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The following list outlines the key CIO Priorities for 2023. Any organization looking beyond six months without using scenarios to guide their visioning risks facing poor forecasts amid multi-vector volatility. Once you read the list, you’ll see these concerns will drive action far in the future and prove plenty to keep even the most adept CIO busy for the next six months.
A few months ago, labor shortages and skills mismatches dominated many headlines. And now the headlines lean toward labor reductions. Don’t be fooled. Good IT talent is still hard to come by. Businesses that need capability should snag talent when they find it but should be careful in overbuilding capacity. Keep consulting relationships in play to grow and contract based on realities on the ground.
Consider how you design your IT talent experience effectively onboarding people, help them quickly find their place and their path to value, and work in a way that makes sense to them and to the organization’s need for structure and reporting.
Many organizations broke their social contracts with IT when they outsourced entire functions. The cost savings, if not actually direct, seemed to go to senior leadership salaries and bonuses as often as in other places. Trust eroded. Taking care of oneself in a hybrid organization is a normal reaction. The best organizations will try to rebuild trust, but CIOs can only represent the truth of their company’s actions; they probably can’t change them.
Recessions typically prime disruption. This recession is likely to do the same. One area to look for is the shift away from the “cognitive” aspects of AI toward the data used to train it. Over the last couple of years, I have been working with Singularity DE in Lisbon, Portugal, on how organizations prepare themselves to be more data-driven. See our book on becoming data-driven on Amazon.
While AI can add value to data, it isn’t the only path toward wringing value from data. Data monetization points in one direction, but more importantly, seeing, and therefore, being able to manage a business at a much more granular level also comes from an improved understanding of data.
Most organizations remain awash in data with little understanding of what it means and, accordingly, how to apply data to gain insights about employees, operations, engineering, logistics or any other function. They may experience some great point insights if, for instance, they concentrate on customer data, but other data often receives less focus and therefore returns less value.
Organizations should consider two efforts in early 2023. The first is to increase the data competency of their teams. Everybody. DBS Bank in Singapore recently trained over 16,000 employees on big data and analytics.
DBS sought to enhance their employees’ ability to:
This suggests that organizations should think about data across multiple dimensions. Don’t just look, for instance, at cost savings or operational efficiencies; also look to employee engagement and environmental impact. Inexpensive solutions that get the job done at the cost of employee engagement or a negative effect on the environment are also accounting problems; they just use different metrics as proxies for future financial impacts.
The second effort extends that knowledge through empowerment. Let departments and functions explore their available data and see what they can glean from it. The results will not be great early on, and they will certainly point to holes in data strategy and management, but those are revelations that, if worked through, can prepare an organization to exit the recession as a disruptor, not just a survivor.
Finance is coming for parts of your budget. If you can’t defend it, you will lose it. Now is the right time to shore up reporting on successes and value.
CIOs should employ both arrows in their budget defense quiver. First, get the accounting right. Focus initial data-driven efforts on understanding where IT spends money and its returns. Develop indisputable accounting practices that leave finance answering questions about why they are bothering you rather than you rushing off to answer their probing queries.
Second, tell better stories. IT notoriously thinks that technology’s impact is obvious and that data about that impact will save them from scrutiny. As too many recent political examples prove, data often fails to convince. Stories on the other hand that connect the people impacted to the value of the tools and processes provided can sway people to remain or become supportive, because the value no longer focuses on justifying investment but in seeing their own success reflected back.
I once implemented a lessons-learned system on some pretty primitive technology when much better technology was available. Using the most advanced chat and search technology wasn’t the clincher for further investment. Engineers shared stories about what they learned from each other and the impact of that learning. Those stories proved a powerful attractor of continued funding.
One of the other disruptions coming out of the next recession might be a deeper call for sustainability. Like ESG or not, some or all aspects of it will likely influence business decision-making going forward, even if the acronym eventually falls apart.
Sustainability readiness should derive from budget and data-driven design. Those organizations will learn how to measure the environmental impact of their investments, and if they work diligently, perhaps the social aspects as well. Data governance policies well implemented and precisely managed will go a long way toward IT delivering on its governance commitments.
Digital transformation seems like a thing that can be done, then done with. It isn’t. Digital Transformation is what all organizations are doing all of the time and will continue to do in the future unless we regress to running organizations with wooden carts and the abacus.
So stop talking about digital transformation. Every organization is already doing it. What they don’t do well is continuous reinvention, which requires agility. And I don’t want to call it Digital Agility because that is just a stupid phrase. Agility means being able to adapt quickly. Agility also includes a smattering of resilience because it’s hard to be agile when you’re dead.
Unlike Digital Transformation, Agility involves all of the concepts that push back against successful Digital Transformation, like culture and budget, silos and data access. Agile organizations seek to meet needs where they are and work through issues holistically rather than with a technology-first mindset. If the blocker for digital transformation is a cultural issue about who can see data, then digital transformation stalls.
Agility-focused organizations can take up the power issue separately without tying it to any win or loss of a big project. Call out the problem and fix it, and once the dust settles, figure out automation, sharing, dashboards or whatever else will enhance the area now that it’s free from autocracy. Avoid pretending that technology is a lever to change behavior—find the right lever to change behavior and then talk about what technology can do.
The bottom line: keep figuring out what to do and what not to do, and do the things that make better sense, using the tools best fit to support those choices—not the most modern or the newest and coolest. Lead with improving the business incrementally on multiple fronts. The big project may bring focus, but it also runs the risk of making all things IT seem insurmountable, expensive, and massive when they don’t have to be.
Work from recognition of where you are and what you can do with things as they exist, rather than waiting for other investments to complete or payoff before taking action. By the time the big Data Lake project completes, you may find dozens of lost opportunities that could have returned tangible value had they not been put on hold waiting for the next big thing.
By the way, this also means that any thought of the current platform being the last and best should be put away next to Uarco printer rulers and removable hard drives. Tech company acquisitions will drive platform migration as organizations seek to consolidate data access and leverage business synergies—and platforms will not stop evolving.
Today’s platform leaders will likely be yesterday’s platform leaders because all of the past platform leaders are, well, past platform leaders. IBM and HP, for instance, are still around, but they are not the same integrated enterprise companies they used to be, as they spun off large portions of their portfolios to the likes of Kyndryl and HPE.
I used to run manufacturing systems on Burroughs B1800 and DEC Vax hardware with systems like Ask ManMan. I migrated from HP ManMan to DEC ManMan—which were very different systems on different platforms. We considered ourselves digital already—we were not transforming; we were transitioning. Gone, too, are Lotus Notes, Novell Netware, and other systems that large enterprises once relied upon. Something will eventually challenge SalesForce as it did Siebel and SAP.
One aspect of managing with agility is not getting too attached to your tech. For innovative looks at mid-size solutions that might scale, look to companies like Sage, Monday.com, Hubspot and Apptivo.
Big tech regulation will likely also rekindle, forcing organizations to keep track not just of competitors but also remain agile amid global movements to regulate data, privacy, and technology reach.
Read more from Daniel Rasmus at Serious Insights
Daniel W. Rasmus, the author of Listening to the Future, is a strategist and industry analyst who helps clients put their future in context. Rasmus uses scenarios to analyze trends in society, technology, economics, the environment, and politics in order to discover implications used to develop and refine products, services and experiences. His latest book, Management by Design proposes an innovative new methodology for the design workplace experiences. Rasmus’s thoughts about the future of work have appeared recently in Chief Learning Officer Magazine, Government eLearning!, KMWorld and TabletPC. A wildly popular article on CIO,com titled, 10 Lessons from Angry Birds That Can Make You a Better CIO, went viral on the Internet.
