What’s the #1 enemy to profitable machine learning, AI & data-driven initiatives?
Dirty data.
And who has had data on their agenda for a decade but are still not deeply involved in data projects?
The CEO.
In a 2019 Deloitte survey, 63% of executives (including CEOs) say they are not comfortable accessing or using data from their tools and resources.
Clearly, a CEO’s involvement in a data-driven organization is important. Very few CEOs realize this. In this piece, I’ll cover why data quality matters, why the CEO has to be at the forefront, and how he/she can be involved in the process.
Let’s dive in.
What is Data Quality & Why It is the Foundation of a Data-Driven Initiative
To be data-driven, an organization must have data it can trust. To get data it can trust, the data itself must meet data quality benchmarks. It must be complete, accurate, authentic, up to date, relevant and clean. Data quality, therefore, is a critical process that acts as a foundation for future data-driven initiatives.
Whether it’s for analytics, for machine learning, for system migrations or AI, the data source needs to be clean from common data errors. Novel sources of data, challenging formats, or raw streaming data are some of the types of complications in data that results in poor data quality. Regardless of the business or industry type, bad data can wreak havoc.
A hospital, a bank, an insurance company, a retailer without a data quality process or solution in place suffer significantly with the consequences of bad data. Imagine a hospital with invalid patient records. Imagine a bank with duplicated customer records. There are plenty of examples where bad data has affected an organization’s operational processes, their reputation, and their credibility.
Bad data cannot be ignored.
And the only person who can emphasize on the need to take data seriously is the CEO.
Why Does the CEO Need to be Involved in a Data Quality Project When There are Other Executives to Take Care of the Matter?
CEOs know they need their organizations to be data-driven because it affects customer focus, employee empowerment and strategic decision-making. Knowing is not enough. CEOs must act. They must not leave it up to CIOs or CDOs to single-handedly manage a project that impacts business processes. The CEO must be involved in the monitoring and implementation of organizational-wide data quality and data governance policies and practices. Some key reasons for their involvement would include:
Allocating the Right Resources:
A data quality initiative involves purchasing of solutions, hiring of talent, consultation with experts, and much more. All of these decisions depend on the CEO. If he/she is not directly involved in the project, they may end up making poor budget and resource allocation decisions. They may inadvertently become bottlenecks and prevent the project to come to fruition.
Ensuring that Compliance Regulations are Met:
In an increasingly data-driven world, data compliances are getting more complicated. Regulations are complex and the resultant penalties are harsher than ever. It is here that the CEO’s attention would be required to ensure that compliance rules are met through consistent data handling practices across multiple business units.
Data compliance problems usually occur when the company does not have a data quality framework in place. For example, an organization may get hit with a hefty lawsuit if the marketing team accidentally sends promotional campaigns to the wrong audience segment. The CEO’s lack of involvement in data governance can be costly.
Optimizing the Organization’s Operational Efficiency:
Marketing, sales, account, HR, finance, support are all key departments that rely on data. The employees within these departments need data they can trust to do their jobs right. Data quality directly impacts an organization’s operational efficiency.
So while employees are often encouraged to take ownership of data, the CEO is equally responsible for ensuring that a data quality solution is implemented across the board. This may involve identifying and purchasing the right data quality solution and training employees on data handling. The rule is simple – clean data makes everyone’s job better and easier.
Changing How the Organization Manages its Data:
Is the data stored in silos? Are there multiple but inaccurate versions of the truth? Is consumer data duplicated in each of these siloed sources? These questions form some of the most basic concerns when it comes to data quality management.
Most CEOs I’ve worked with are unaware of how data is stored, handled, managed, and processed within the company. The lack of a data governance process contributes to this knowledge gap, making it difficult for the company to get accurate & strategic insights. When this knowledge gap is removed, the CEO will be in a better position to implement data management policies & bring about a new change.
Building a Data-Centric Culture
Cultural change happens from the top. If the CEO implements data governance policies and takes a strong initiative in building a data-driven culture, it sets the expectation for the company. The CEO’s investment of time and effort in driving initiatives will pave the way for a data-centric culture.
Decisions will be made on reports and analytics rather than on guesswork and assumptions. Insights will be derived from real-time data rather than on the previous year’s data. Teams will be able to demonstrate the link between data and business outcomes.
How Can CEOs Involve Themselves in the Process?
Ask any CEO about being data-driven and they will share grand ambitions of digital transformation, AI and ML – but ask them how they are being involved in the process and they may fumble with the right answer. Luckily, it’s not that hard. Here are three ways CEOs can involve themselves in the process:
Set Up an Educational Program for All Levels: Data quality is an organizational-level initiative, every senior leader from every department must be given the necessary educational program that explains why the organization needs to focus on data quality, the consequences of bad data and how data quality can be achieved.
Form a Data Management Taskforce: Form a data taskforce and be part of regular sessions or meetings to decide on vendors, consultants, talents and the resultant business or project outcome of these decisions.
Make Data Management a Business Process: For long now, data management has always been siloed away as an IT headache. Business leaders know they can’t rely on their data, but they don’t know what exactly is wrong with it. For example, they don’t know that customer data record is being duplicated across multiple departments by various people. They don’t have a business process to handle data. It’s imperative then for the CEO to shift data management from being solely an IT department ‘s responsibility to business leaders of key departments. Data quality is a matter of the whole business.
The Bottom Line
Technology is dependent on data and clean data is dependent on the people involved. It’s not enough to purchase a tool or hiring a BI analyst to clean data. It’s an organizational responsibility and the CEO leads this change at the forefront.
