CIOs see a tsunami of data on the horizon.
The proliferation of endpoint devices combined with systems of record and other applications continue to pump up the volume of data available to organizations. That raises the stakes in terms of storage, management and security, as well as the pressure to realize the potential value of all that information.
At times like this, it's helpful to remember that as problems go, abundance is generally a good one to have — even if you're dealing with a superabundance that causes headaches in the short term.
To get a sense of the scale of the data-wrangling challenges, consider a few numbers:
- There are already billions of connected IoT devices delivering data — but in just a matter of years that's expected to become trillions of devices.
- 71% of CIOs say the explosion of data produced by cloud-native technology stacks is "beyond human ability to manage," according to a global survey of 1,300 CIOs and senior IT practitioners conducted by Coleman Parkes and commissioned by Dynatrace.
- 59% of CIOs say that without a more automated approach to IT operations, their teams could soon become overloaded by the increasing complexity of their technology stack.
These challenges are only exacerbated by the ongoing difficulty of attracting and retaining IT and data science talent.
So, the question is, what can CIOs do to not just cope with this data surge, but turn it into a source of power and a strategic advantage — the way a hydroelectric dam turns a flood of water into electricity?
Turning the Tide with Smart Data Management
Here's one saving grace: Although the incoming data is complex, managing it doesn't have to be. New data management tools are being designed with the capabilities to help you rise to the challenge.
What that means is that if you keep up with the technology, you'll be able to keep up with the flood of data and harness it to help you achieve your business goals.
We're talking about a fundamental change in the way businesses use data — a transformational shift in the relationship. Instead of just using data to tell you what's already happened, you'll be using analytics-driven insights to predict what's about to happen, so you can put the right strategies in place ahead of time.
A key part of enabling this vision is the effective deployment of AI and machine learning.
- A survey by MIT Technology Review Insights of 600 global C-suite executives, including CIOs, found that well over half of executives expect AI use to be widespread or critical in business functions by 2025.
- More than three-quarters (78%) of the executives in that survey said that scaling AI and machine learning use cases to create business value was their top priority for enterprise data strategy over the next three years.
Among their many other uses, AI and machine learning tools can help with managing infrastructure through capabilities like auto scaling, auto healing, auto optimization and more.
Strategic Considerations: The View Is Worth the Climb
Here are three principles that should underpin your vision for digital transformation:
- Data Centricity. Making data centricity a core value — which means breaking data out of its silos and putting it at the center of your business, rather than thinking of it as merely another resource you make use of — is key to realizing the transformative potential that data-driven technology can deliver, especially the advanced analytics capabilities of AI and machine learning.
- Data Democratization. A related important idea is the democratization of data: Rather than thinking of data as something arcane that only data scientists and IT professionals can understand and access, data and analytics insights are accessible to and used by team members throughout the organization.
- Removing Barriers. Effective deployment of low-code and no-code software such as that available in Power Platform can further boost the ability of all team members to contribute their creativity and ingenuity in ways that propel your business forward.
[h2] The Rewards of Getting It Right
Although there may be some short-term pain in realizing this vision, the payoffs are substantial enough to make it more than worth an IT leader’s time.
√ Centralization. By getting your data into a state-of-the-art cloud ERP system such as Microsoft Dynamics 365 Finance and Supply Chain Management, you centralize and democratize it, so that everyone is working from a single source of truth and can access the value that clean, accurate data can deliver.
√ Unlocking the predictive value of data. Accomplishing the above means you also make it possible for AI and machine learning to identify patterns in the data, enabling everything from predictive maintenance to better sales forecasts and the ability to detect important shifts in customer behavior and respond with greater speed and agility.
√ Automation. With the ability to automate repetitive everyday tasks, you'll be able to free your team members to focus on higher-level tasks and compensate for labor shortages.
√ Data security. Security concerns are on everyone's mind thanks to the uptick in data breaches in the past few years. Choosing the right data management solution allows you to put security concerns at the forefront, and make sure your protective systems and procedures are up to date and ready for current challenges, as well as what's ahead.
Eyes on the Future
Good data management and robust cloud-based analytics will be required to prepare for the biggest coming trends of the next few years — including Web3, augmented reality, mixed reality and the metaverse.
Although many are understandably still hesitant about embracing these still-in-the-oven technologies, you don't want to be left in the dust, either — and that requires doing the homework and laying the data management foundations now, so that you'll be ready to take advantage of new capabilities and opportunities as they appear on the horizon.
Put simply, prioritizing data centricity and democratization gives you the footing you need to set and pursue bold new goals, rather than getting stuck in catch-up mode as you're held back by the limitations and liabilities of legacy systems
Get Your Data House in Order
To start, you need a thoughtful and well-vetted data management strategy in place. It needs to encompass everything from data governance to data warehousing, analytics, security and more.
Avoid these pitfalls along the way:
- Sometimes getting your data into a structured form is a bigger challenge than expected — especially if the data is coming from disparate sources and platforms with conflicting formats and/or gaps in record-keeping.
- Data regulations are getting stricter all the time and need to be navigated with diligence and expertise.
- The costs of data storage are going up. Figuring out what data to keep and how to keep it in the most cost-effective way is critically important.
The bottom line is: You can't solve tomorrow's problems with yesterday's technology.
But the good news is you don't have go it alone as you get your data house in order. Getting expert guidance from experienced veterans in architecting data management solutions can not only lighten the burden but strengthen your confidence that you're on the right track and fuel your progress toward key milestones.
At Columbus, we're ready to help you develop and implement your plan for digital transformation — and we'll be by your side every step of the way, from planning through execution and troubleshooting, to help you get the most out of what modern data and analytics tools have to offer.
Want to learn more about how Columbus can help you tap into the transformative capabilities of AI, machine learning and cloud-based analytics technology? Get in touch with us today.