Video Transcription
Hello, everyone. Thank you for attending C cube live. It's good to see you here today. Before we get started, I'm just gonna go through a couple of quick housekeeping items.
So first is our live q and a. There's probably gonna be a lot of questions throughout this presentation. So if you have any, feel free to drop them into the q and a down below, and we will have time reserved at the end to answer those questions for you. And then next is the recording and slide.
So as you've seen, in the emails that you've received, by attending this webinar, you have also guaranteed that you will receive the re the full recording as well as the slides that we go through following the webinar today. So if you're nervous about missing anything, don't worry about it. You'll be able to review everything after the webinar is complete. So without further ado, I am going to hand things off to Taylor, who is going to be going through the demo today.
So, Taylor, take it away.
Thanks, Alyssa.
So thanks everyone for joining today's session. Really looking forward to kinda showing off CUBE in more of a health care biotech specific format today. I'll quickly introduce myself here. My name is Taylor. I've been a solutions architect at cube for about two years now. Come from an FP and a consulting background in the past. So used to implementing lots of other tools out there, namely Hyperion s space, t m one and one stream.
Really looking forward today, though, to kinda showcasing what I love about Qube and why I think Qube is really the best solution in the space today.
Our agenda here for today's session, we're gonna start for any folks who haven't yet seen demos of Qube just with kind of a brief introduction on Qube, running through a couple of slides right off the bat. Then we're gonna dive into the live demo portion where we're gonna cover a multitude of different topics, and we'll reserve time at the end as Alyssa mentioned for some q and a as well as share casing some resources for you as well. Next slide, Alyssa.
But we're gonna kick things off here with a brief poll just to kinda get a sense of what people's current challenges are when it comes to running your FP and A processes or kind of what topics you feel like needs improvement.
So your choices here are are forecasting the effects of patient volumes, revenues, and service utilization feels very challenging.
Option b is conducting what if scenario analysis.
C is identifying cost improvements for medical supplies and pharmaceuticals.
D is monitoring and adjusting staffing levels based on patient volumes, e is identifying and adjusting for potential shortfalls in revenue, and, of course, there's an other option as well.
So feel free to make your selection there, and I'll be kind of revealing what the most common response was here next.
Alright. Looks like the most common response here was conducting what a scenario analysis feels the most challenging in your FP and A processes. So that's definitely gonna be something that we'll address during today's demo, something that I hear from customers across a multitude of different industries as being a really challenging facet of their business.
Awesome.
Well, for the introduction to queue portion here, we're gonna run through a couple of slides here just to kinda set the stage. So starting with this kind of introduction slide here, this is really gonna be a demonstration of Qube today, really showcasing how Qube is a holistic FP and A platform. And what I mean by that is Qube is built to really help you handle and better automate your financial and operational reporting, planning, budgeting, and forecasting.
We kind of reside within a cloud hosted database, but the primary interface of working with all of your data that's coming from that cloud database is a spreadsheet, which is really what makes you cube unique in the marketplace.
We don't force our customers to handle and work with their data in a proprietary web grid, a web portal or platform, you're able to really report out on and plan around all of your different what if scenarios and use cases where you're comfortable working today, which is either in Excel, Excel online, or Google Sheets.
And next slide here, Alyssa.
And kind of the old way that a lot of other Fpne tools in the market used to kind of approach spreadsheet driven FP and A processes was through really outdated technology, really rigid coding schemas, syntax, and logic set up in the spreadsheets to allow Excel or Google Sheets to talk to their underlying databases.
Those types of tools are inherently really difficult for customers to own and manage themselves because they're typically gonna have to rely on a lot of technical expertise or consultant involvement when it comes to getting their models set up and modified over time. We like to take what we call the cube way or the cube approach when it comes to managing your data within spreadsheets, and this is gonna be driven off of more modern technology. We're using a patent pending API technology that allows our system to talk to spreadsheets without all of that convoluted coding language in the front end, which inherently is gonna make our platform much easier to use, quicker to implement.
It's gonna give you also more ownership over your models and ownership over any changes you might wanna make as well, ultimately making Qube a much more scalable and flexible solution that can be really designed to handle data coming from customer source systems regardless of whatever industry they're working in.
Next slide here, Alyssa.
And this slide kind of illustrates the approach to kinda how we handle that data synchronization behind the scenes. So walking from left to right here, what we're gonna do here behind the scenes in cube is connect and map into any of your source systems to pull that data into our cloud database, and these source systems can either be financial general ledgers like NetSuite, QuickBooks, maybe it's Oracle Cloud, or maybe it's more of an operational source system like Salesforce, HubSpot, maybe it's also something coming from a payroll system. Regardless of of whatever data you need to pull in for your reporting and planning, we're gonna house all of that in one centralized source of truth in the cloud. But again, that key differentiator with Qb is that you're not working in a web portal with that data, you're gonna be able to report on that data and plan around that data within a spreadsheet environment.
