Agile AI-based feedback and feedforward loops start where planning stops

COVID-19 Pandemic Disruption

The COVID-19 pandemic has been a severe global humanitarian crisis. For the CPG industry it was one of the biggest simultaneous demand and supply side disruptions in recent times where the complexity and volatility of the operations hit an all-time high.

Front-line and planning and execution teams within these companies faced increased pressure to respond to either the huge up-surge in demand or down-surge in demand depending on the category of business.

In the early weeks and months of the COVID-19 pandemic, for many segments that saw…


What defines AI in Demand Forecasting and Planning. Is it the process, technology, or outcome? Especially when there are many offerings that talk about using AI/ML in this space. Customers often ask the question “Is it really AI”. So how should one think about AI in this space?

Appreciating the complexity and nuance in the Demand Planning and Forecasting process

This question, “Is it really AI?”, comes up a lot. Demand Planners have been using “statistical” forecasts for many decades. So, what separates an AI based forecast from just another better “statistical forecast”?

It is a valid question especially in…


First published in Samya.ai Blog: https://samya.ai/paradox-of-planning-moving-from-the-focus-on-performance-in-the-past-to-performance-in-the-future/

It is quite a paradox that whilst planning is a future thinking and forward-looking exercise the performance of planning is always measured in terms of past and YTD performance.

As an example, Demand Planning teams spend a lot of time in analyzing their forecast performance in terms of different metrics such as MAPE (mean absolute percentage error) and Forecast Bias (tendency to over-forecast or under-forecast).

These metrics are great indicators of which areas the plan is off-track and not performing vs. the realized actuals.

Various views of these metrics are created:

  1. At different levels…


First published in Samya.ai blog: https://samya.ai/overcoming-the-accuracy-vs-agility-trade-off-in-demand-planning-forecasting/

The question of accuracy vs. agility has been a long debated one in the CPG demand planning world. Usually accuracy and agility are seen at loggerheads with each other, especially during turbulent times marked by heavy promotional and competitor activity, recessions, weather calamities and pandemics such as COVID-19.

This is due in part, to the inability of current demand planning processes and systems to anticipate and proactively respond to volatility. Many systems and processes are not learning enough to adapt to increasing complexity and volatility. …


First published in Samya.ai blog: https://samya.ai/5-questions-to-ask-your-demand-forecasting-vendor/

As stewards of the forecasts in a CPG organization, demand planners face daily struggles as they strive to determine and forecast product demand with accuracy. And while demand forecasting continues to be a problem, it’s just one piece of the puzzle. In addition to accuracy, demand planners need the agility and ability to proactively anticipate and respond to trends, patterns and shocks.

But traditional forecasting systems simply weren’t designed to adapt to the complexity and volatility in today’s environment. They tend to be rules-based, operating in a linear and sequential way, and because they…


Make it Hyper-Real for your Early Stage Investors

I have been an angel investor and advisor for about 3 years now having invested in startups in India across different sectors. Some of my investments are pretty early stage- Pre-product prototype, Pre- product-market fit, MVP no customers, MVP with POC customers, MVP with 2–3 early customers, etc.

Early stage investing is an art. It is a low data, high intuition scenario.

There is no equivalent or even remotely similar product in the market. Hell the market might not even exist and might need to be created.

Most seed stage institutional investors…


This post is not about advice on startup ideas, business model, product or funding, etc. It is about the inner life of a startup and its people.

Life in a startup is daunting for founders, the early founding team and employees; especially in the early stages. It is not for everyone with its emotional, mental and physical ups and downs, but is extremely enriching if done well — it is an extreme sport and requires perseverance and practice.

As an individual maximizing oneself in a startup and maximizing the startup are intertwined; like in many organizations but in the startup…

Deepinder Singh Dhingra

Founder, Investor, Advisor,Passion for working with startups and founders, B2B, SaaS, AI/ML, Business-Product-Finance Intersection

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