7 tactics to increase the accuracy of your forecasting

7 tactics to increase the accuracy of your forecasting

Oct 16, 2020 | Analytics, Management, Operations

 

Certainty in forecasting is the holy grail, being certain of the future means success. However, as we know the only thing we know for certain about the future, is that it will not be the same as the past, or present.

Quantifying uncertainty appears to be an oxymoron, but reducing the degree of uncertainty would be a really useful competitive outcome.

When you explicitly set about quantifying the degree of uncertainty, risk, in a decision, you create a culture where people look for numbers not just supporting their position, but those that may lead to an alternative conclusion. This transparency of forecasts that underpin resource allocation decisions is enormously valuable.

How do you go about this?

  • Start at the top. Like everything, behaviour in an enterprise is modelled on behaviour at the top. If you want those in an enterprise to take data seriously, those at the top need to not just take it seriously, but be seen to be doing just that.
  • Make data widely available, and subject to detailed examination and analysis. In other words, ‘Democratise’ it, and ensure that all voices with a view based on the numbers are heard.
  • Ensure data is used to show all sides of a question. In the absence of data showing every side of a proposition, the presence of data that emphasises one part of a debate at the expense of another will lead to bias. Data is not biased, but people usually are. In the absence of an explicit determination to find data and opinion that runs counter to an existing position, bias will intrude.
  • Educate stakeholders in their understanding of the sources and relative value of data.
  • Build models with care, and ensure they are tested against outcomes forecast, and continuously improved.
  • Choose performance measures with care, make sure there are no vanity or one sided measures included, and that they reflect outcomes rather than activities.
  • Explicit review of the causes of variances between a forecast and the actual outcomes is essential. This review process, and the understanding that will evolve will lead to improvement in the accuracy of forecasts over time.

Data is agnostic, the process of turning it into knowledge is not. Ensure that the knowledge that you use to inform the forecasts of the future are based on agnostic analysis, uninfluenced by biases of any sort. This is a really tough cultural objective, as human beings are inherently biased; it is a cognitive tool that enables us to function by freeing up ‘head space’ reducing the risk of being overwhelmed.

Consistent forecast accuracy is virtually impossible, but being consistently more accurate than your competition, while very tough, is not.  Forecast accuracy is therefore a source of significant competitive advantage.

 

Header cartoon courtesy Scott Adams and his side-kick, Dilbert.

 

Forecast in cartoons

4 steps to effective cross functional performance improvement

4 steps to effective cross functional performance improvement

Sep 23, 2020 | Analytics, Management, Operations

 

When you want superior performance, implement a number of key cross functional metrics.

Gaining agreement on a set of metrics that genuinely track a projects cross functional performance is not a simple task. KPI’s are usually focussed on functional performance, whereas optimal performance requires that cross functional dependencies are reflected in the KPI’s put in place.

The standard response of functional management to such an idea is that if they cannot control a process, how can they be held accountable for its performance?

To get over this reasonable question requires that there is agreement across three domains, and collaboration around the tactical implementation of a processes improvement.

Let us use a reduction of Working Capital requirements as an example, requiring 4 steps.

Agreement on strategic objectives, and accompanying KPI’s.

The strategic objective becomes making the enterprise more resilient, and therefore able to adjust to unforeseen shocks. One of the strategies agreed is the reduction of Working capital. There are many parts that make up working capital, inventory being a major one in a manufacturing environment. As the joint objective is to make the enterprise more resilient, it is agreed that Inventory levels must be reduced.

Agreement on what ‘success’ looks like.

The absence of an outcome that signals success means that any improvement will do. There are numerous measures that can be applied, how much, when, what outcomes, compliance to standards, variation from the mean, and many others. In this case, a reduction of inventory levels by 15% without compromising customer service, is the agreed metric of success. Agreement across functions that this is a sensible measure will deliver the opportunity for cross functional alignment, and will contribute to delivering the strategic objective of resilience.