So no matter where you and your teams are currently working, whether that's Excel, Excel online, Google Sheets, on PCs, or on Macs, or a combination of those across your business, you're gonna be able to reside where you're comfortable, keep your existing models, easily spin up new models from scratch, and you'll also always have the ability to push your data out of cube and upload it back to something like a BI tool as well.
Next slide here, Alyssa.
So our agenda here for today, we're gonna kick things off by running through some reporting and analytics examples where I'm gonna show you just how easy it is to spin up new reports from scratch using our ad hoc feature, how we can also automate existing templates and models that you might have set up in spreadsheets today, and we'll also cover some data visualization topics here. Then we're gonna move into kind of the back end structure of this real briefly just to kind of highlight how we're handling things like your different business hierarchies and organizing your data, how we're pulling data into the cloud from your different source systems, kind of more of that admin level perspective of things.
And then after that, we're gonna cover some planning and modeling topics. We're gonna look at collaborative department level budgeting and planning. We'll also cover more health care and biotech specific examples here as well, such as maybe planning around clinical trials or expenses across various clinics.
And we're really gonna focus in on how easy that collaboration and that workflow piece is within Qb.
But without further ado, I'm gonna take over the screen here, and we can start diving into the demo portion of today's session. So again, where we're gonna start here is from more of a reporting and analytics use case, and then we're gonna kind of flow into other topics as we move throughout this piece.
But what I'm gonna showcase here first is really gonna emphasize the ease of use when it comes to spinning up new reports from scratch utilizing q.
So let's say I'm working with Alyssa today. We're working on building out a new report, and we wanna see data coming from multiple different source systems like our general ledger, our CRM, maybe our payroll system.
Building up new reports from scratch without a system like Qb is inherently really difficult because you're forced to create static data dumps from your general ledger and other source systems, manually consolidate that data using spreadsheet logic. It gets really tedious to update those models over time as well. But when we're utilizing Qube, what I can do here is starting from a completely blank spreadsheet tab, I can now allow this spreadsheet to talk to all of my cloud hosted data that's residing in that cube database by using this add on here within either Excel or within Google Sheets.
Anything I'm showing you here today in Excel is gonna work the same way in Google Sheets. But in order to build up a new report from scratch here today, what I'm gonna do is click on this new button and this is gonna show me all of the different slicers of my data that I have available behind the scenes. Your slicers might look different. I have things like my accounts hierarchies, my departments, products, and markets in this model, but yours might be clinics, pharmaceutical that you're producing.
But what I can do here to build a new report from scratch is simply drag and drop these slicers into either the rows or the columns of this spreadsheet here, kind of like a pivot table. So I'm gonna take my accounts that I wanna report on and bring those into the rows. I'll pull in my entire income statement hierarchy, and maybe I also wanna pull in some metrics coming from my CRM, which is Salesforce. So maybe we wanna look at our customer bookings, maybe our customer counts, our new logos, and maybe let's also pull in some HR specific metrics like the number of FTEs we have, maybe their salaries and their taxes.
So data from three separate systems is gonna be pulled into the rows of this report, and maybe I wanna report on this data for the past two years. I'll bring in two years of data by selecting time across the column headers, and maybe let's also nest our scenario or whatever version of data we're reporting on here such as our actuals.
If this is all we need to see in the rows and columns, we can go ahead and add our other slicers as filters down below. And to actually generate this new report from scratch, I'm not building any code, any cube specific syntax here. All I'm doing is clicking fetch data, and cube is now automatically constructing and populating this new model for me in a matter of seconds. And it can even collapse for me any rows that don't contain any data.
And now I'm gonna zoom in here a little bit so it's easier to read. But since Qube is founded on that more modern technology without the use of any complex syntax or code in the formula bar or hidden in the rows and columns here, I can now start to reformat this report however I want to before I start sending it out to other departments and other end recipients.
So to make this report look a bit more polished and professional, maybe what I wanna do here first is get rid of the grid lines right away. Maybe I also wanna break up some of these accounts with spaces between the rows. These are activities that would have previously taken me a really long time to do, and they also might have gotten wiped out in some of those more legacy tools that I was using in the past because they were typically confined to more rigid formatting structures.
I'm also making all these adjustments to my formatting here just like I would normally in a spreadsheet, so there isn't gonna be a heavy learning curve for me here when it comes to making these changes.
Maybe Alyssa also asked me to get rid of something here within this report, like, maybe get rid of the quarters and the years. Maybe she just wanted to look at the months. I can go ahead and start selecting out portions of this model that aren't relevant for my reporting today, like all of these quarterly columns. And as I start selecting these and deleting these out, again, cube is not gonna break on me.
It's gonna react exactly as any spreadsheet would to that change. I can also add spaces in front of the rows, above the column headers if I want to. And maybe between a couple of these months of data, I wanna see something like my year to date actuals between March and April. What I can do here with Qb is simply insert a couple of columns like I normally would in a spreadsheet.
