Improving Field Sales ROI White PaperKnowing the ROI of the Field Sales Force has never been more important to ensure the optimum level of resource is allocated to ensuring perfect execution. This paper examines some of the fundamental prerequisites brand owners should consider in setting up effective measurement tools.

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Overview Field Sales teams are expensive to run, but their impact on sales can be difficult to calculate. Many brand owners rely on imprecise assumptions about the impact of sales activities on revenues to generate an assumed ROI.

However, the advent of more widely available retailer Scan or EPoS (Electronic Point of Sale) data allied with flexible SFA systems means that brand owners can know with certainty the ROI of their Field Sales investments.

This can lead to more motivated sales people, working smarter and achieving better results which both they and their management can easily see.

What is Field Sales ROI & Why Does it Matter?

Defining Return on Investment (ROI) is simple - simply open any dictionary. The investment is the financial cost of the exercise. The return is the financial benefit associated with that exercise. The ROI is a measure of the return in relation to the investment and is normally expressed as a ratio – 3:1 for example. From this we deduce that for every £1 invested the exercise has generated £3 of benefit.

So far so good, but what does this mean in a field sales context? Firstly, we need to calculate the cost. This consists of the salaries and expenses of all merchandisers, salespeople, sales managers and dedicated administrative staff associated with the field sales force. It may also include some allocated head office costs. The expenses should include the cost of running cars, pension schemes, training and recruitment. In some cases, the field sales activities may be outsourced to an agency or broker, in which case their total charges including bonuses must be considered, plus the internal cost of any dedicated staff managing that third-party relationship.

So, whilst it’s not rocket science outlining the cost side of the equation, defining the return is a rather trickier.

This is all about calculating the incremental sales generated by the field team.

If the sales team takes orders, then the value of those orders could be said to be the direct result of the sales visit. But what would have happened if the salesperson had never called? If the brand owner supplies products which are important to the retailer, surely the retailer would have placed an order direct rather than risk a gap on the shelves?

We can therefore see that even in markets where orders are taken it is not obvious how much of the sales revenue can be clearly isolated and defined as genuinely incremental.

This challenge becomes even harder in an indirect environment. Major grocery chains have sophisticated inventory management software, where ordering is automated with ‘Just in Time’ arrival of stock to store. That means there is no need for orders to be taken at store level by sales people.

The role of the field force is twofold in this environment. Firstly, to assure compliance to Head Office agreements. The brand owner’s Key Account Management team will have agreed the products (SKUs) to be ranged in each store format and banner, the promotional programme and the new product launch schedule. If individual stores haven’t implemented any aspect of the agreement, the field sales person’s role is to remind the store manager of that obligation and reinstate the plan.

In addition, the field team may be able to exert extra influence in store. Maybe there is some promotional space which is allocated at the store manager’s discretion.

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This helps us answer the question ‘Why does calculating Field Sales ROI matter’? It matters because the brand owner needs to know where the best ROI will come from. Is it an additional £250k on Field Sales resources to concentrate on improving compliance and boosting display?

Perhaps a promotion can be given additional sites in store, or greater prominence than was agreed at Head Office, and this added boost to sales can be unleashed by the skill and relationship of the local field sales person. Essentially the sales person is making the customer marketing spend (trade spend or below the line investment) work harder to generate more sales.

Whether the field team is fixing occurrences of non-compliance to central agreements, or boosting the sales of a previously agreed event, it is clear that these actions will typically generate incremental sales – over and above what would have occurred with no sales rep visit.

It follows that if we can calculate the value of these incremental sales, we can make the ROI calculation. For £1 we spend on field sales, we generate £x of incremental revenue.

This is not the end of the financial exercise however. Sales revenues are normally provided by retailers to suppliers at net retail value. The brand owner sells in at a much lower price to the retailer, so that is the actual revenue generated. Arguably this doesn’t go far enough either.

The brand owner needs to know how much additional margin was generated, so that the net spend can be compared to the net benefit.

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Or would it be better spent running more promotions with retailers?

Alternatively, would an improvement in retailer discounts and incentives provide greater rewards?

The reason to calculate Field Sales ROI is to be certain that resources are being allocated to the right mix of investment initiatives across the business. Critically for senior sales management, knowing the financial impact of increasing or decreasing the size of the field sales team is vital if attacks on headcount are to be resisted. The Field Sales Director who cannot say how much sales will increase or decrease in these two scenarios is likely to be a victim, rather than a master of events.

How is ROI Typically Measured & Calculated in the Grocery Channel Today?

Traditionally the ROI of Field Sales is not dealt with in a forensic way by most brand owners. Of course, brand owners with large field sales teams, whether in house or outsourced, are interested in tracking the impact and value of their investment, but often lack the systems or tools to perform a detailed calculation.

Many legacy ways of working are based on assumptions. These have their roots in well-meaning and reasonable thinking, which will nevertheless produce an unreliable approximation of the ROI rather than a solid figure.

This approach is typically deployed by brokers or field sales agencies and goes something like this.

