A map provides an individual or organization with a visualization of the route they will take. Beneath every map, whether it’s a GPS map on a smartphone or on a vehicle’s dashboard or even an old-fashioned paper map, lies a wealth of engineering. Consider, for a moment, the depth of detail on a map, from topographic definitions, the shape and position of buildings, forests, the course of a river, and the location of infrastructure ranging from roads, power lines and railway tracks. Bringing all this information together into a usable result that provides excellent user experience, accuracy, and gets people or goods to a place safely requires a major level of data engineering.

In today’s business, the complex ecosystem of vendors that are needed to meet the high demands of a customer, their changing behavior patterns, and the speed of commerce all demand that an organization have the ability to examine the landscape in which it operates. By looking at the environment, an organization can understand where it is and in which direction the business is heading. Data engineering enables organizations to chart this course.

Without an engineering data set, organizations will not be able to produce a map containing the details needed to safely navigate the business. It’s like a keyless card. The engineering data will allow the organization to understand if a line refers to the topology, the national border or the railway. Or in business terms, let a number be P or L.

Mapping, data and engineering have a long and intertwined history. In the early 1800s, during the industrial revolution, canal building became a booming industry in the UK to compete with current investments in Fintech. To successfully dig the canals that would connect the mines to the industrial heartland of London, Glasgow or Birmingham, a geologist, William Smith, used the data he had collected to create a geological map of the United Kingdom (it still hangs on Burlington House, London and worth a visit). Smith’s map is the outline that would be the data point from which channel makers and revolution industries would follow.

The map Smith created for these business leaders detailed the best routes and where the mineral deposits would be. Smith turned data into information, which led to even more advanced engineering.

Today, data collection is considered one of the top three skills cartographers need to have. Modern business is no different, many organizations collect data, but they lack the ability to design that data into a map that can help the organization navigate its vertical market or potential disruptions to their market.

In recent years, the ability to collect and store data has become easier and less expensive thanks to enterprise cloud computing. However, collecting data does not always unlock actionable insights. A physical map does not detail, for example, the number of trees in a forest. These would be excessive data levels; instead, a form of forest as a landmass is depicted. The color and symbols inform the map user that it is a forest, giving them an instant insight into the type and size of the obstacle they are facing. Consequently, the map user is able to make more informed decisions and follow a course through or around the forest.

CIOs must therefore ensure that their teams and the company have a good foundation in data engineering. This will map their business journey – or the customer journey when transacting with your organization.

Knowing the size and composition of an obstacle facing the organization, the company is able to respond, often in real time, to changes in customer behavior or regulatory requirements. CIOs with a well-defined data engineering base for their operations have been able to respond to pandemic lockdowns with greater efficiency than those with data but little information. Armed with a data set and an engineering strategy, organizations are able to understand business behavior and, therefore, model changes in that behavior when faced with challenges such as that demand remote work.

Data engineering in an organization breaks down silos and therefore prevents a team from gaining insight that colleagues in a different department or market cannot access. With an engineering data set, organizations are able to easily identify where opportunities exist for improving efficiency, productivity and profitability. Data engineering benefits the entire organization; the most successful organizations design data and then democratize that data across the enterprise. If everyone in the business has access to the same map, they can use it to visualize their journey and see where customer bottlenecks and pain points are. The map then allows these frontline team members to work with their colleagues and the leadership team to describe and correct that challenge. The ultimate beneficiary is the customer, which of course benefits the organization.

So the next time you’re keying a postcode into your sat nav or checking the location of a nearby restaurant online, consider the data and engineering beneath that map, then ask – can – do we as an organization make our data visible and usable at this level?