I can reference these headers containing my actuals, the month of March, and throw in a handy time shortcut referencing year to date. And I don't have to build any logic or formulas to this column like I would in a previously static Excel report. What I can do to see this data here is just simply click fetch data, and q will do all that work for me of dropping in my year to date actuals, again, without me having to manage tons of formulas and lookups in the spreadsheet.
So the process of collecting, consolidating, and aggregating your data is gonna be much faster when you're building new reports from scratch, and you can also easily update what data you're pointing out here as well. I'm looking at just my actuals right now, but since I don't have actuals for the remainder of this year, maybe I wanna bring in my budget. Now instead of having to require cube staff to build a new template for me, paying exorbitant consulting fees, What I can do here is simply type budget myself over these headers, carry that across my spreadsheets. I'm not changing anything here in this sidebar or any formulas or logic here. All I'm doing to get that data is clicking fetch one more time, and q is gonna do all the work for me of updating this model with my budgeted data without blowing up all of those earlier formatting adjustments that I made out to the left.
And now we can see here that I have my financial metrics down the rows here at first, but I also am layering on other detail coming from other source systems. So, again, Qube is not confined to just being a financial solution. This is also a solution built for other teams such as maybe the sales department, the operations department, the HR department for all of us to get that centralized source of truth.
Now, typically, after I walk through this initial ad hoc reporting example, people ask me, what does it look like to automate my existing templates? I have reports formatted in ways that I like, and I don't wanna have to sacrifice that. I'll dive into that piece here next by showcasing this kind of pre formatted template that I have here to report out on a BVA analysis of my P and L accounts and some operational KPIs. Now right now this is simply a template with the different accounts that I wanna report on down the rows, my different versions of my data and time periods across the columns.
There's no syntax or logic set up in these cells here and cube is not yet connected to the There's no syntax or logic set up in these cells here, and cube is not yet connected to this report. But in order to get this report to talk to all of my underlying data that's residing in that cube QCloud database, what I'm gonna do as an end user is simply highlight this report capturing all those row headers and column headers. And in this right hand cube sidebar, what I'm gonna do is click select and select range to ping that cube API.
And cube is now recognizing things in my report that match all my underlying business hierarchies.
It's finding those versions of data, my time periods, my accounts down the rows, other slicers are being added to the filters here. And to see all of my most up to date data flow in here, all I'm doing is clicking fetch data in that sidebar to ping that Qube database, and Qube is dropping all of this information for me at the click of a button.
And now I'm not confined to keeping this report as is. Maybe next month when I have additional historical actuals that I've closed out, I can use any drop down selectors, pivots on my report here to roll this forward to the next month. So we're now referencing the month of June, so that when I click fetch data, Qube is gonna read that updated header and refresh everything for me. I can also rely on these filters that Qube is auto populating for my other pivots of my data that aren't showing up on my spreadsheet. Maybe I wanna filter down to just one of my subsidiary entities instead of reporting on my high level consolidated company. So I can do something like pick my US entity today, click fetch again, and Kube is doing all that work for me of refreshing this data without me having to run static data dumps from my general ledger and other source systems.
Now I can also do something like maybe build upon this report over time as well to bring down more sections of data. We're just looking at my actuals and my budget for June, but maybe I also wanted to see my year to date forecast starting in June. So what I'm gonna do here is simply insert a column like I would normally in a spreadsheet, and I'm just gonna type in the header for my forecast. We're gonna reference that June header, but add in that YTD suffix again. And I'm not adding any complex code or formulas here in this column in order to get this to talk back to queue. I've simply referenced those headers containing that version of data in that time period. And in order to see that data flow in, the only thing I'm doing here is clicking fetch data in that sidebar to ping that Qube database, and Qube is gonna automatically recognize and consolidate that year to date forecast for me on the fly.
And, again, this is meant to kind of display and reflect any existing reports and models that your team might be building out today. This does not have to be a rigid format or structure. This is really meant to showcase how we're able to embrace whatever you have set up in spreadsheets without requiring you to rip apart your existing models, jam them into any proprietary grid or web structure.
Now the first time we're cubifying your reports in the way that I just showed here, you know, things might not perfectly match all of your underlying business hierarchies that you've built into the cloud. That's perfectly fine, but there are ways to automatically fix this as well. So let's say right off the bat, when I've cubified this report, I wanted to make sure that I spelled everything right down the rows and across the columns. What I'm gonna do here is navigate to the sidebar and validate my report, and Qub is now gonna show me any unrecognized fields or dimensions from the spreadsheet.
Some of these issues that Cube is flagging for me, I'm not gonna worry about too much because these are really just headers on my page. For example, Salesforce data personnel details are just headers for these groupings down below. This dollar sign and percentage sign are just headers for these variance columns, so I'll go ahead and ignore those issues. But this first issue here looks like an account code, and I can see there on row seventeen that I'm not getting data back for that row, but I wanna fix that.