We know that if we ask our merchandisers to place SRP (Shelf Ready Packaged) units in store the sales effect will normally be fully incremental. The value of the product in one of these units may be £100. So, our field sales person has facilitated the sale of an incremental £100 of sales. That all sounds OK.

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However, most sales actions aren’t as clear cut as that, especially in major retailers where the list of approved actions in store by reps is a fairly short one. For actions like merchandising the shelf (making the shelf neater, facing up the stock, replenishing from the store’s stockroom and so on) the impact can’t be easily calculated in the same way.

So, the agencies will fall back on assumptions. They’ll make a value assumption about each action, normally in conversation with the brand owners. If some research data is at hand to support the assumption so much the better, but more often than not it will simply be a ‘best guess’.

Does this really matter? If the agency and the brand owner are in a long-term relationship, then setting KPIs and targets around sales driving actions is a ‘good thing’. After all, if the brand owner sees that the number of the most valuable sales driving actions is increasing year on year, surely that means that the sales probably are increasing and if costs stay stable then the ROI must be getting better?

Not necessarily. The problem with estimates like these is that there is no sound method for checking the authenticity of the claims made by the field team. Let’s suppose that a less than enthusiastic sales rep makes a visit and does very little.

Maybe he or she claims to have done some merchandising. Better still for estimated sales impact, a claim of a secondary site might be made. Even more convincing if the display had already been built by the store’s staff, but the rep takes a photo of that display and attaches it to the electronic record for that store as ‘evidence’ of their own work.

How can the sales agency’s management verify the claim of a sales driving action? How can the brand owner be sure that all of the aggregated claims in the agency’s weekly report reflect the reality of the week’s work?

They can’t of course, which doesn’t make either of them complicit in the fiction, but it does mean that they’re ignoring the flaws in their process.

Is There a Better Way?

Happily for the data scientist, many of the world’s leading retailers make available detailed data about the sales of their suppliers’ products. Often provided via a self-serve web portal, this information can be extremely granular. At the extreme of the granularity continuum brand owners can see the number of units and value sales of every SKU in every store, on a daily basis.

The Scan or EPoS (Electronic Point of Sale) data can then be used to calculate the incremental effect of specific sales actions taken in store.

Of course, the EPoS data is provided at the SKU level, which enables the possibility of recording the incremental sales effect at SKU level too. However, this is only possible if the SFA or CRM (Sales Force Automation or Customer Relationship Management) software also records actions at this level of granularity.

Often a reliable ROI calculation is frustrated by an inadequate software deployment. If an additional display site – a dump bin for example – has been won during a multi SKU promotion, a recording which simply mentions the brand or sub brand, but not the flavours or sizes of the packs in the bin will be insufficient for a solid calculation.

This means that a fundamental prerequisite for a dependable ROI calculation is field sales software that enables all actions to be recorded at SKU level, including the facility to attribute multiple SKUs to a single action.

In contrast to the dumpbin example, some calculations are relatively straightforward. If a SKU which should be ranged has been accidentally delisted at local level and a field sales person manages to get it relisted by the store, it is reasonable to conclude that the sales recorded subsequently can be attributed to the rep’s action.

However, the final calculation must be more nuanced than this.

Whatever the nature of the sales driving action, the calculation methodology needs to provide for two comparison points. The effect needs to be measured ‘Before and After’ the sales intervention by the sales person. That means that we need daily data from the retailer, a date stamp for the visit and information for the SKU on which the action was taken. We can then measure the impact over time, normally taking at least 7 days prior to the action and 7 days afterwards.

In order to make the calculation robust, we also need a ‘Test vs. Control’ environment, for which a control group of stores is required. The members of this control group comprise a statistically significant sample of similar stores which are alike in all other respects save one – they are not visited by the brand owner’s field sales team.

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The sales in these stores are compared to the sales in the ‘test’ store – in other words the store where the action was taken. The actual effect of the rep’s action is the result of a calculation which considers not only the increase in sales in the test store, but also any change in the sales of the control stores.

Imagine that a sales action is taken to improve the visibility of an ice cream SKU. Over the next week the weather improves dramatically, temperatures soar and sales increase considerably. Without a control group a simple ‘Before and After’ calculation would attribute all of the increase in sales to the action taken by the sales rep.

The weather would have impacted sales positively in the control group as well, giving us higher baseline sales for our incremental sales calculation. Now we can subtract the increase in the control store from the increase in the test store to allow for the effect of the weather and highlight the net impact of the visibility improvement.

Armed with the outputs from this highly granular and accurate way of working the brand owner can generate highly valuable insights to help drive sales.

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Field Sales Managers can easily see which members of the team are producing the best sales results and where coaching support is required for those performing less well.

Senior Sales Managers can see which sales actions work best and incentivise these activities to drive the right sales driving behaviours.

Customer Marketing Managers can study which promotional initiatives most require help in store from the field team, and in which categories different discretionary display types have the greatest effect.

Is it Worth the Effort?

