Bad Planning – The “Risk” Layers

Production forecasting is fundamental to every E&P’s decision-making, and these forecasts are usually bad. 

Forecasts are always wrong – that’s how predicting the future works – but the forecasts that are informing high-dollar investment decisions are unnecessarily and repeatedly low quality for completely preventable reasons. It’s not because of old software or bad engineers. It’s because of inadequate process, deficient communication, and bias.

Don’t just take my word for it…

There are a lot of factors at play here but today, let’s talk about “risk.”

A scary story

In working with a mid-sized US-based independent E&P, I found six, yes six, places between the decline curve and the executive team where different types of what they called “risk” had an impact on the production forecast.

First, a couple decisions around factoring in “risk” grounded in legitimate technical motivation: 

  • the reservoir engineer ignored downtime to keep the EUR the same
  • the production engineer added operational risk (i.e. downtime) to make the near-term forecast more realistic

Then, the management adjustments started rolling in:

  • A small bump up by the asset manager so that the annual number is the same as last time in an attempt to avoid meaningless variance analysis
  • A 5% haircut by the asset VP because they missed last quarter by 2% and spent a month explaining why
  • A smoothing exercise that makes each month an average of the previous 3 months by the corporate planner. No bumpy graphs allowed.

And finally… a “Strategic Financial Risk” of -3.35% was applied by the corporate planning manager.

I’m not saying that each person involved didn’t have an understandable reason for doing what they did, whether it was job security, not understanding the impact, or trying to avoid unnecessary questions. I am saying that the executive at the end of this line doesn’t have a chance in hell of understanding the information they are given, much less knowing if it’s a P10 or a P90. 

Then the actuals come in…

“Why did we miss?”

Answering that question accurately is impossible, but then dozens of people work for a whole month to come up with a (worthless) answer. The first two changes were made in the decline curve of individual wells themselves, then the next three were made at the asset level, then the last one was made at the corporate level, and none of this was explicitly documented. Good luck with your variance analysis…

It’s not just them

This was not an isolated situation – some version of this happens in almost every E&P that I’ve worked with. However, not every executive is blind to the factors going into their forecasts. Not every organization develops their quarterly guidance through this game of high-stakes telephone.

In some companies, it’s clear what goes into the forecast. People know that there is planned downtime at a processing facility that brings next month down by 10% (that’s not risk, by the way). There is a separate scenario used for midstream planning and negotiations. They’ll share the P70 with IR, use the P50 for budget, and use the P30 to fund the bonus pool.

The Drivers

This type of system is built on trust and ownership, then process and technology. Understanding weaknesses on each front can make the cause of our forecasting woes pretty obvious.


When a frontline manager sees the field level forecast, that number will be compared to what the boss will think of it. If they got punched in the head last time a forecast was shown below target, what do you think they’re going to do? They’ll defer that pain as long as possible by sweeping bad news under the rug, holding out hope that the team can figure something out to make it up. Meanwhile, the boss’s boss is making decisions thinking that number is the realizable, P50 forecast when in reality, it’s probably not going to happen and the people on the team all know it.


Some would call this accountability or empowerment, but those have been bastardized to be nothing more than a term that executives and HR managers nod their heads at. Ownership is about letting people run their part of the business. That means that they are allowed to fail. Put on a leash so they don’t destroy the business (it should be longer than you think) but if they feel strongly about a decision that you don’t agree with and you overrule them, one of three things will happen. 

1. They quit. 

2. Worse, they will make decisions and won’t tell you. 

3. Even worse, they won’t care as much and will just follow the path of least resistance.

When organizations attract great talent but don’t know what to do with it, this is where things go.


Do the asset teams complain about corporate changing their numbers? Do people talk about something, or someone, being a black box? Do people describe planning as a distraction from their real work? All are signs that the process is either non-existent or ill-defined. Everyone understanding their role as it supports the rest of the organization is the only way that the ship will go the right direction.


This industry has some of the most impressive technology in the world being used out in the field, but we’ve got a lot of ground to make up (about 20 years worth) with our data management and tools that we put to use in the office.

The hours spent deliberating about why February looks weird on the graph, or being mad at the person who didn’t know they shouldn’t change the unique well identifier, are lost forever. That’s stupid and we should not waste another second on it.

There has to be a good way for teams to access the data they need, to do their individual work, and then easily share it with others. When I say good here, I mean goodIntegrations are seamless, important assumptions travel with the data, and (gasp) wells have the same names across systems.

The companies that do this…

The executives that build a culture of trust and ownership, supported by good process and technology, understand their business as it really is. They then use the right information for the right purpose. They have mutual respect with their people because they trust and understand each other.

These are the companies that have a competitive advantage because they make better decisions, faster.