I'll do that by simply clicking edit, and I can start searching for that account here. And we'll see that from my cube hierarchies, I should have named this discount on my report, not disk. I had a typo. I'll fix that by clicking on that name, and cube will automatically update that row header for me so that as soon as I go back and fetch my data again, all my data is gonna drop in on that row because Qube can now find that in the system.
And And you're gonna notice that the revenue line that need that did not change because we're no longer relying on Excel formulas to aggregate all of those total accounts up above. Qube is handling all of that work for us behind the scenes, which we'll dive into here next.
Awesome. But, again, this is meant to showcase how we're not gonna rip you out of the place that you're comfortable. So you're also welcome to keep anything that you like in your spreadsheets as well for quick variance analysis and checks. I like to keep my variance columns set up as Excel formulas because if I send this report out to Alyssa today, she's not gonna have to ask me to go into the back end of any system and tell her any underlying logic that was built for these formulas because she can simply reference this as a normal Excel calculation.
So, hopefully, this display kinda how easy it is to build new reports from scratch using cube and how we can easily connect into and embrace your existing models. What I'm gonna pivot into here next is kind of the underlying architecture that's running behind the scenes to help support all of this.
So I'm gonna open up the Qube web portal here next to kinda display some of that more admin facing work here that's happening behind the scenes, and we're gonna start on this dimensions tab. So in Qube, similar to some other FP and A platforms, sample model called CatalystCo here today where I have Now this is my sample model called CatalystCo here today where I have all of my different hierarchies, business hierarchies, and roll ups structured out here across the top. This includes things like my chart of accounts, so my income statement, my balance sheet, my cash flow statement, but it also reflects things like metrics coming from my payroll system such as my FTEs, their salaries, or even metrics coming from a CRM, more operational data from Salesforce like my customer bookings and customer counts.
I have other pivots of my data like my different departments.
I have various versions of data that I can handle and manage within Qube as well. We can create as many of these scenarios as you want to maintain multiple different budget iterations, forecast versions, what if scenarios that you wanna structure out, And Qube is gonna house all of this data in the cloud now versus in the past having to maintain all these scenarios and static spreadsheets.
So what I mean by that is that we're gonna be storing all of your history in an actual scenario in the cloud coming from your source systems. You can, of course, have those actuals locked down to keep them secure. If you have existing plans and what if scenarios, we can load those into cube as well, but you can also keep building upon these versions over time. So right now, I might have an ongoing kind of lockdown forecast that's been approved by the board and it's stored in this forecast scenario, but today maybe I wanted to spin up a new copy of this which is gonna be leveraged for my quarterly reforecast.
Now instead of having to copy and paste data across disparate Excel tabs, what I can do in qb is simply click on that forecast.
I can then create this copy behind the scenes, name it whatever I want to, And right now, this is gonna exist as a copy of that first forecast, but now different budget owners, department heads can reference this new plan in any of their templates in a spreadsheet, make their changes to their data there, and using Qubes built in spreadsheet interactivity, they'll be pushing those changes back to the cloud. And And you'll see this later on in my demo, but since Qube is now handling this data in a cloud hosted scenario, it'll be much easier to report on variances between different versions to track those downstream changes.
You also will have the ability to actualize your data over time by using our merge scenarios feature, and we also have an AI feature called the smart forecast, which allows Qube to auto generate new scenarios for you using an AI generative model that can be fed with data coming from your history or other versions.
Now this is kind of a standard financial example where I have all of these dimensions. I also have different time hierarchies, things like my subsidiary entities, products, and markets. But for a health care or biotech company, we can also set up really any dimension that kind of manages and organizes your specific data. So I'll showcase here a couple of examples. We have this company called Healthy Living Co, which is kind of a conglomerate of different clinics. So in this company, we have, of course, our standard financial accounts as well, but we also are layering on a lot more operational KPIs, such as the rooms available within each clinic, the maximum appointments that different practitioners can take throughout the month. We have things like utilization assumptions for our different employees, productivity percentages as well, All these different KPIs related to nurses as well as KPIs related to some of our technology like our monthly revenue generated by our MRI scans.
We also use a dimension called subregion in this model too to plan and track for all of our different clinics that are operating across various cities, various states here, and we can roll those up into different regional groupings.
And within this cube as well, we also have formulas built to really handle a lot of ongoing calculations that are happening within this company. So for example, something like our monthly provider hours utilized is calculated as our utilization assumptions for our providers multiplied by the maximum one on one hours that they can take throughout the month. Monthly MRI costs are being auto calculated by q. Nurse compensation is calculated by their salaries times the employee count divided by twelve months of the year. So all of these regular ongoing metrics can be built in the back end of Qube to handle a lot of those logic and calculations that you might be doing in a spreadsheet.
Now for more of a biotech specific company, we also have this ABC pharma company here as an example where in this company, we're planning for a lot of different pharmaceutical drugs that we're producing. So we have this drugs dimension here with a list of all those different drugs that we produce. And in the accounts, we have some different metrics namely our different variable costs and expenses that we have for all the different stages of our clinical trials. So we have stage one as a research and discovery phase, stage two, which is preclinical studies, stage three is clinical trials, stage four is approval. So we can start planning for kind of the phases of production of each of these pharmaceuticals.
