Data Is The New Business Fuel, But It Requires Sound Risk Management
Morgan Palmer is CTO of ETQ, helping customers achieve success by attaining new levels of excellence through quality for over 25 years.
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In 2006, mathematician Clive Humby coined the phrase “data is the new oil.” Since then, it’s taken off like wildfire. Today, data fuels business actions, customer experience, new healthcare discoveries and fundamentals in every conceivable industry.
I was thinking of the phrase recently when I read an article in the Wall Street Journal written by Marie Leone of Deloitte Insights. The article focuses on the need to safely leverage the power of data. Just as oil has extreme value to the world at large, keeps our homes warm and keeps transportation systems running, actionable data keep businesses functional and fuels their growth forward. Yet, as the Deloitte article says, “To build and maintain trust, organizations need to demonstrate that they are responsible stewards of their customers’ and employees’ data and that they are carrying out data gathering responsibly.”
As companies increasingly drill for new sources of data and use it to fill data lakes that empower predictive analytics, AI and other smart decision-making digital tools, they need to take a strategic approach to its safe, ethical and effective use. Not only is data privacy and transparency becoming important in e-commerce, it’s also essential within business enterprises and their ecosystems.
Below are key considerations companies need to keep in mind in order to reduce data risk and ensure the safe, strategic and fair use of actionable information:
Ensure transparency each step of the way.
While consumers are concerned with how their personal data is gathered and shared, business users and customers are equally concerned with how data is collected. From employee behaviors on the manufacturing floor to customer call center complaints, whenever specific information is gathered, companies need to make it clear that this is taking place and for what intended purposes.
Break down the silos, but keep the departments.
Likewise, while it’s important to remove the silos between corporate functions in order to share data enterprisewide, it’s important to identify where specific data came from so you can trace its lineage and address any questions directly with the owner. It’s also important to include cautions on every dashboard that data should be used and shared with discretion—internally and externally.
Identify the problem first and create scalable data solutions.
Once you understand why you need certain types of data, it’s much easier to home in on exactly what you need. If sales for a specific product are declining, you might want to start with your own quality data and then review data on external suppliers if needed. Data risk is better managed when you can harness what you need to get to the root cause. Managing quality data requires scalable data management solutions that can ingest data from many sources such as the shop floor, inventory, customer complaints and sales.
Ensure data security when it comes to remote work.
Today’s remote or hybrid work model poses a whole new set of security challenges. Many companies can minimize risk by leveraging a multicloud strategy, but the risk associated with malware or ransomware can compromise crucial corporate and customer data. Despite this, according to a report from Menlo Security, only 27% of organizations have advanced threat protection in place for all endpoint devices with access to company data. It’s crucial that companies deploy advanced cybersecurity software and also train employees on acceptable use of public or home-based Wi-Fi usage.
Keep bias out of AI.
While enterprise data provides the fuel that drives accurate AI, it’s important that data scientists ensure that bias doesn’t creep into the algorithms that are developed. Data should be analyzed to ensure that it is diverse and doesn’t lead to any decisions that could provide an unfair advantage to certain populations. As an example, AI that helps to determine the best suppliers to work with should be trained with diverse supplier data.
Consider supplier data risk.
Speaking of suppliers, it’s not enough that data has proper governance within the organization. This must be the case externally across suppliers, as well. It’s important to build visibility into the supply chain and ensure that suppliers also have a data risk management plan in place, along with security tools that can help flag risks and vulnerabilities in the external environment. On top of this, risk-sharing agreements with third parties can improve overall accountability.
Data may be the new oil driving effective decision making, improved customer experiences and brand reputation. Yet, as with all business drivers, it requires continuous oversight to ensure that it is secure, accessible, relevant and unbiased. It needs to be treated like the precious resource that it is.
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