Three Lessons Data Management Can Learn from Meal Delivery Services

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Click to learn more about author Lisa Spagnolie.

Enterprises today are acutely aware of the exponential growth of data. However, according to a survey by PricewaterhouseCoopers, only 15% of firms currently have access to the right data needed to achieve their goals. In the face of massive data overload, today’s enterprises don’t have time to wait for IT to work through the backlog to make data available, instead they need this data to be accessible and easily digestible for the average business user to gain a competitive advantage.  

While thinking about possible solutions for organizations today, I couldn’t help but relate the necessity of companies to deliver data in a manner that is at least “half-baked” with meal delivery kits like Blue Apron, Sun Basket, and HelloFresh –  the “ingredients” are ready for you, pre-measured and pre-prepared, so all you have to do is follow the steps, and voila! –  you have turned a selection of ingredients into a delicious meal.

In the digital economy, Data and Information Management analysis should be similar. Enterprise teams need to be able to access and leverage data that has been cleansed, integrated and presented in a way that can be turned into action by the average business user. When it comes to looking at the lessons enterprises can learn from meal delivery services as it relates to implementing a Data Management system that sets business teams up for success, there are three key relations I see:

Lesson #1: Data needs to be at least “half-baked”

Food is an important part of people’s daily lives—without it, we wouldn’t survive. Plus, in a world where people spend their days running from meeting to meeting, not everyone has a large amount of time to dedicate to cooking. This is where meal delivery comes in: it gives you the ingredients pre-measured with a step-by-step recipe for creating the final meal. Cooking the meal isn’t as daunting and confusing when it’s laid out step-by-step, just like when data is presented in a way that makes the next steps clear and easy to do.

Similarly, data is at the center of everything businesses do. It informs every decision they make and enables them to gain insights into their successes, their failures and everything in between. That being said, not all businesses have a data scientist or chief data officer at hand to make sense of the mountains of data that are collected each and every day. Not only do businesses not have time to wait for IT to analyze the data, but for many companies today, finding Data Science talent can be a challenge—according to a recent LinkedIn survey, businesses need more than 150,000 data scientists in the U.S. alone, and that number continues to climb each day. Data needs to be accessible by anyone within an organization so that they can analyze, interpret and glean insights from their data. A survey of 80 data scientists found that they spend 60 percent of their time cleaning and organizing data, which reflects how necessary data profiling is for organizations.

Businesses need timely access to trustworthy data and insights so they can use it to streamline processes and maximize efficiency. Since not everyone has a data background, it needs to be presented in a way that’s at least half-baked, or in data terms,  it has to have gone through some type of cleansing process to make it easier to understand. By leveraging a data cleansing solution, organizations can detect and correct corrupt or inaccurate records from a record set, table, or database, which helps improve decision making, efficiency and productivity for business users.  After data cleansing, the data can be more easily analyzed and understood by anyone in an enterprise—all that is needed for the data is the final preparation.

Lesson #2: Anyone can do it, with or without a data background

Unfortunately, not everyone has the culinary expertise of a chef. People need a little help with cooking their meals too. While there is a vast world of complicated meal recipes out there, meal delivery kits keep it simple. They give anyone the ability to make a delicious meal, with or without a culinary background. When ingredients and steps to preparation are laid out in simple terms (and delivered straight to your door, for that matter), it gives anyone and everyone the ability to cook a great meal. Meal delivery makes it easy to be a chef and better data makes it easier to be a “data scientist” for your business.

Similarly, not everyone is a data scientist. Data democratization is the idea that anyone can have access to (and understand) data. The goal for enterprises looking to implement data democratization strategies is to arm employees across departments with the skills and tools they need to glean insight to relevant data and use it to inform decision making. When data is presented in a way that is at least partially cleansed, anyone can take the pieces and begin to analyze it, with or without a data background. Having a system that can take both structured and unstructured data and marry the two together to deliver insights is also a key part of the data democratization and insights process. With cleansed data and these types of “mash-up” systems, anyone can become a data scientist for their business; they can begin to interpret and glean insights from the data because it’s presented in a way that makes it easy for them to take the final steps. Half-baked data is data made simple.

Lesson #3: Faster, easier and “delicious”

Meal delivery kits are meant to save people time and money with delicious results. They open up new possibilities—better cooking, new meals, much like better data, leads to better insights and better customer experience. The “delicious” results from meal delivery kits are much like that of pre-cleansed and stored data: having the data at least half baked, opens up new possibilities (or new menu options so to speak) for what you can do “in the kitchen” or in the enterprise.

When data is presented at least partially cleansed, it is not only easier to understand, but it’s much faster to analyze and bring about “delicious” insights for a business. Because the half-baked data is ready for the final steps of preparation, it saves whoever is analyzing the data the time it would take to initially begin the process of cleansing the data. When you take in to account the different knowledge levels and various data backgrounds of whomever is working with the data, the time saved in this process could be substantial. This process is also part of data democratization: the ability to access data insights in near real-time translates into faster decision-making, and that in turn means teams can be more agile. Speed in data cleansing and analysis helps to drive action and inform business strategy to give enterprises a leg-up on the less data-savvy competition.

Like a meal delivery service, data needs to be presented in a way that makes it easy for everyone. With better data comes better insights and faster business decisions. The easier the insights, the more an enterprise can get ahead of the competition and save themselves money in the process. If you begin to think of your half-baked data like a meal delivery service, you are well on your way to becoming a culinary—I mean— data Rockstar.

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