We can plan for the revenue generated by the production of those pharmaceutical drugs as well, and also planning for other operational expenses like marketing expenses, different employee expenses as well, things like rent and utilities, and also product demand and price per products.
So, again, we can customize all of these dimensions around your business criteria and the ways that you want to slice and dice your data. And once we've set up all that core structure behind the scenes, we can now start feeding in data from your source systems.
So on the source data tab here, this is where we're gonna make connections to your general ledger, your CRM, your payroll systems, maybe a data warehouse as well, and we have a multitude of different ways of connecting to different source systems.
Cube is a really source system agnostic platform. So as long as there's a method of getting data out of a system, we're gonna be able to ingest it either through an API, a direct kinda custom connector, programming file uploads as well. In my case today, I have a connection to my general ledger, which is NetSuite that I can either schedule to sync back into Qube overnight on a weekly cadence more automated. But I also have the ability to always on demand push my data into Qube, specifically maybe during month end close when I'm making lots of journal entries.
So maybe I know that I just made a few entries in NetSuite that I wanna feedback to Qube right away. So what I'm gonna do is click this import button, and what Qube is gonna do is first ask me to resync that connector to my general ledger. So when I click this resync button, what Qube is doing is it's checking that source system for anything new that might have been added there that may not have a place to live in Qube yet. Maybe I built new general ledger accounts within my chart of accounts in NetSuite, or maybe I added a new product line or a new market grouping. Qub is gonna flag all those new items for me first before trying to load in that data and then allow me to go to this really interactive, super intuitive mapping screen that I can start to manage and run myself.
So this mapping screen is gonna show me my full chart of accounts and other business hierarchies from my source system, and it's also gonna show me how I've mapped those items back into queue. This mapping is gonna get set up for you during implementation, but it's incredibly easy to maintain changes here over time. Maybe I don't like where shipping income is flowing into within cube right now, and I wanna change that up. So I can easily pick from this drop down to push that somewhere else, or I can simply apply a filter to navigate to those new accounts that came through from that resync of my data and then decide if I wanna push those into existing accounts that are set up in cube already or build new ones from scratch.
So, again, the idea behind showing you this kind of back end maintenance, the dimensional structures, the data source syncs is really to emphasize that that this is gonna be a customer owned solution where you're not gonna have to rely on cube staff or hire consultants or product experts to maintain this system.
So hopefully, this looks really easy to manage from an admin perspective.
What I'm gonna kinda pivot into here next is more of that collaborative approach of of planning across different departments and how various end users can work to push data back to Qube from that spreadsheet environment.
So I'm gonna open up another template here, and this template that I'm showcasing right now is a model that I use for my quarterly reforecasting in my business. So this first page here is kind of a variance check where I can look at all the departments in my company and compare two versions of their data in these two columns.
This first version is that finalized forecast that has security on it in the back end of cubes, so nobody can make changes here anymore. But I'm also referencing that quarter three reforecast, which right now is completely in sync with that original forecast, which I'll prove out by re fetching back that data.
But what I'm gonna be doing here today is acting like I'm one of these department heads, and I'm gonna start plugging in some adjustments to that quarterly reforecast.
And where I'm gonna make these inputs here is from this input tab. And what we hear a lot from our customers that used to be really difficult to manage in static spreadsheets when it comes to running their planning cycles, regardless of whatever industry they're in, is first just getting their data prepared and ready to kick off that cycle. And secondly, it can also be very tedious to collect inputs from different stakeholders and budget owners when you're running different what if scenarios. And Qube is really gonna be built to really automate both of those functions.
Firstly, we're gonna really help with that preparation of your data whether you're bringing in historical actuals or another version of your data into your templates for planning purposes because we're connecting those templates to the cloud here via the sidebar.
So I've loaded in my history for last year and the first part of this year, and I'm no longer using rigid spreadsheet formulas to pull this data together, which means as a budget owner, I can easily pivot on this data however I need to to kick off my planning process. We're looking at the marketing team right now, but maybe I'm the head of sales and I wanna see my data today. So I'll go ahead and pick my department from that selector, re fetch that data, and kube is now gonna do all the work for me of pinging that database and refreshing this information accordingly.
So that saved me a ton of time on the front end of my planning cycle, but Qube is also gonna be here to help collect any inputs that I make from this model as well. So maybe I'm working in the marketing team and I'm planning on renting my team a new office this year and I wanna add some additional rent expense to my reforecast.
I can go ahead and plug in any adjustments that I need to here. Maybe our rent is starting this month, going out to the end of the year. So we're gonna carry that across. And now instead of having to email this template to Alyssa and have her manually input her models and update her reports, I can let Qube do all of that work for me when I use this publish data feature that's built into the sidebar.
