More than any other C-suite executive, the CIO plays a key role in the decisions around emerging intelligent technologies.
The concept of Cognitive Automation typically piques some interest in C-suite executives, but rarely ever to the magnitude that it touches the CIO. Leading the way when it comes to the company’s long-term technology strategy and infrastructure design, CIOs have an insider view into the challenges companies face when they try to extract valuable insights from their data--and maximize ROI and resource allocation at the same time.
For Cognitive Automation to solve the technical issues organizations today are facing, CIOs must:
Sometimes, real-estate investors conclude it is better to tear an entire house down and rebuild from the ground up, rather than fixing existing problems. Similarly, a CIO might reach the same conclusion. However, it’s not that simple (although building an entirely new technology infrastructure for a large company is rarely, if ever, described as “simple”).
To implement Cognitive Automation, project leaders must achieve buy-in from other stakeholders. Part of the challenge is the fact that humans don’t like change—especially radical change. In addition, organizations tend to have at least some reliance on their current systems and processes, and this reliance is reinforced when those systems and processes serve their purpose.
Because of this, a Cognitive Automation system should be able to sync with existing systems; it should have the capability to crawl and explore different technologies, translate and disperse learnings throughout the system, and give insightful responses and feedback. This can usually be achieved by strategically overlaying the new system on top of the existing one. The technology team must invest as much time as necessary to ensure the integration works seamlessly.
One major issue IT departments consistently face is underutilizing the highly talented and knowledgeable individuals on the team. Although not done purposely, it’s very common for technology teams to be offloaded with mundane system tasks that are a result of a poor infrastructure. And all too often, the needs of non-tech executives and managers don’t align with the way the system was designed to function.
A successful adoption of Cognitive Automation results in technology workers being used in ways that maximize the value they can provide. Organizations will need to upgrade their visions of each role, i.e., data engineer, business analyst, data scientist, etc., or just help create the environment in which each person has the space and support to take a more strategic approach to work as initially intended.
When strategizing how to begin using Cognitive Automation, CIOs should work with organizational leaders to determine the most pressing business needs. Outside of this, starting with functions that feed into other processes is ideal.
For instance, working on a project that results in the system being capable of showing inventory numbers in real-time will make it easier when your focus shifts to having the system provide real-time financial statement data based on different scenarios. Inventory and cost of goods sold affect financial performance significantly, so finishing the first project would place the company several steps ahead towards finishing the second one. It’s akin to freeing two birds with one key.
Fully adopting Cognitive Automation and the mindset that comes along with it will always shake up an organization. It’s important for technology leaders to understand this and embrace the spirit of flexibility--there will likely be pain points along the way, but it’s essential organizations have someone who leads the way.
The Cognitive Automation mindset is all about getting rid of waste and manual tasks that can be completed by computers so resources can be rechanneled into other areas that will radically transform the way decisions are made. The future of decisions is Cognitive Automation. This means certain reports managers once “relied” on, but were really slowing them down, can be discarded. Positions may even need to be eliminated or rewritten to align with the new needs of the company.
This isn’t a one-time challenge. Companies must remain flexible going forward. As Cognitive Automation technology evolves and learns from historical decisions and data over time, needs will continue to change. Ideally, output will grow, recommendations will get better, and functionality will soar. For a company that begins its Cognitive Automation transformation today, there’s no way to predict exactly how high its performance will increase over time--but Cognitive Automation experts will agree it is exponential.
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