Agreeing on tactical diagnostics.

Tactical diagnostics are aimed at tracking and optimising the short term performance detail of the components of the agreed objective. Which parts of a project are working as expected, and which are not. You can make the changes in these on the run, experiment, learn, adjust. It is usually not necessary to have these on the high level dashboard, they are for the teams and individuals responsible for the execution of a strategy to determine the best way of doing them. What is critical at the tactical level, is that those involved clearly understand the wider objective, and their role in achieving it.

Application of the diagnostics.

As the old saying goes, ‘what gets measured, gets done’. In this case, to reduce inventory without compromising customer service, requires the co-ordination of many moving parts, some of which will need some sort of a scoreboard to track progress on the tactical improvements.  For example, transparency of raw materials inventory and incoming delivery schedules to those doing production planning, matching production to real demand, improving forecast accuracy, managing DIFOT levels, levelling production flow between work stations, and many others. These should be made visual to the teams engaged in the work, at the place where the work gets done.

For all this to work, the KPI’s need to be simple, visual, apparent to everyone, and as far as possible dependently cross functional. In other words, build mutual KPI’s that reflect both sides of a challenge.

For example, stock availability and inventory levels. Generally those responsible for selling do some of the forecasting, so they always want inventory, manufactured yesterday, to be available when a customer needs it. As a result of uncertainty, they tend to over forecast to ensure stock availability when an order arrives. By contrast, Operations tends to like to do long runs of products to satisfy productivity KPI’s, so you end up running out of stock of the fast movers, while having too much stock of the slow lines.

The solution is to make the sales people responsible for inventory levels, and the operations people responsible for stock availability. In that way, they collaborate to achieve the optimum mix of production and inventory. This mutuality ensures functional collaboration at the tactical level, leading to making decisions for which they are jointly accountable.

You are in effect, forcing cross functional collaboration where it does not naturally exist in a traditional top down management model.

None of this is easy. If it was, everybody would be doing it. That is the reason you should be on this journey, it is hard, and so delivers competitive sustainability.

 

 

 

The trouble with SMART goals

The trouble with SMART goals

Aug 3, 2020 | Leadership, Operations

I love smart goals, they provide a road map, discipline, and a definition of what success looks like. Over the years they have proved to be very useful.

However, as I get wiser, I realise there is one vital element missing from Smart goals:

Compounding.

Compounding is, as Einstein noted, the most powerful force in the universe. To compound, you do little things that build on each other over time, becoming increasingly more powerful at a geometric rate.

The benefit of compounding is that you learn as you go, it is learning oriented, whereas SMART is by definition, goal oriented, it has an end point.

The obvious solution to this dilemma is to make every project a series of goal oriented components, that together and compounding, deliver the continuously improving outcomes. This sort of view forces to you to be ambidextrous in the way you look at performance.

On one hand, you are down in the weeds working with the detail, while on the other hand, there is the really important helicopter view that is able to make the compounding impact of all those tiny improvement obvious over time.

At its core, this is what lean thinking is all about, continuous improvement that delivers over time.

What are the 2 common characteristics of useful metrics?

What are the 2 common characteristics of useful metrics?

Jun 15, 2020 | Management, Operations

Metrics at their best deliver game changing insight and wisdom. At their worst, they are misleading , irrelevant and a pain in the arse to collect.

So, what are the two characteristics that make a great metric?

The metric is a leading indicator.

A Leading indicator is a reliable measure of what will happen.

For example, if you have the data that shows that for every lead you generate, you convert 5% at an average purchase price of $50, and those customers buy twice a year for  an average lifetime of 3 years, you can calculate with some confidence what each lead is worth to you. In this case, it would be: 100 leads X 5%  X $50 X twice a year X 3 years = $1500.

The metric is causal.

The most common mistake I see, is metrics that confuse cause with correlation. There are many things that correlate, despite the fact that there is no relationship between them. One does not cause the other.

