Udit Poddar, CEO & Co-founder, WorkOnGrid, in conversation with Emerging Manufacturing Magazine
Q: Grid now monitors 10M+ meters across 20+ utilities. What have been the most visible changes at the grassroots level, for example, faster solutions, fewer billing disputes, or reduced field crew dispatches?
It is quite interesting how this plays out in different markets and utilities. Utilities in different regions typically run under different operating pressures and therefore have varied use cases. The use cases typically depend on the location, type of commodity and also the maturity of the utility in their digital journey.
At the grass root level, we typically see the benefits for either consumers or the utility field crews. For consumers, the largest impact is on the predictability of their consumption bills and higher reliability and quality of power through early detection of issues and typically 20-30% faster response rates to failures, outages and even move toward a more preventive asset maintenance and replacement cycles from the utilities. We also, definitely see better engagement and consumer awareness through proactive communication by the utilities for events like planned outages, estimated bill amounts and proactive alerting of consumption spikes etc. This reduces overall call rates and bill shocks which have been a major concern from consumers.
On the utility side, there are multiple benefits that come in the form of better prioritization of asset maintenance cycles that reduce field visits drastically and in some cases by upto 50% while driving the same results. We also typically see a higher field crew satisfaction as they have access to specific and accurate actionables, locations and alerts while they are out on the field. While it’s difficult to measure, these softer parameters are often essential for better employee satisfaction and impact the quality of service that utilities are able to provide to their customers.
Q: How critical is an interoperable, AI-native layer like Grid in addressing the challenges of fragmented utility IT (HES, MDM, CIS, GIS, OMS, SCADA) that often behave like an “unreliable grid” for data?
Most utilities already have good systems. The problem is that the metering head-end, meter data management, billing, GIS, outage management and SCADA were each bought to do one job, and they were often not built to work with the others. An incident like a transformer failing from overload, can lead the operations team to pull up multiple versions of the same data to arrive at the right diagnosis.
The idea for us is to connect and orchestrate their data, so that we are able to provide as much context as possible for any event across the network or consumers. This primarily reveals itself in two real world outcomes in different use cases: First, noise drops sharply, because hundreds of related alarms can be grouped into one incident, and operators see only what needs to be actioned on. Everything else is for deep diving as the need may be. Second, a lot of response actions can be automated so that systems can work with each other for better response times like – AMI system based on specific conditions, creating tasks for the field teams automatically in their work management systems.
The next layer and this is where we think where LLMs or AI can help enhance this when very specific agents that monitor these event streams, rank them by impact and gives the operators an explainable and auditable priority list to decide what to go after first can really impact key operational KPIs for utilities. However, for these to work it is very critical to understand that we need to invest in the data foundation and quality which is often the most overlooked part about AI roll out plans and is becoming the hinderance for pilot to production stories now.
Q: In practical terms, how does Grid change the way utility teams plan and manage daily operations? What impact have you seen on revenues and losses?
So, utilities are very interesting and somewhat difficult primarily because of the sheer spread out nature of their assets and operations. Because they also run critical infrastructure and provide essential services, they are often under regulatory pressures & obligations not just from a reporting level but also service delivery point of view. These factors make speed of information flow very critical for them to first make sure they are fulfilling their regulatory obligations and second so that they are continuously improving their profitability.
It is also critical to understand that while there are newer business models that are emerging with the spread of distributed energy resources and better consumer intelligence, a utility’s revenue creation opportunities are often constrained and therefore revenue optimization or efficiency increases are often the lowest hanging fruit for a better bottom line. To this end, Grid first and foremost enables the right teams to have access to the information they need to take decisions and actions faster. With what I like to call the “Sensorization” of the distribution networks, there is a lot of opportunity to detect, plan and act on information for improvement of the bottom line and we ensure the right teams get the right information fast.
The impact numbers are often consistent and also depends on the market and use case. For example, in emerging markets with high losses, we’ve seen both energy and water utilities commercial losses drastically reduce (from 2% to higher single digit within first few months of deployment). We are also seeing new age revenue creation opportunities like upselling signals from the consumption patterns etc.
Q: Grid has grown to 10M+ meters and 20+ utilities with a small team and a recent $2.4M Series What has enabled this capital-efficient growth model?
Three things made it possible.
First, we spent our early years fitting the product to utilities before trying to scale it. We tried many ideas and dropped a lot of them. This helped us create one platform that works across electricity, water and gas and across very different markets, so a new utility or problem statement is mostly configuration rather than a custom build. That keeps delivery costs in check as we add customers.
Second, Grid works with the systems a utility already owns. We don’t ask anyone to rip and replace their existing system. That shortens sales cycles, and projects start showing results within 3-4 weeks rather than after a long replacement cycle.
Third, the team. We have stayed small on purpose and hired people who take full ownership of what they build and deliver. A small team that owns outcomes moves faster and spends less than a large one that passes work between departments.
