How IT is Like Painting the Golden Gate Bridge – and What to Do About It
There’s a common misperception that the Golden Gate Bridge has to be repainted every seven years. In actuality, the painting occurs continuously to protect the 1.7-mile steel span from the corrosive effects of salty air, roadway pollutants, age and the sun.
That means that, on any given day, teams of workers must brave those famously cold winds blowing into San Francisco Bay from the Pacific Ocean to apply fresh coats of International Orange to the suspension bridge’s 746-foot-high towers and sweeping cables. It’s a Herculean task costing hundreds of thousands of dollars and untold hours each year to keep the circa 1930s marvel so beautiful.
In many ways, information technology (IT) operations are a lot like that. Chief Information Officers frequently bemoan the fact they spend far too much time and money maintaining old, outdated and barely functional systems left to them by their predecessors. Indeed, operating costs made up approximately 71 percent of IT budgets in 2017, according to Gartner.
The trouble with focusing so much attention on all of this “technical debt” is that CIOs can’t spend as much time as they would like on innovation, which is why many are considering cognitive automation.
Cognitive automation leverages artificial intelligence (AI) and machine learning (ML) to sift through vast amounts of data located in various digital locations. It then indexes and analyzes that information to predict outcomes, make recommendations and even handle many time-consuming repetitive tasks.
In IT terms, this technology effectively allows enterprises to automatically streamline processes, monitor for potential breakdowns, apply fixes and more efficiently facilitate the flow of accurate and actionable data throughout companies. More to the point, it permits CIO organizations to offload maintenance work to machines so they can spend more time doing what they do best – which is innovating.
Unfortunately, many CIOs think they are already doing that by digitally transforming. But what is digital transformation really? Arguably, it’s taking something old or physical and migrating it the cloud, which feels innovative. And make no mistake, such efforts are vitally important for any organization hoping to survive and thrive in the 21st century. Yet, it’s about as innovative as moving your decrepit college furniture around and saying it’s all new. Little has really changed. No matter how many times you rearrange things, you’re still only making the best out of what you have. You’re servicing technical debt.
To rise above that, you must change how your business works, operates and reaches decisions. And it all starts with recognizing and acknowledging the differences between technical debt and true innovation.
If you find yourself saying, “we have a data quality problem,” or “our data is so siloed we can’t do what we want with it,” or “we first have to upgrade existing systems and software to newer versions,” you are making technical debt excuses. Ditto that if most or all of your staff is buried in ERP, CRM, data lake, cloud migration, digital transformation or similarly hairy projects. What all of these statements say is you’re over-committing your resources to years-long efforts. Like repainting the Golden Gate Bridge.
What you should be doing is deploying AI and ML technology to service that technical debt more efficiently so you don’t have to. For example, if government transportation authorities could come up with a more weather resistant version of International Orange, they might not have to employ so many painters to maintain it as often each week. Instead, they could reallocate those workers and funds to accelerate other promising innovations, such as building underground roadways, smart roads and high-speed magnetic railways systems. Similarly, if you viewed AI and ML as your improved “paint,” you could focus on other emerging technologies that might help your business do a better job of tracking and understanding customer sentiment in order to provide them with differentiated brand experiences.
CIOs can also utilize cognitive automation to help their companies anticipate, address and stay digitally fit in the face of volatility, uncertainty, complexity and ambiguity (VUCA). This is a critical capability because 90 percent of enterprises have had to confront disruptions – such as operating cost pressures, political upheavals, leadership turnover, and adverse regulatory interventions – that affected their businesses, according to Gartner. Yet only a quarter were “fit enough” to come out ahead in the end.
The fittest of companies deploy technologies such as cognitive automation to ensure they don’t let opportunities slip through their hands like grains of sand. For instance, the larger a company gets, the more difficult and time consuming it becomes to balance supplies with demand. Ideally, you’re tracking needs for all of your products in every market you serve at a granular level. But if you want to watch 12,000 products in 40 countries, 50,000 cities and 5 million zip codes, it’s really not humanly possible. To cope, companies manage supplies regionally. This works to a certain extent. But it does not allow them to stock up to meet actual in-market demand. Nor does it grant the ability to send products just-in-time to warehouses and markets in need rather than to storage facilities and areas where there isn’t a need.
With cognitive automation, CIO organizations can step outside of their normal IT boundaries and take on broader, more strategic responsibilities within their organizations. It gives them the time to do so and helps augment decision making to overcome technical debt and spur innovation.
You don’t have to continually paint that bridge. By applying a new kind of paint – cognitive automation – atop legacy systems, it’s possible to alleviate any shortcomings and help your business become technically fit. It just takes a desire to shed old habits – and the ability to focus on the true meaning of innovation.
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