For example, there is a correlation between ice cream sales and drownings, which on a graph looks identical, but there is no causation between the two. Look deeper, and you might see that on sunny days, more people eat ice cream, and more people also go to the beach, swim, and therefore risk drowning. There is also a close correlation between ice cream consumption and a shark attack. This second correlation would also suffer from very ‘thin’ data, which make any sort of causal relationship even further from the truth.   However, a glance at a graph, which takes on some credibility as someone has actually created a graph, would suggest there is some causation.

For a metric to be of any real use, it has to be the catalyst that changes behaviour, and delivers a predictable result. It is not always easy to sort the causal from the correlative. When you need some experienced wisdom, give me a call.

 

 

 

How do you trouble shoot flow?

Feb 27, 2020 | Lean, Operations

You never get this process of articulating flow right first time, or second, maybe third for simple tasks. People are always people, they are in a hurry, forgetful, negligent, or new to the task, so it has to be made as easy as possible.

Toyota pioneered this idea of flow in a manufacturing environment, but whether you are in a factory, or in an office, the process is the same. There has to be a process for continuous improvement, or at the least one to identify and remove impediments to orderly and consistent flow, in any organisation that aspires to survive and prosper. It results in the optimisation of the process, which is usually radically different to what is required to encourage innovation, which is by its nature more ‘scrappy’ and disorganized, as the activity seeks to test its viability and grow.

Improvement only comes from a stable environment, where things happen in a consistent and predictable manner. When you have stability, you are in a position to experiment, and observe quantitatively the result of the experiment. Was it beneficial, is it worth incorporating into the standard process? If so, then the process check list is changed to incorporate the change as the new standard procedure. If not, a note is made so that at a later time someone can review and know the change has been tested, or indeed, use it as the base for construction of a hypothesis and further experiment that takes the change one step further to where it may make the difference.

A client some time ago installed a coffee machine in the tea room. An expensive unit, that took beans, ground them and dispensed with hot water and milk on demand. The unit has three  things that needed to be done. Beans added to the container, water added to its dispenser, and the line from the milk bottle, held in a small refrigerated unit on the side, needed to be removed and cleaned each day.

These seemingly simple things caused a lot of problems, and really shitty coffee. Water was put into the bean dispenser, (strangely perhaps, beans did not seem to find their way into the water dispenser) requiring an extensive service (twice) and the milk line seemed immune to any cleaning.

To address this challenge, we engaged the staff in a bit of a game, using a fishbone diagram and post it notes. 

Within a few days, the diagram was covered in suggestions, which at a lunchtime meeting we ‘workshopped’ down to those that the people using the machine thought were the best. We wrote a checklist, or standard operating procedure  for the coffee machine, which was tested over a few weeks by a small group of heavy users, then posted on the wall of the kitchen, as well as included in the businesses then developing library of SOP’s.  We also left a big framed photo of the fishbone on the wall in reception, as a reminder to all that improvement was everybody’s job, and that it could be fun, as well as useful.

And, far fewer problems with the coffee machine since.

 

Header photo courtesy Alwin kroon via Flikr

 

 

The single best financial measure on which to focus improvement initiatives: Cash Conversion Cycle.

Feb 3, 2020 | Governance, Management, Operations

 

 

How long does it take you to convert your products into cash?

This is one of the most important but overlooked measures in most businesses I see. It goes to the manner in which you manage all the processes  and resources it takes to turn ideas, products and services into cash, the lifeblood of every enterprise.

Your Cash Conversion Cycle, (sometimes called cash to cash cycle) is the time from the order of raw materials, in the case of a manufacturer, to the payment of the invoice related to a sale. In other words, days inventory (which includes raw materials, Work In progress, and finished goods), plus days debtors outstanding, minus days creditors outstanding.

Reducing your cash conversion cycle time can be a huge competitive advantage.

There are a number of well understood ways to reduce your CCC, the catch is, that it is a delicate balancing act between differing functional responsibilities.

