you data efforts fail. Making sure you have the right tools to create a successful data strategy for your intended audience is incredibly important.

How will you access the data, and who will have access to it?

Giving your entire company access to all collected data is probably not the smartest thing you can do for your data security efforts. Sensitive information such as customer data, contact lists, and employee records are among those only select individuals or teams should have access to. Recent findings published in Varonis’ 2019 Global Data Risk Report found interesting facts regarding employee access including that, “17% of all sensitive files were accessible to every employee”, “27 percent of a company’s users had removal recommendations, and were likely to have more access to data than they required” and “Fifty-three percent of companies have over 1,000 sensitive files open to every employee, up from 41 percent last year.'' Much of this unnecessary and possibly damaging access is because of lax policies on governing stored data. So, while making your data strategy, be sure to set and implement clear policies on who does and who does not have access to sensitive files.

Having a data-driven enterprise is imperative in keeping up in today’s competitive landscape. Without using data to back important decisions it is nearly impossible to be a strong contender. We at Agilence have developed a data analytics solutions for the retail, restaurant, grocery, c-store, and pharmacy industries to provide enterprise-wide insights and improve the decision-making process. 20/20 Data Analytics can consolidate data sets, identify patterns, spot internal fraudulent activities, send automatic alerts and more, delivering user-friendly actionable insights.