Market sectorization: how to reconcile a theoretical ideal with ground truth
Sectoring a territory involves creating a coherent structure of territories that are compact, but above all balanced in relation to representative business indicators: revenue, numbers of customers or sites to visit, workload, market potential, and so on… Powerful algorithms can now be deployed to come up with a hypothesis for an optimum sectorization.
This kind of hypothesis takes into account and cross-references multiple quantitative parameters and frees up a vision of something that is not necessarily bound by any existing sectorization or tied to the particular criteria that inspired what went before.
When presented with a proposition that is optimized in theory, respecting statistical values, with balanced territories in terms of distances travelled and individual workload, it is common to see fierce reaction on the part of mobile teams already working the sectors concerned. Claiming to know better thanks to their longstanding experience in the field, staff will usually take issue with the proposal and say it is unrealistic because it doesn’t take account of this or that constraint: longer distances to be travelled, having to use a route that is always prone to traffic congestion, or some other issue that would have a negative effect on their productivity and hence on their capability to achieve set targets.
Sectorization, as calculated by an algorithm, is therefore only very rarely – and maybe even never – applied ‘as is’ without a fine-tuning stage at the end. A whole raft of tweaks and adjustments will turn out to be essential to incorporate information that is hard to quantify, and which the algorithm could not possibly take account of: the quality of the relationship with certain customers is one of these, and then respect for the portfolio history is another… Vital to the calculation of course, will be where staff actually live, as this is bound to change over time. Nonetheless, we can usefully devote some time to measuring the effects of these manual fine-tune events, as all too often, in seeking to satisfy all interested parties, and protect the status quo, there could be a less useful tendency to revert back to the original sectorization: less than ideal, for sure, but a scenario that is already accepted by teams on the ground. The danger is to allow this to over-influence thinking, and risk side-lining a plan that could promise substantial gains in efficiency.
The challenge is this: how to manage the fine-tuning of the theoretical sectorization delivered by the algorithm without losing any of the benefits proposed, and also without reverting back to the previous model with all its shortcomings. At this point, you have to ask the right questions, and knowingly make decisions and possibly even compromises, at several levels.
1st consideration – should the priority be where staff live, or opting for perfectly balanced sectors?
The first issue to address, prior to sectorization, is the following: when creating sectors, should you take as your starting point the reference locations for individual staff (home addresses, branch office or agency of affiliation) OR conversely, create a number of defined sectors as a function of workload to distribute, without fixed departure points, and then attach sales staff to these as a second step?
There isn’t really a ‘right’ and a ‘wrong’ answer to any of these questions: it all depends on the business strategy of the company, and the direction this is taking the activity, as well as on the nature and behaviours of the sales force in question.
We can useful look more closely at two types of situation. The less common of these is as follows: if the sales force are established, and well spread out over the territory to be covered, it could prove sensible to use their home addresses as the departure point of choice. This means that sectors generated will be realistic as to daily distances travelled: a staff member can always be more efficient if, at the start of a new day under a new regime, they find themselves working their own patch. This configuration will mostly be good news for most sales staff, and they will in turn prove to be more effective in the short term. It does require, nevertheless, good coverage of the territory upstream: for example, if all your sales staff are concentrated in and around the city of Bordeaux, and the sectorization has to cover the whole of the South West, it would not be realistic or prudent to generate your sectors using private residences of staff in the team as the starting point.
The second scenario to consider is what tends to happen when sales teams are subject to high staff turnover. In this case, constructing sectors as a function of the home addresses of sales staff would force you to regularly reconstruct the sectorization, and risk damaging valuable customer relationships built up over time. Much better that territories are dividedup in a balanced way in terms of workload and potential, and then allocated to staff by managers. The advantage of this is that sectors proposed will be stable over time, unless, of course there is some kind of radical transformation of business activity for the zone. You need to be aware that this option could potentially be a source of more volatility when assigning new sales staff to an area that is not ideal in relation to their own geolocation, and carries the risk of a less than ideal coverage of customers or prospects distributed over the territory because of the penalties afforded by longer journeys or routes.
2nd consideration – making manual modifications to preserve and maintain privileged business relationships
While the algorithm will suggest the best possible solution in relation to quantitative indicators (drive-times, sector balancing), certain indicators are not easily quantifiable, as they are relative. The relationships between customers and resources belong to this category: many have been built over years, but apart from in terms of specific quantifiables, their true ‘business’ worth cannot be taken into account by the algorithm.
It will be possible to preserve some important aspects of these privileged relationships through manual tweaking, and by juggling the relative merits of each to decide between those that should be kept at all costs and those that can be transferred with relatively little negative fallout to a new salesperson, the aim being to constantly strive to avoid creating the same sectors as before.
So it will be possible to some extent to rearrange the allocation of customers to the margins of the newly proposed sectors, or again to create enclaves within a sector in the interests of preserving certain privileged relationships. These modifications are made nevertheless to the detriment of the optimization: customers that are far away from the sector will be more costly to visit, in terms of distance and time.
3rd consideration – including all actors concerned in the sectorization process, and recognizing and acknowledging the value of their knowledge of the terrain
Last but not least, it is vital that staff – regional directors or sales staff concerned directly – are included in creating the new sectorization, as these are the people who are really up to date as regards ground truth. They are best placed to identify any anomalies in the constitution of the proposed sectors, notably in terms of accessibility and feasibility (taking into account road traffic conditions, easy access routes, tricks of the trade…).
Importantly, their knowledge will be indispensable to help with decisions influencing the final shapes of sectors thanks to their perception of work equality. For HR reasons, it will be unwise, for example, to design sectors that are completely city-based or rural within the same region. This will inevitably lead to tensions, and unwanted pressure to reshape sectors in ways that may not be logical, or profitable.
When actors concerned by change at all the various levels are called upon to advise on sector creation, they will feel in turn some recognition for the expertise they have, to good effect. Seeing their knowledge of the terrain valued, they are less likely to oppose any proposed changes, and positively relish participating in designing the new structure. While their knowledge of the business constraints and peculiarities of the terrain will certainly not be taken into consideration by the algorithm, these have unquestionable value when it comes to manual tweaking and putting in place the final touches on sectors to deliver a result that is both more realistic, and better accepted.
The possible pitfall to beware of in a manual sectorization, as a follow-on to an automated one, is to reproduce, almost unconsciously, the historical structure. For a successful transition towards an optimized sectorization, you will need to put change management in place for all actors concerned: teams on the ground, managers and regional team leaders, but also the customers who might see their principle company contact change. Re-sectorizing and fulsome cooperation go well together: make sure you integrate all levels concerned, and not just the managerial level, in order to get clarity and as much knowledge of the terrain as possible added into the equation. The counterpart to this investment in change management is good uptake and bonding with the new structure – the new sectorization should fulfil the promise of more efficiency and greater savings for the company because it has been rationalised by the algorithm, and it will be well-received because it takes account of the human dimension and individual expectations.