In the pre-deregulation milk industry in NSW, my then employer, Dairy Farmers, paid the dairy corporation for its milk, as all production was vested in the corporation, in 30 days. We sold to milk vendors, the monopoly distributors, on 7 days terms. This gave us a -23 day cash conversion cycle. On the day of deregulation, from which retailers could buy from whoever they wished, that cycle changed radically. We paid the dairy farmers, our suppliers, in effect, C.O.D., and supermarket retailers paid us 90 days. Our cash cycle went from -23 days to +90 days for supermarket sales, a 113 day turnaround overnight, which cost in the region of 60 million dollars in working capital.

It was a big pill to swallow.

So, what are the strategies that can be employed to improve your cash cycle time?

Reduce inventory.

Physical inventory in a service provider is not a consideration, as there is none beyond consumables. However, in most cases of service businesses, there is some sort of project involved, which takes time to deliver. In this case, time can be considered as inventory, and the quicker the ‘inventory turnover rate’ the better.

A manufacturing business generally has inventory in three parts: raw material, Work in Progress (WIP) and finished goods. While it is tempting to manage each separately, the downside is the potential impact on customer service, so they must be managed together.

  • Purchase reduction. Too many times I have seen a Purchasing Manager instructed to reduce inventories, which is easily done by simply reducing purchases. However, done in isolation, this almost always leads to manufacturing shortages, and angry customers.
  • WIP reduction. Similarly, WIP is often seen as relatively easily reduced by doing longer manufacturing runs. The unfortunate consequence of which is usually increases of finished goods inventory of slower moving lines. When there is a multi-stage manufacturing process, longer runs also leads to WIP build-up in front of slower manufacturing sub-processes.
  • Finished goods reduction. Finished goods are the most expensive inventory items, as you have added time, labour and the input materials to produce them. Nevertheless, being out of stock when a customer orders is never good. Alternatively, depending on your business model, putting their order on a future delivery date can be managed, but the longer the delivery lead time, the more likely the customer is to go elsewhere.

The upshot is that inventory can be reduced, often by substantial amounts, but it takes leadership, functional collaboration, and appropriate performance measures to be successful while retaining customer service.

Decrease debtor days

Debtor days are a function of both your trading terms and diligence in collecting debt as it becomes due. A strategy that usually works, is a polite reminder that the invoice is due to be paid in a few days. It is too easy to leave debtors to pay their bills as and when they are able.  A bit of friendly, polite pressure applied might see your invoice  go to the top of the pile, at least over those who do not actively and politely follow up. Diligence, and being a very polite ‘squeaky wheel’  pays.

Another useful way to reduce debtor days is to split payment. When selling some items you can reasonably have as a part of your trading terms a deposit, and partial payments over the period between order and final delivery. This happens when you build or renovate a house, there are stepped payments in line with project milestones. Think creatively about how you might introduce similar stepped payments, your cash flow will love you.

Manage creditor days

Managing creditor days is not just a matter of delaying payment, although this is the most common reaction. Your suppliers are in the same situation you are, setting out to reduce their cash cycle time, and if you are a recalcitrant debtor to them, they will tend to reduce their levels of service, demand C.O.D., or even simply refuse to supply. Secondary to a shortened cash cycle is a reliable cash cycle. If your suppliers know from experience, and negotiation,  you will pay the invoices on a given day, they will tend to leave you alone, or even agree to an extension of terms. In effect they are exchanging a shortened cycle for a reliable one. Experience tells me paying exactly to the terms agreed is the best strategy, as it enables renegotiation of those terms.  

Management of cash is an essential discipline for success, and the time it takes to convert an order into cash is about the best measure there is to proactively manage your procurement, manufacturing and sales demand planning processes. Out of measuring the cash conversion cycle time will come a number of contributing measures that will together make the enterprise more competitive, resilient,  and agile.

This is all pretty simple to say, but like most things in life, much harder to do. When you need an experienced hand, give me a call.