When it comes to business, the concept of maturity can have many implications. A mature company may be one that has an established vision, mission, workflows and operations. Such organizations have done everything from mastering a continuous improvement process to creating a successful revenue cycle. Analysts have built charts, indices and other tools to measure this concept of business maturity.
However, in today’s increasingly digital world, the ability to collect high-quality, relevant data and be able to access and analyze that data to drive desired business outcomes is becoming a foundational aspect of enterprise maturity. Businesses must be able to use data to accurately diagnose problems, identify opportunities and find solutions quickly enough to execute against them in real-time.
C-suite executives can examine the 3 Ds of enterprise maturity and agility to determine where their organizations fall on the continuum and to map a direction for the future.
Starting at the most basic level, an enterprise must evaluate its current data, where it comes from, how reliable it is, and whether it’s easy to access in a usable way. Gartner’s 2020 Magic Quadrant for Data Quality Solutions report discussed the fact that substandard data quality costs businesses nearly $13 million per year.
Companies must begin by ensuring that they have a single location, or a data lake, where all quality data can be stored and accessed. Once that location exists, a process for gathering, assimilating and scrubbing data must be created. It’s imperative that the data be high quality and accurate; as soon as someone trying to use the data begins to distrust it, the entire system is in danger of collapsing.
The next stage of data maturity revolves around access. Having high quality, reliable data is of no use if business professionals cannot access, understand, analyze or use it in a way that drives business decisions on a daily basis.
Consider that the typical process in many companies today begins with business professionals struggling with a problem. A request is sent to a data analyst who may spend several days, or even weeks, searching for the right answer. By the time the cycle is complete, the question may no longer even be relevant.
The most mature data system allows companies to search, find, understand, access and analyze accurate data to go from question to answer immediately.
Hypersonix offers Jarvix, an Alexa-like virtual assistant, that’s ready and waiting 24×7 to answer the business professionals’ questions. Using natural language technology and built on a solid foundation of collecting and organizing the right data, Hypersonix delivers a mature data system for a wide range of customers.
Working in concert with a maturing data storage, collection, and analysis system, companies must move up a five-level continuum of making more mature business decisions.
At the first level, organizations must determine if they can make business decisions at currently desired intervals. For example, a board of directors may want an annual performance report or an internal audit team may require a monthly inspection report. Companies that can meet these basic requests with high-quality and trustworthy data will facilitate high-level decision making.
The second level raises the bar, challenging the business to make more frequent decisions, either increasing the intervals from something like quarterly sales reports to monthly ones or, better yet, making decisions as soon as a business need arises. Organizations that can automate some aspects of decision-making, such as triaging the type of customer support that may be required in a call center, can begin to move further along the enterprise maturity continuum.
Stepping up to the third level introduces the ability for businesses to predict the results of potential future decisions. For example, a retail store manager may want to test out various what-if scenarios about holiday pricing and promotion strategies before actually making a decision. A mature data-driven system that can assimilate historic, market and competitive information for that particular location may be able to accurately predict the results of such decisions.
The fourth level of maturity allows organizations to make a mid-campaign course correction with accurate, real-time data. For instance, a company that chooses to run a promotion one week suddenly realizes that expected outcomes are not being realized. Data shows that an error was made or an unexpected event such as weather has affected outcomes. Mature organizations will be able to revisit current data and determine the best course correction, whether that be to halt the promotion, shorten the campaign, or simply tweak the available products to improve outcomes.
Finally, the fifth level of maturity brings the company to the point of broadening its vista, asking what decisions that were previously unimaginable due to system constraints are now possible. This level of maturity has the potential to accelerate business growth, market expansion and customer success to yet unseen heights.
The final “D” in enterprise maturity and agility has to do with the level of digitization available to an organization. This revolves around the ability of a company to automate and digitize programmatic actions or outcomes quickly and efficiently.
(I want to open this section with what a less-mature enterprise may be doing. Not sure if this is correct, but hopefully, it gives you an idea of what I’m looking for.)
Beginners in this aspect of maturity may be struggling with mostly manually made decisions, for example, examining reports that drive business decisions for the upcoming month or sales cycle. No programmatic systems yet exist to automate decision trees.
A more mature company may have created automated systems that can make some basic determinations before a business professional even gets involved. For example, a customer service center suddenly receives an influx of troubleshooting calls, which are flagged as out of the ordinary. A mature digitized system may be able to determine if there are particular patterns, such as calls coming from a particular geographic location or related to one category of products.
The system can automatically analyze historic and current data to come up with some possibilities, which can then be sent to the appropriate division for resolution. For instance, perhaps IT is tapped to resolve a DNS entry problem for a particular geography or a call center representative can be alerted to the fact that the customer on the line had a colleague make account changes the day before, locking certain aspects of the account.
Digital maturity automatically finds issues and suggests resolution, helping to make the business professionals’ lives easier, more rewarding, and more productive.
With all this discussion of data and decision maturity, it’s important to turn the focus for a moment back to the company’s workforce. Individual managers, employees, contractors and others must be dedicated to creating a data-literate organization for enterprise maturity and agility to come to full fruition. According to a Tech Target article, nearly two-thirds of companies say they experience employee resistance to making data-driven decisions.
The people working with, accessing, and using the data must truly appreciate the value of the organization’s data and the possibilities it affords. Fostering a culture that respects the power of data as well as one that will help continue building that data into the future allows a business to truly harness data for ongoing, comprehensive, organization-wide decisions making.
Businesses that make a conscious effort to move up each of these 3Ds of enterprise maturity and agility will secure a more competitive position within their respective industries. Every organization has the opportunity to revisit its culture and be creative about creating an ambitious customer experience. It’s time to embrace data, decisions, and digitization and step up to a new level of success. What’s your digital ambition?