I can even add memos to indicate what that expense is for. We'll call this new office for marketing. And once I click publish data, Qb is gonna read everything that changed in this model and compare it against what was originally in that quarterly reforecast, and it's gonna store those changes in the cloud. So now from any other spreadsheet, whether it's this same workbook or a workbook saved on Alyssa's desktop, we could pull together any type of variance analysis report that we want.
And without having to use spreadsheet formulas, we can simply fetch back this data and immediately view the impact of that added rent expense. So we have a thirty thousand dollar difference between these scenarios on the marketing department's line.
Now for those of you that prefer to work in Google Sheets, these same activities can be applied there as well. So I could have a budget input template here set up in the same kind of format. Maybe in this case, we're pointed at the sales department. We're planning on maybe doing some more enablement of our sales reps this year.
So we're gonna add some expenses to this training line. Maybe we're starting this enablement exercise in August. We've got maybe eleven hundred dollars worth of training, and we're gonna carry that through for a few months of the year. And the same way that I did in Excel, we're gonna go ahead and publish that data from Google Sheets.
So this is, again, feeding this data back to that cloud hosted database.
So I can now pivot either into a report within this g sheets model or I could also go back into Excel here. And as soon as that data has gotten fed back into cube, I could flip over into that sales department here from this spreadsheet.
I can fetch this data, and we're gonna be able to see that eleven hundred dollars populated on that training department's line just as it appeared in that GSheets model. And And we can also report on this at a more holistic level at that department variances report as well as soon as we click fetch data.
So, again, the idea here is that you can work wherever you're currently comfortable in whatever models you might have set up today for your planning purposes. Qube is not gonna require you to rip apart those models, rebuild them into any rigid syntax, structure, or web format. We're gonna embrace what you have already, which is really what makes our implementation so much speedier, faster, easier, and really allowing you to kind of get more up and running much more quickly.
But these were just examples that were kind of more generic just to give you a high level overview of how Qube handles planning. What I'm gonna pivot into here next is more health care and biotech specific examples that will hopefully kind of reflect what you might be currently doing today in your businesses.
So I'm gonna first open up this health care specific model here and we're gonna pivot into that cube, so we're gonna go to that Healthy Living Co. And this organization here is, again, that same organization that I walked through in the back end of cube where they have multiple different metrics, KPIs that they're planning for across their various clinics.
So this model is set up to allow us to plan across all those different subregions either on a KPI level. We We can also plan by more holistic metrics here. So we can just pick a metric that we're planning for and plan at every single location that we have in the company. But in this case today, maybe I'm gonna be doing some planning in my Orlando clinic. And we're gonna be planning in this budget version two. What I'm gonna do here first is retrieve whatever data is housed in that version and in that subregion.
And maybe today, what we're planning for is, increasing the maximum number of appointments that our different practitioners can take throughout the year. We had thirty four available appointments in the first half of the year, but now that it's July, maybe we wanna start ramping up that productivity. So what we're gonna do is bump this up to forty appointments, and we're gonna take that across our spreadsheet here. And since Qube has a lot of these metrics kind of built into underlying formulas and calculations in that web portal, we can now go ahead and publish that data back to the cloud, and that change is gonna be reflected across any other metric that was implicated by adding more appointments throughout the year.
So now I can pull together a variance report like I have set up here where I'm tracking the differences between my budget v two and an original budget in different accounts such as my contribution profit, gross profit, and gross revenue. So once I fetch back my data, we're gonna see that by adding those additional appointments in that location for Houston, we're gonna be able to generate an additional about a hundred and fifty four thousand dollars in contribution profit, which is being driven by an added three hundred and sixty thousand dollars or so of revenue.
So we can easily make inputs from a spreadsheet according to whatever metrics we might have set up today. We could also do this at a different level as well. So maybe we're planning for the different machines that we're operating in these different locations.
We have the number of MRI machines available, utilization assumptions, scans per day, maybe what the revenue is gonna look like per scan. And maybe in this Orlando region, we are expecting to need to hire a new MRI technician because we're gonna be taking more appointments. So what I'm gonna do here is starting in that same month, July, I could increase that to three here and bring that through across my spreadsheet. Go ahead and publish that data. And since we're now hiring a new employee, maybe we're now gonna see some increased expenses because this person comes at a pretty high salary. We can go to our variance report here and we're now gonna see that on that Orlando location, we're gonna have increased expenses here that are gonna be really driving a change in that contribution profit and that gross profit as well.
And, again, we can also do this in a different way too. Really, any kind of format that you're planning in, whether it's region by region, KPI by KPI. We can set up these templates for you or allow you to work with your existing models and automate that process of collecting those inputs that different team members are making.
Now to dive into a more kind of biotech specific model, I'm gonna open up another template here that's associated with that pharmaceuticals company that I was walking through earlier.
And this model here is a little bit more complex than that health care model that I was showing earlier. In this model, we have a lot of different drivers that we're feeding into kind of a calculated model that we have set up for our forecast and our different plans.
