From drawing up a business plan to predicting sales and growth, you’d be forgiven for thinking a crystal ball was your most useful business tool. However, when it comes to forecasting there are more reliable indicators of what lies ahead – as long as you know how to read the signs and interpret wisely. The better you are at planning ahead, the better you’ll perform when there are significant changes in demand. Nowhere has this been better shown than during the global pandemic.

Once up and running, there’s a temptation for businesses to use internal information and not consider the outside world as much. There’s a danger that you’ll work from lazy assumptions such as ‘last year plus 5%’ or ‘what head office asked for’. While such targets may have some grounding in real data, setting truly informed objectives is essential.

Assessing what’s going on around you in the business world is relatively easy at a strategic level –  for example, if you were a national restaurant chain, you could look at a range of readily available information in order to decide where to open a new location, such as overall economic growth, local population and consumer confidence.

Below the strategic level, leading indicators are even more useful. If you can reliably predict demand, you can use this for operational decision-making. All of these decisions have an intrinsic lead time to implement, so you need to be thinking ahead to where you are going to be. For example, a hotel might look at web hits, enquiries and bookings as a sequence showing where levels are headed.

COVID-19 has shown us all that we need to really think about our leading indicators. For companies with a process lead time of 0-4 weeks (eg, in distribution and simpler manufacturing), the existing order book and weekly incoming orders gave a good leading indication of the level of near-term operational activity. The disruptions came mainly from customers changing required dates or from supply chain interruptions. One university had scientists ringing up chasing delivery of equipment, only to be informed that their own goods-in departments had been closed and order dates pushed back. By maintaining their customer relationship management (CRM) system, companies could obtain reasonably reliable pipeline information, but only after the initial shock to the system had subsided.

Another company I supported was in a long lead-time business, so from May to July its manufacturing and sales levels (lagging indicators) were ‘normal’ and not affected by the pandemic. However, I suggested they explore and report their outgoing quotes and incoming order positions (both leading indicators of future performance). These showed a contrary picture: quotes going out were about 50% down on normal, and orders in about 75% down. The board discussion initially focused on why the quotes and orders were not more closely aligned, when the discussion really needed to be about how the business would survive in six months’ time on just 25% of normal activity. People were struggling to understand that the ‘today’ experience was not indicative of future performance and needed time to understand the whole picture.

Further analysis of the conflicting data was helpful. On detailed examination, many of the quotes were actually re-quotes where a customer’s purchasing team was either trying to look busy, or to see if they could gain any cost reduction in a weak market. The conclusion was to refine the leading indicator to use the value of new (not repeat) quotes issued.

So, how do you find and use leading indicator data for forecasting? Start by assessing the different levels of data, and remember, these are only indicators.

• Macro level – Bank of England forecasts for GDP, interest rates; national consumer confidence indices; and industry-level growth predictions.
• Regional level – local population growth; regional consumer confidence indices; regional salary level data; investment in local infrastructure; and conversations with your bank manager, auditors and other professional advisers.
• Industry-specific – growth and forecast data from industry bodies; competitor benchmarking (mostly lagging but information like new product launches are leading); appointment of key individuals; reduction in workforce levels (loss of skills, capacity) in your customers and suppliers; and competitor activity.
• Regional and industry specific – grant and other funding availability; and numbers of planning permissions granted.
• Direct supply chain intelligence – customer behaviour (your quotes and orders – levels, conversion rates, reasons for losing); competitor behaviour (entering or leaving the market, price and product changes); and information from suppliers (how busy are they doing things for your competitors?).

Many directors are optimistic and bullish about their ability to ride out difficult trading conditions, so you may face the issue of being the Jonah in the room when predicting a downturn. Some people will simply not accept bad news at first. You have to make a strong case. Typical excuses you will have thrown back at you include:

• we have experienced recessions before in this industry (our opinion is more valid);
• order intake is naturally variable or ‘peaky’, so if you wait long enough we will have a big month to balance this out and we will top up with future orders;
• this short-term deterioration in order intake could just be a random fluctuation; and
• we will be more able to respond to future orders when they come in.

One answer is to try to anchor your information as facts rather than opinions, to de-personalise the discussion. Understanding the root cause of an unusual situation can be illuminating, as it sets the numbers in the context of the business. It’s also helpful to look at an order book not as a total value but as time phased in a monthly table to show the reality as it will hit the monthly performance.

Another answer is to have two forecasts – one prepared using your leading indicator information, the other a more bullish set (based on ‘informed opinion’ from the noisiest person) and run these as two parallel scenarios. When you then look back and review forecast accuracy in future months, you’d hope to see that your method was a better predictor and people will buy into its validity, or at least understand where it can be improved.

The pandemic has thrown up examples where data may be pointing one way but closer analysis raises further questions. Apple and Google, for example, examined travel patterns before, during and after lockdown. So far, so useful.

However, these figures should not be mistaken for an indicator of overall economic activity – more people travelling may mean they are returning to the office, but we don’t know whether those people were previously working from home or not working at all.

Equally, a rise in the number of people visiting non-food retail stores between January and now [November] may look like recovery, but seasonal patterns indicate that consumer spending in Europe is usually 5-15% higher in July in a ‘normal’ year. And while a rise in spending on debit and credit cards might also seem like a positive indicator, that needs to be balanced against the fact that cash transactions have dwindled dramatically as card payments are seen as more hygienic.

Looking in the rear-view mirror is never the best way to navigate your way forward. A business cannot be run well by simply looking backwards, or at today’s outputs. You need to plan resources and funding for future business levels, and you have to find whatever clues may point you reliably towards future conditions.

A mnemonic – REAR-FAR – is usually wheeled out at this point.

• Research available data sources.
• Explore information in your own company.
• Analyse the data and any conflicting information.
• Refine your indicators if needed.
• Find the root cause(s) at a human behavioural level.
• Anchor your information in facts, not opinions to de-personalise the discussions.
• Review your forecast accuracy with hindsight and consider improvements.

While leading indicators are vital when examining declining levels of business, they are equally important when managing a recovery or growth phase. Remember that resources such as trained staff, stocks, equipment, space and funding may need to be put in place before the increased sales activity actually arrives, but the right leading indicators will assist in smoother planning and implementation. And never forget that your own behaviour and decisions will also affect outcomes.

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