Data makes today’s world go round.
I was enthused to join data and AI trailblazers at the 2021 CDO and Data Leaders' Global Summit, a one-day virtual event that took place on May 5, 2021, with discussions from over 90 senior and C-level data and analytics leaders across the globe.
My role as the chief data and AI officer at Omnitracs is to harness the vast amounts of data across our many products and applications and deliver value to our stakeholders in terms of insights and intelligence. That was one of the main focus areas I expanded on as a panelist in the session, Data and Analytics Best Practices: Establishing a Data-Driven Culture. In the session, I was part of a panel discussing experiences and best practices on leveraging data to identify opportunities, overcome challenges, and drive value. Let's explore.
Pinpointing pain points to identify opportunities
Listening to stakeholder challenges and business case needs is the optimal starting point involved in connecting your data strategy to business and technology initiatives. My team and I are focused on understanding the stakeholders and their motivations and pain points regarding business value.
When the pandemic first hit last year, like the rest of the world, we were scrambling to figure out how to make sense of it and cater to our customers. As innovators enabling the transportation of goods across county and state lines, we were able to come to market and issue real-time alerts when a driver was entering a COVID-19 hotspot, giving our customers insight into the precautions and restrictions in at-risk places. This was a very high-value project done in a two- to three-week timeframe, and it served as an example of creating something fast and meaningful. We leveraged our robust data platform to launch this work. The technology piece is so important there as you add velocity through a standardized and reusable platform. This is an excellent example of where demand is also growing. People are not just looking for data opportunities; they're knocking on the door, showing how data democratization is quickly taking hold.
Overcoming challenges when aligning data and AI with business objectives
Regarding data growth, you want to be in a position where the volume of requests is high, and people are coming to you with tangible business goals. Once you have these ideas, it's essential to prioritize them based on need and business value. When you have the prioritization in place, you need to ensure you have access to high-quality data. Finally, you should incorporate the algorithms you want to apply to the data. Having a skilled data team well-versed in technology better ensures this multi-departmental effort is a success.
Compute capacity is another challenge. You can solve many problems, but you need the right amount of computing and storage to do that. In our industry, the intelligence at the edge (otherwise known as AI in the cab) when the driver is on the road is real-time intelligence, so compute capacity at the edge should align with the needs of the business.
We've also enabled other value insights and use cases, like real-time intelligence for safety, metrics around correct following distances, and driving alertness. We have to look at which major problem we're solving for the customer, whether it's safety, productivity, or another type of use case. Data is exponentially increasing, so we should continuously work with a use-case mindset.
Putting your data-centric culture together
The first component in establishing a data-centric culture recognizes that data is our specialization as data professionals. The rest of the world doesn't speak our language because it's such a specialized domain. That's why it's our responsibility to speak the language of the business and tie our data initiatives with those objectives, helping our stakeholders understand how we can deliver value to their business. Communication is vital to whatever we do. We need to speak the language of the business with employees on all levels and talk about successes and challenges while remaining transparent. This builds trust and facilitates the data culture we want to create.
Additionally, there's been a vast and recent push for digital transformation, which is loosely defined as business integration of digital technology, across industries. Digital transformation is an excellent opportunity for the data piece to be a change agent. You always have to make sure you're hitting all the levels and meeting your team members where it's appropriate for them to be involved in understanding your efforts and their roles.
Respecting privacy and limiting roadblocks
Utilizing customer data is all about trust. Customers need to trust you with their data and make sure you're adhering to regulatory and privacy constraints. There are different elements involved in earning and keeping customer trust, but it starts with meticulous data governance. You must have an understanding of regulatory and contractual obligations.
At Omnitracs, we have a rigorous data governance process. It's all about delivering value to our customers. From an edge intelligence perspective, if we can enhance safety and productivity, we are helping our customers find ways to leverage data and make use of insights that they can use in real time. All of these elements are a balancing act, no doubt. You have to deliver value and ensure customers are confident you're treating their data right.
Understand what's truly happening across your operation with Omnitracs Data and Analytics solutions so that you can achieve business intelligence in the digital age.