Hello, and welcome to our demonstration of Certinia PSA: Services Revenue Forecasting. Most services organizations don’t have an easy way to forecast revenue for their active and pipeline projects. Typically, this is being done in spreadsheets – which isn’t efficient or accurate. Our PSA Services Revenue Forecasting solution helps our customers to move away from static forecasting reporting, and to operationalize the revenue forecasting process. Not only will this get you out of spreadsheets, but it also will provide your organization with more confidence in the accuracy and timeliness of the data. Additionally, we give you tools to analyze your forecast for key insights into trends and change between versions of your forecast.

Let’s take a quick look at the revenue forecasting process. We start with the forecast calculation. What this does is it looks at the projects and opportunities that you wish to include in your forecast, and it creates monthly forecast records for each project and opportunity. We are able to forecast project revenue using common revenue recognition methods: deliverable-based, which is time based revenue; or perhaps milestones that are recognized all at once based on a specific date. We also can accommodate equal-split methods. So, if you have a milestone, for example, that you’re going to recognize evenly over a certain time period, we can forecast it in that way. We also support percentage completion for milestones and projects, which is often a challenge for our customers in their forecasting. You can schedule the forecast calculation to run for your whole organization, or you can also run it on demand for specific projects and opportunities. As you have changes to projects and opportunities, when that calculation runs again, it picks up those changes. So, your forecast calculation stays up to date in that sense.

Once we have calculated forecast records, the next step is to create what we call a forecast version. Forecast versions can also be scheduled and created automatically. A forecast version is a time period that you define, and it’s the time period in which you wish to view your forecast. So, some organizations just look at current quarter. Some look at current quarter and next quarter. Some prefer a rolling 6-month forecast or rolling 12-month, but we have about six options you can choose from in creating that version in viewing it.

The version also takes the detailed forecast data and summarizes it by region, practice, or group. So, you can get a summary at those levels as well as drill down into the details of each. Then, we give you the ability in viewing the forecast version to compare it to other versions.

We also offer the ability to make manual adjustments to versions. Some organizations simply create a forecast and view it. Others like to make manual adjustments to create different scenarios to reflect potential or known risks and upside. This is very commonly done in spreadsheets, but we give you the ability to actually do this within the PSA solution.

Then, once you’ve finished making adjustments, and you wish to use that particular forecast version – the adjusted version as your official forecasts that you’re reporting, then you can lock that version from further changes.

We also give you reporting and analytics so you can get key insights into not only your forecast breakdown but also your accuracy and trends of your forecast over time.

So, at this point, we will switch over to live product and actually walk through that forecasting process that we just had the overview of.

So, in this view we’re looking at a project. On this project is a deliverable revenue-based project, meaning that we have some time-based revenue coming from time cards, and we also have set up in our project some milestones that we’re billing. So, you can see we have a series of six milestones. One has already been approved, and then the rest are planned. Each one has a target date associated with it as well as a dollar amount. So, when we run forecasting, it’s going to pick up all of the planned milestones, and forecast them according to the target date. It will forecast the full milestone amount according to the target date.

The one on the top line here will be counted as actual revenue in the forecast calculations. So, our forecast calculation will calculate how much in a given time period is attributed to actuals, and how much is still scheduled or forecast revenue.

If we go and look at project forecasting just for this project, at a glance I can see a chart that shows me my forecast revenue by month, and then below that we see the detailed calculation records. So, when we run that revenue forecast calculation, what it’s doing is calculating very detailed forecast records by time period. In this case, these are monthly time periods. For each time period we can see how much revenue is scheduled. We also can see over here how much is actual revenue. This detailed data is what gets pulled into our overall services revenue forecast.

Again, this is a deliverable-based method that we just looked at. We can also support, again, percentage completion for projects, as well as equal-split revenue method forecasting.

Okay, so now that we’ve looked at the actual forecast calculation, we’re now going to come to our Services Revenue Forecasting Workspace. From this workspace we can perform certain tasks. For example, we can recalculate our revenue forecast. So, again, as we have changes to projects, we want that reflected in our forecast so it’s as accurate as possible, and that can be scheduled to run. We can also run it on demand from here. So, if I’m going through a forecasting exercise, and I want to make sure that I’ve got the most accurate forecast data as possible, I could go ahead and recalculate it.

Then we can also create the forecast versions from here. So, the forecast version is taking that calculated forecast data and summarizing it into our forecasting time period. It also is summarizing it by region, practicing, and group. We can view the forecast here. This chart we’re looking at is our forecast for our services organization. In my view, my forecast version is a 6-month rolling forecast. I can change the time interval over here. So, we have filters, and I can change the from period and the to period, and will dynamically update this. If we look at all the to periods, I can select from any of these months in that list.

We can also switch from a monthly view to a quarterly view just by toggling over to the quarterly button. We have other filters here as well. So, depending on your organization and the size and how you have chosen to configure your PSA org, you may have different regions defined, you may have different practices, and different groups. So, if you are a larger organization and you have different regions and you want to actually look at your forecast by region, you can do that here.

