27 Jul Let Technology Disrupt You For The Best
By Sylvie Ouziel,
International President, Envision Digital.
Some of us will remember the first mobile phones (“do I really need such an expensive gadget when there is a phone booth around every street corner”) or their first email, or their first Internet search (I remember finding myself in front of Google wondering what exactly to search and what to do with it!). It probably tells a lot about how visionary I am!
In the corporate world, the arrival of Enterprise Resource Planning software created an equivalent disruption. Be it SAP, Oracle, Peoplesoft, Microsoft Dynamics or others, the first implementations were taking users and management by surprise. Standard screens and process flows were, to some extent, rigid. ERPs were not fully aligned with the current way of working and the usual corporate lingo of the company. Plant managers would complain that slightly more data entries and screens were needed than before and that what was always known as an “item reference” should now be renamed “part number” or “SKU code” or whatever the new software was calling it…
However, the first corporations which broadly adopted ERPs, in what was back then a leap of faith, quickly recognized four major benefits coming from connection, integration and synergies.
Yes, the plant staff had to change their habits but… data were flowing seamlessly along the value chain.
Full real time transparency was gained: all raw material, work-in-progress, finished goods inventories, client and purchase orders, machine availability status and failure reports were now at your fingertips, worldwide.
Productivity was no more about executing each single task as fast as possible but about the end-to-end systemic performance: accounting and reporting were automatically up to date without the need for clerks to reenter information about procurement, production or shipping. End-to-end performance went beyond the corporate walls where companies could connect their supply chains and automatically update each other’s inventory and accounting systems via EDI or even automate their billing and financial settlement transactions, system to system.
Overall optimization could be automated: Manufacturing Resource Planning modules could “see” inventory levels across factories and warehouses around the world and automatically optimize production plan.
Budgeting and planning became a more informed and fact-based exercise as detailed simulations and projections could be conducted at enterprise level in the tool.
Those four benefits can now be achieved in the world of IoT and AI but probably require the same type of leaps of faith to be truly uncovered.
Real time transparency is now enabled by real time sensors informing about energy consumption of a building, traffic in a store or a street, existence of empty parking spaces around the corner and air quality in the district.
End-to-end productivity comes from avoiding human intervention along the value chain… No need to place a three smiley button device or send a field force technician to check the cleanness of the public bathrooms or the proper functioning of an equipment when a sensor can automatically do it. No need for a command center in which feedback from users, field force technicians, or cameras are received and analyzed by employees who then trigger an action and dispatch an intervention team. The sensors themselves can trigger the proper intervention thanks to AI on the edge or in the cloud. For instance, a security camera can detect via image recognition that a critical safety barer was removed on a construction site and send an instruction to dispatch a security team to recover it. No need for physical construction site inspection or command center staff. Similarly, air quality in chemical plants or energy consumption of building can be real time monitored, removing the need for manual data gathering, reporting and inspection by authority.
Overall optimization can be achieved if all the sensors and “machine systems” get on the same page. For instance, within a harbor or a third-party logistics warehouse, cranes and forklifts operating for various companies can coordinate their tasks beyond corporate boundaries in order to minimize energy consumption and overall handling costs while optimizing service level. At the scale of a city, public lighting can be triggered by luminosity and presence detection, while public lamps can host cameras and air quality sensors allowing real time adjustment of traffic light, traffic instructions and navigation systems recommendations as well as automatic rescue dispatch in case of accident detection. Systems can also perform real time optimization in a multidimensional way: energy, operations, service levels and maintenance activities can be simultaneously considered.
Last, simulation and planning can be conducted thanks to digital twins, modeling equipment’s and systems. Wear or failure risks can be predicted and avoided by preventive actions: specific vibration on an elevator or a change in the sound of an engine’s rotor or even the noise of a liquid flowing in a pipeline constitute leading indicators of an issue which can be avoided by early action. Digital twins also allow more strategic decision-makers to play “what if” scenarios and decide on capacity increase, contingency plans or refurbishment timing. The reaction of a district to an inflow of population, a heat wave, an adoption of 10% of electric vehicle by drivers, a deployment of 10% of roof top solar capacity, a power outage of one hour… can be simulated in a realistic and quantified ways to inform city planners.
Those are only a few shallow business use cases among an almost infinite set of possibilities offered by real time combination of AI and IoT to foster machine-to-machine, “no-human touch”, cooperation. Exploring those use cases will require more and more leading-edge companies, organizations, government to take “leap of faith” actions and adopt IoT solutions, unlocking network effects and cross boundaries synergies. 5G can be one of the catalysts of this revolution but most of the use cases I mentioned are implemented today and only “wait” for bold generalization decisions. Like for any revolution, first movers will have a chance to shape the future.