To take advantage of the multiple benefits associated with transparent Field Sales ROI, a brand owner may need to change its ways of working. Collecting store visit data at a more granular (SKU) level will likely require changes to data collection procedures, SFA software updates and training of sales staff. Incentive schemes will need to be rewritten. The contract with the broker or agency will also need to be renegotiated.

That’s quite a workload. So, in addition to the benefits listed earlier, what is the bigger picture?

One massive positive change will be in the way that resources are allocated to retailers’ stores. Today a list of stores to be visited (a call file) is normally generated based on the size (sales) of each store. The smallest stores in the retailer’s estate will be left off the list, whilst the bigger ones will receive the greatest number of visits.

That means that the biggest stores will get the most field sales time, whether they need it or not. That still sounds logical, so why wouldn’t they need this extra effort?

The answer is simple. Often the biggest stores are the best managed and have the fewest problems. They are in the spotlight from the retailer’s head office, so they’re also the most likely to adhere to head office policy.

This means that they’ll have the highest level of compliance to suppliers’ head office agreements and be the most resistant to a sales rep trying to get a little extra display space.

An ROI based approach soon exposes the vital facts when the incremental sales generated in this type of store are below expectation. The call file can then be flexed accordingly. The best, most compliant stores will still be visited frequently, but maybe for less time per visit, or even with a small reduction in visits too.

That time can then be reinvested in stores which need it more. These will typically be stores already achieving a strong ROI based on the store’s poor levels of compliance to head office agreements and their higher levels of receptivity to local negotiation by the rep.

At times of seasonal peaks (Christmas, Easter, Valentine’s Day, Halloween etc.) this discretionary approach can prove even more valuable as resources can be diverted from stores with low incremental potential to those where the opportunity is greatest.

As resources at store level are gradually optimised the overall national ROI improves because sales personnel are assigned to the stores which produce the best incremental sales for the investment in effort.

There is another, more subtle effect.

As sales teams become aware of the financial impact of their actions, a change in mentality occurs. The emphasis of the business demonstrably moves from being focused on activity to being focused on the sales impact of activities.

That’s a significant cultural shift. The number of displays claimed in a week is no longer king. The incremental sales generated becomes the most important focus area. Sales teams become competitive about their ROI rather than their activity levels.

Regional Field Managers concentrate their coaching activity on improving the skills in the areas which make the greatest financial impact.

POS (Point of Sale) materials that work are provided in greater numbers. Those that don’t work as well are deprioritised or cancelled entirely.

The business can become totally re-energised by a fresh new approach that values the right actions in the right stores and provides transparent measurement and reporting to keep the improvements coming.

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Introducing an ROI mentality to a CPG sales team is a major undertaking, but one which can produce sparkling results.

In categories where the accepted ‘rules of the game’ mean that all players provide large field sales teams, the results can be dramatic.

For the brand owner that achieves differential advantage the prize is significant, and the effects long lasting.

CONCLUSION – THERE’S A BIG UPSIDE FROM MAKING THE CHANGE

About 20:20 RDI

20:20 RDI was established to pro-vide actionable insights for consum-er goods companies by analyzing retailers’ Electronic Point of Sale (EPoS) data. In recent years, a grow-ing number of enlightened retailers have made this data available to suppliers, with the aim of driving mutual efficiencies, especially in optimizing retail execution. More recently the granularity of the available data has increased, so that brand owners can now see sales of every product, in every store in a retailer’s estate, on every selling day of the year.

This means a mountain of data, presented in a different way by each retailer. Our software allows brand owners to interrogate this data, driving insights and highlighting opportunities to increase sales and improve salesforce ROI. We work with data from major grocers, department stores, pharmacies and convenience retailers in many markets across the world. Our clients range from the 2nd largest food manufacturer in the world to companies with less access to analytic resource keen to discover what the latest thinking is in this area and how it can apply to them in their situation.

In June 2017, we were acquired by StayinFront, Inc., a global leader in salesforce automation and retail execu-tion. This allows us access to significant product develop-ment and customer support resources and provides our clients with even better levels of customer service. We also have a worldwide network of offices providing sales and pre-sales support as well as ‘follow the sun’ help desk provision across all time zones.

Visit 2020rdi.com or email info@2020rdi.com to learn more.

About StayinFront, Inc.

StayinFront, Inc. is a leading global provider of mobile, cloud-based field force effectiveness and customer relationship management solutions for consumer goods and life sciences organizations. Companies of all sizes, in over 50 countries use StayinFront software to streamline sales operations and reduce the complexity, time and expense associated with field efforts. StayinFront products are seamlessly integrated to provide companies with timely, accurate field data and actionable insights, enabling field reps and management to Do More, Know More and Sell More. Headquartered in Fairfield, New Jersey, StayinFront has offices in Chicago, Canada, the United Kingdom, Turkey, Ireland, India, Australia, Singapore, and New Zealand. Through its 20:20 Retail Data Insight subsidiary, StayinFront delivers stand alone and tightly integrated actionable insights and guided selling by analyzing retail data to brand managers and sales forces around the globe.

Visit stayinfront.com or email sales@stayinfront.com to learn more.

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