So, right now I’m looking at all of my regions, but I can easily toggle this to, for example, just look at Australia. If I just want to look at Australia’s forecast, I can do that, and it dynamically updates as I do that. Or, if I want to look at certain practices. So, let’s look at our consumer practice. When I look at consumer, we can see we have a fair amount of unscheduled revenue in our forecast for consumer. Whereas, if we look at our financial services, most of it is scheduled revenue.

We also have options to filter on project, on account name, project manager name, as well as on opportunities. So, again, this forecast can include your opportunities as well. It is an option as to whether or not you wish to include them.

I want to point out the colors in the legend here. The darker blue represents your actual revenue. So, we can see that in this first period here of the year, we do have some actual revenue. Then everything in the lighter blue is considered scheduled revenue – so, that’s forecast. Then we have unscheduled revenue, which typically is coming from our opportunities.

Down below, in this chart, this is where we can actually compare two versions. I’m looking at my live or my most current version compared to a version that we created back in December. If I click on this, I’ll get a list of all the various versions that we’ve created, and I can pick any two versions to compare.

Over here on the right, it shows me my variance between the two versions and highlights that it was an increase of 9.18%. I can also visualize the versions in this chart below.

From here, I can drill into details to understand what changed between the two versions. This is where I can really start to get some insights into that.

So, let’s drill down into the details here. At the top, we can see trends between the two versions that we’re comparing. So, again, the light blue is my live version; the darker blue is my December version that we’re viewing.

Down here, if I want to understand, okay, where do we have changes in our forecast? I can see there’s quite a bit of change. If I look at this by our practices: quite a bit of change in the two forecast versions coming from our financial services practice and some as well from our consumer practice. I can look at this by region, by practice, by group, or project manager, or project. If we want to dive into the consumer practice and say, okay, what, what in consumer practice has changed between our two forecast versions? As soon as I click on consumer, it changes this chart over here, and I can see these are the projects contributing to the variance. Specifically, I can see this analytics project is the biggest contributor to the variance. If I click on that, then, below, I see details on that project. So, there’s a milestone on the project, and it also gives me some information on the overall project. What I can see is that, in our current forecast version, we have a milestone of $60,500 that did not exist in the prior version in December. So that’s why we have a variance there. Just the overall project dollar revenue amount is higher in this live version versus our earlier version. So we can see where that variance is coming from.

Okay. So, we have reviewed our current forecast version, and we compared it to a previous version, and we were able to drill into insights into what had changed between the two versions. A lot of organizations will simply utilize this forecasting analytics tool here for viewing their forecast data. However, some customers take it a step further and like to make adjustments to their forecast version. Again, this is very often done in Excel, but we offer a way to do that here within PSA without having to leave it.

Going to this review forecast version brings us to this page. So, on this page, we can pick the version we’re viewing, and I am viewing our current live version of the forecast here. If we scroll down, we’ll see our forecast summarized, in this case, by practice. So, again, you can define in your forecast set up if you want to view your version by practice or by region or by group. In this case, it’s by practice, and if I expand a given practice… So, let’s expand high tech, then we can see what’s comprising my forecast for the high tech practice.

So, I’ve got six projects here. If I had opportunities, they would also show up here as well. If we look at the deliverable project – this is the one we looked at earlier – and we look at what’s forecast, we can see that we have these two milestones that are forecast in our view. If we go forward to March, we can see that this payment number three for $40,000 is scheduled for March. Right now, it’s in all three of our scenarios. So, for every month, we have a worst case, an expected, and a best case. This is where we can make adjustments to the forecast. We can either make adjustments at the milestone level, we can make adjustments to the overall project, or the overall practice level as well. So, in this case, we’ll make an adjustment to the milestone.

So, I’m going to go into this $40,000 milestone in our worst case category, and we’re going to adjust the value down to zero because we have some project delays, and we know we’re not going to be able to get this revenue in March, and we think worst case that this is going to push out to, say, the May timeframe.

So, in the target time period, we can select May. Not only is it going to make an adjustment to March, but it will also make an opposite adjustment in the May time period, moving that $40,000 to our May worst case category. So, we’ll adjust that, and then we’ll also adjust the expected.

In reality, we think that we will really be able to pull this milestone in April. So, it’s just going to be pushed out one month, we think, so this will be our expected forecast. So, I’ve made those changes here. Our best case is still getting this milestone in the month of March. I’m going to save the changes I’ve just made. You may have noticed that there are these red indicators in some cases, and in other cases there are green indicators. These are really there to make it known that a change was made. If you hover over it, you can see very clearly what the variance is, and what the percent variance is, and whether it’s an adjustment up upward or downward.

As we make changes here and save them, we can view them up here in this chart as well. So, we’re able to see the difference between our best case, our expected, and our worst case. So, once we’ve completed all of our adjustments to the forecast version, and we’re ready to report this out as our forecast for the time period – whether it’s for the current quarter or some other forecasting period – we can lock it from further changes by clicking on the lock version button.

Depending on our forecasting cadence, a new version will be created in the future, and we would go through this same process at that point in time.

So, to summarize, we’re able to generate a forecast without exporting any data out of PSA. Because our forecast is generated directly from projects and opportunities, we can easily gain insights into the trends and what has changed version to version.

So, I’d like to thank you for your time in watching this demonstration. I hope it was informative and that it proves valuable in your decision making.