So this first tab that I'm on is my drivers tab where I can plan for various forecast assumptions for the different products and pharmaceuticals that I'm producing.
I have these multiple different products, alpha, beta, gamma, eta here that are in different stages of production. Some of them are ready to be launched to our general customer base, but others are more in that kind of preclinical study and trial phases.
We can plan around the probability of moving to future phases here with these assumptions. So maybe in this gamma product, we're expecting the probability of this product moving to stage five to maybe decrease a little bit down to only seventy percent. We can make that input there. We can change anything for our other products here or change other metrics here like the duration of remaining in certain stages.
Maybe for our ADA product, we're expecting it to be in that stage four for more than ten months. Maybe we're expecting twelve months here before it can roll into stage five. So we're gonna have more expenses kinda generated in that stage four because of it residing in that stage a bit longer. We can also plan for kind of the royalty rate expected from producing these different products. We've got this set to fifteen percent for all of our product lines, even changing the price per product. Maybe for our alpha product, we did some market research and realized that we might need to bump up this price a bit. So we'll bring this up to sixty two dollars instead.
And once we're making all of these changes here, whether it's changes to those high level assumptions or changes to the research costs expected in each of these stages, we're gonna be able to go over to this forecast calculations tab and see how this starts to flow into our model. So our model here is gonna be be tied back to Qube. We can go ahead and pick that ABC pharma company here from that drop down and go ahead and publish all of those changes back into the cloud. So Qub is reading all of those inputs at that product level, at all of those different KPIs.
It's housing those changes to those metrics in the cloud. The same way that I showed in that more financial model and that health care specific model, all of that information is being populated here behind the scenes so that now when we pull together a variance analysis report where we're tracking our forecast against a reforecast, we can fetch back that data and see that as a result of all those changes that we've made, we're gonna have an additional forty two thousand dollars worth of royalty income.
We can also pivot to other years as well if we wanna go back to twenty twenty four and see how the changes to different stages have impacted that, we can also reflect that maybe we didn't see any variances yet. But as soon as we start launching those products, we're gonna have increased revenue because we increased that price for that one product line.
And we can also easily pull together monthly reports, product level views of this. We have this report that tracks all of our KPIs, financial accounts down the rows. All of our time here is across the columns so we can fetch our data and view any changes reflected here for those reforecasting periods. We can also retrieve this data just for one drug at a time. If we just wanna track the ADA drug, we can fetch that and see how this changes all of this information here. We can additionally pull together products level views of this where we're tracking KPIs by products by those reforecasting periods as well.
Now so far, I've really been leveraging spreadsheet driven kind of classic financial and operational models here just kind of displaying values.
But, of course, there's always gonna be a need to share out visualizations, board deck files to different end recipients for them to more easily digest that data. So for any of this data here within this company, I can pull together nice visualizations to track kind of trends in my revenue or trends in my total expenses, tracking something like EBITDA or even product demand here. And all of these charts that you see here are driven off of a data table down below that's connected back to Qb via that sidebar.
So since we're no longer relying on Excel formulas to link up all of this data, running static data dumps from our different source systems, we can easily refresh this data however we need to on the fly. I could pivot for just one specific drug line like the alpha drug, fetch back that data, and and we're gonna see these charts update accordingly. I could filter by different time periods if I want to. So I could go back a month if I needed to, and we're gonna see that product demand update as well if we've had any changes happen there. But what's also great is that aside from just leveraging the flexibility of a spreadsheet to generate your different dashboards, we also have systematic dashboards that are available on the web facing side of Qube.
So these dashboards are gonna be available to any end user who has access to q. This will give them the flexibility to log in to q. They'll be able to view all the relevant kind of slicers and pivots of your data. I have different revenue breakdowns here to track things like revenue by my markets, product budget to actuals comparisons, different quarterly trends. I also have some operating expense KPIs and some core financials.
And all of my different end users of Q can hover over these various dashboards to get quick insights about that data. They could even investigate that data a bit further using a drill down functionality, and they can also apply filters across the top to easily pivot on something like maybe a subsidiary entity. Maybe they're pivoting on a specific product line or a specific region or clinic in your case here. But, again, any of those dimensions that you have kind of stubbed out behind the scenes in Qube are gonna be displayed here and give you that ability to filter by just like you came from that spreadsheet environment.
Awesome.
And these were just a few examples here. But, again, the idea behind Qube is that this is all going to be customized around your business. So, really, however you're currently planning for, whether it's pharmaceutical production or whether it's expenses per clinic, we're gonna be able to adopt and embrace your existing models instead of requiring you to rip them apart completely and spend months training up into the system and getting that implemented.
And once we do have all of your kind of models cubified, built out, you've invited different end users to your queue, there's lots of ways that they can start interacting with those models here. Since we're utilizing a spreadsheet interface, we can upload any of those spreadsheet templates to cubes library to give really quick access to different end users.
