Collaborating on Sales Data
Discover how to collaborate on sales data with Claret. Understand the reconciliation process, learn how to spread forecast data, and make impactful updates to your sales plan.
The power of Sales Collaboration is in the ability to work with and manage the same set of data across the business so that everyone is always on the same page.
Updating sales plans
The main objective in Sales Collaboration is making updates to the sales forecasts. When we configured the Sales Collaboration page above, we add the "Hist / Fcst" Row Type. We made the "Forecast" Sale Type editable. As mentioned before, it is recommended that this be the only Sale Type you make editable.
When you make a Sale Type editable, you'll see in the Sales Collaboration page where you can make edits or updates to your sales plan.
Unless you are at the lowest level of the Item hierarchy and the lowest level of the Customer Group hierarchy, when you make an update, Claret will take your number and spread it or reconcile it down to the lowest level Item @ Customer Group for that month. See the Reconciliation section below to read more on how this is done.
Reconciliation
So, how does the reconciliation work? Let's review the below illustration. In the "Old" column, the ZAM Brand has a total of 100 cases which is the sum of the three items within that brand. In the "New" column, someone has overwritten the 100 cases at the brand level with 200 cases and that has reconciled down to the underlying items based on their respective contribution percentage (derived by their existing quantities) to the brand.
This reconciliation methodology is also used in Long Term Planning.
Spreading forecast data
At the end of each row of data, there is aggregated values for half years (H1 and H2) and quarters (Q1, Q2, Q3 and Q4). These show the total value for the months they cover. For example, if Oct, Nov and Dec have sales data of 6850, 7144 and 9329 units respectively, then the Q4 total will be the sum of these.
If the Sale Type we are working with is editable, then we can use these aggregated figures to also make updates to each period. The way we do this is by 'spreading' the forecast data.
For example, if we wanted to update our Q4 forecast above to be 26000, we could do this by clicking on the value, and entering this into the value box.
Once we do this and save, as is noted in the box, this will then 'spread' the forecast across Q4. The spread happens in a weighted manner so that the contribution each month was making to the quarter is maintained.
| Month | Original value | Contribution to original total | New value |
|---|---|---|---|
Oct | 6850 | 6850/23322 = 29% | 26000 x 29% |
Nov | 7143 | 7143/23322 = 31% | 26000 x 31% |
Dec | 9329 | 9329/23322 = 40% | 26000 x 40% |
Spreading the forecast in this way will also result in a reconciliation downwards as well if the spreading is being done at a parent level. (See Reconciliation)
Spreading the forecast using this feature can result in a lot of data being updated very quickly so make sure you are clear on what will change when using this feature. You may wish to have a sale type you use to test spreading forecasts prior to making updates to your actual forecasts.
What happens though if you use this feature on a combined history and forecast row (Hist/Fcst)? In this instance, the 'spread' will first take away any historical data that can't be updated, and will only spread across forecasts.
For example, if we are in August, and wish to update H2, July has already past, so we won't be able to change the data for July. Spreading the H2 forecast will first subtract the July value, and then spread the remainder over the remaining months. So if are moving the H2 total for the CLM Central Coast White from 31,759 to 33,000, the July figure (2607) will first be subtracted because we can't change that now. So we will have 33,000 - 2607 = 30393 to spread across August - December (and July will remain at 2607).
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