Prior low-cost region strategies have expired their usefulness.
For the past several decades operation teams have sought getting their work done by leveraging the lower salaries and cost structures provided by working in parts of the world where wages are comparatively low. This push for efficiency moved call centers, back-office work and most of the world’s supply chains to developing nations such as Mexico, Eastern Europe, and China. Now, these strategies have come into question. Eastern Europe is seeing war on its eastern edge and experiencing all-time high energy costs. China has become a less favorable supply chain environment including the logistical logjam of shipping containers and ships waiting at sea.
Despite the current adversities, companies need to find a way to get their work done economically and accurately. Physical locations have their drawbacks as companies consider their options. Do they double-down in Mexico, which is certainly not immune from trouble? Other Asian or Central American countries? Do they invest in a setting up the infrastructure in brand new low-cost regions? Where is the situation stable enough to ensure the return on investment? Like the move to China back in the 90’s, this transition would take decades to reap any benefit. And along the way, who’s to say those choices wouldn’t present their own challenges.
Carve out contextual, non-mission critical work and move those tasks to emerging A.I. platforms. These platforms can be anywhere and everywhere you need them to be.
I’ve used Geoffrey More’s model of Core and Context with several operations teams. This is a powerful tool in thinking about where investments in resources are applied and then how to think about managing the team’s charter and direction. Team members that perform core and mission-critical work need to apply their time as much as possible to their main charter. Sales team members ought to be drumming up orders as much of their week as possible. Finance team members should be spending their time on matters that can make material difference to the income statement and balance sheets. Procurement and Supply Chain team specialists must be focused upon ensuring that in-bound material for use in finished goods is on-time and competitively priced. Distractions equal waste.
This is where the opportunities lie. How much of your team members’ time is spent doing non-mission critical, contextual work? I can guarantee you, it’s more than you think! Alternately, if companies could identify leakage and eliminate it, these key resources could spend on more strategic activities.
An example is the re-training a new colleague on a process that was previously learned by someone leaving the team. New A.I. tools learn tasks once and forever and will even self-improve them over time. Once learned, they never go on vacation, have a sick day or make a goof. The next level is to integrate new best practices from other companies that had similar problems and found better solutions. At the tactical level, there are hundreds of pockets of repetitive work that can now be augmented, if not completely replaced, by A.I. algorithms.
Emerging Decision Intelligence platforms
Emerging decision intelligence platforms leverage prior A.I. technologies but are advanced and adapted to the company-specific decision-making process. Decision Intelligence platforms are like 3-D printers. Their strength is their adaptability for any company’s decision-making process. Inside of them, is the application of artificial intelligence algorithms that can predict the best answer for a given input. This new combination of advanced technologies continually collects immense datasets, observe past decisions and their outcomes, and leverage all of this to determine the best probabilistic response for your company’s current circumstance. Like the tactical example above, they can even merge outside benchmarks or winning strategies from industry experts into their recommendation engine.
These new Decision Intelligence platforms are stretching the CxO management reach beyond classic human grasp and well-faster than traditional “plan-do-check-act” speeds. Basic Business Intelligence tools already track thousands of KPI’s across hundreds of global corporate teams. They constantly collect precise data from a verified “source of truth”, and alert just the right leader when calculated outcomes seem to be vectoring away from an optimized result. More advanced systems, take these data and can then recommend actions with the probabilistic outcomes. These systems can, amongst other “what-ifs”, adjust operational plans as fresh data pours in. Inefficiencies in processes that pose a threat to revenue are identified, analyzed, and promptly averted, almost instantly. These systems are increasingly able to be in touch with a myriad of data sources and activity all at once, and keep management informed as it iterates constantly to ensure the intended business outcomes are on course. This uplifting of the digital endpoint allows senior management to also move themselves higher on the Maslovian Hierarchy to more strategic decisions while the A.I. system keeps routine decision flows on track.
Perform an audit of your organization and find out for yourself how much time and resources are being wasted with manual workflows that could be more efficiently automated.
It’s time to take a new lens on the work your team is doing. Out of your mission-critical, core people, how much of their time is being spent curating repetitive data and collecting context? What is the cost of the delay waiting for this work to be done? Wouldn’t that resource be better used on more strategic core activity? These decision flows should be mapped and analyzed for movement to A.I. agents. Companies are starting to bring experts in who can analyze how “decision flows” are threaded into their current processes and know how to weave automation into them. Once identified, this work can be encoded for the A.I. uplift.
Of course, the other alternative is to invest in yet again, another low-cost region of the world, find human resources, invest in infrastructure, build a team, struggle through communication barriers… and then find out a few years later that you have to pick up stakes and start all over again somewhere else! If these new technologies can remove a significant part of the tactical work, maybe the low-cost region math because irrelevant. Once the investment in decision intelligence tools is made, the goal is to move as much turn-of-the-crank work as possible to the cloud. With that done, the remaining work might just as easily be done at a U.S. headquarters than overseas. These now more efficient contributors can spend their time on what really matters to the business.
The movement toward leveraging A.I. tools and Decision Intelligence platforms is inevitable. After the initial fear that “the computers will take over”, even the effected staff will recognize that they’re spending their time on headier activities and more rewarding endeavors. Companies that take the leap now will forever be ahead of those that cling to past outdated methods.
For more on this topic, please contact the author.
Joe Carson
VP Business Development, ExperienceFlow.ai