So every month or every quarter, maybe I'm updating my budgeting input template for my different budget owners and department heads, And I can upload this here to cubes library for different users to download, and each user who has access to cubes is gonna have specific security assigned to them so that when they're downloading this report and fetching back their data, they're only gonna see data relevant to either their department, their entity, or their sector of the business.
And the way this all gets kind of assigned and set up is gonna be via this team's function here that we have on the left hand sidebar. So I'm an admin level user. I can add any user to my cube or modify their existing access. So if I'm adding Alyssa to my cube as a new budget owner, I'll click that new button.
I'm gonna add Alyssa's email here, assign her to a permission group. I want Alyssa to have ownership over her budget, so I'm gonna allow her to modify data in cube. But maybe I don't want Alyssa to have access to certain sensitive data points. Maybe I don't want her to be able to investigate the underlying, employees that are rolling into these salary expenses in these different KPIs.
So I'm gonna lock her out of these accounts so she doesn't have access to that data. And maybe I'm also gonna make sure that Alyssa can only modify the plan for her department marketing. If she tries to write back into any of these other teams here, she'll receive an error in the cube sidebar that says she doesn't have access to make those types of changes.
So, again, the idea here is that we're designing a cube not just for the finance or, but we're also building a cube that can handle planning, reporting, forecasting for any other department. But we have all of this underlying security and robustness behind the scenes here really built out to make that a much more secure lockdown process for the different end users and to ensure that, you know, people aren't working where they shouldn't be.
But I hope that this is a good overview of cubes specifically kinda tailored to the more health care biotech industries.
I'm going to stop sharing my screen here at this point, and I think we can start to take some questions here that anyone had throughout this demonstration.
Awesome. Thank you so much, Taylor. We do have a few questions here that we can get to.
So one of the first ones is, can you limit access to users to certain departments like sales?
Yep. Guessing that might have been asked before I showed that security piece, but, absolutely, you can lock different users out of writing back to certain departments, even reading data from other departments. And that security can be applied to any of your dimensions as well. So if there's a product line that you don't want people to view data for, for example, that security can also apply there.
Awesome.
Can Qube help me plan for fluctuations in clinical trial expenses?
Absolutely. Absolutely. Yeah. That's definitely a a common topic in the biotech space. So any existing models that you have set up today for planning for clinical trials, we can connect into and let you publish from those models. You can keep all of that kind of underlying logic that you have residing in those templates, and Qube will pick up any outputs that are resulting from changes. And that's gonna give you that easy ability to run what if scenarios, different version comparisons to track those impacts of either, you know, planning for increased expenses or even, you know, revenue planning with those products as well.
Awesome. Couple more. Is it typical to work with a consultant to onboard Qube?
Yeah. So that's the big differentiator with Cube and a lot of other kind of FP and A tools that I've worked with in the past. Cube really is built by design to be a more customer owned platform that doesn't really require consultant involvement and support.
You will be working with a customer success manager once our implementation team sets up your cube, gets all of your data loaded into the cloud. But that customer success manager is an in house cube employee.
They are not working on hourly consulting fees like you might expect in some of those other tools. They're really meant to be a go to resource for you to leverage to become a better kind of power user of Qube and to help you answer any questions throughout if there's changes to your business and to your models that you might need help with kind of Qubifying and getting up and running.
Awesome. And then the last question we have here is how can I use Qube to plan for CapEx when we purchase new equipment and facilities?
Yeah. That's a great question. So if you have models set up for CapEx planning, maybe you're tracking, you know, categories of different items that you're purchasing and you have a depreciation schedule built in there, we can cubify that template, and you can start publishing from that template, planning for maybe changes in when you're purchasing a certain item. You can see that reflected on something like your balance sheet or your cash flow statement.
Or we also do have models available that you can download and kind of leverage as a starting point for those types of activities if you don't have something like that built out already. And that's, again, something that that customer support manager is gonna be really great at kind of helping facilitate for you too, you know, getting you started off on the right right foot with either cubifying your models or working with you to leverage our templates.
Awesome. Well said. Thank you so much, Taylor. This has been great.
Before we let you go, I just want to quickly go over some resources like we mentioned earlier.
I will share my screen.
So if you liked what you saw today, but you still have some more questions and you wanna go a little bit more in-depth, you can request a custom cube demo, and we will schedule some time with you and make sure that you get all of your questions answered. So you can feel free to click that button there.
Next, if you're interested in receiving finance tips, tricks, advice from different finance professionals and leaders throughout the industry, you can subscribe to our biweekly newsletter, the finance fix. It is written by our CEO and founder, Christina Ross, who all also happens to be a three time former CFO. So she's been there, done that, knows her stuff, and she has a lot of great advice packed in here. So definitely recommend checking that out. And then finally, we have our strategic finance pros Slack community.
This is made up of a bunch of like minded finance professionals like yourself who have gone through likely a lot of the same trials and tribulations that you have gone through. People are always willing to offer advice, and there are also a lot of different webinars and content pieces that we like to submit in there, to provide for you that are especially made for community members. So that's a great place, if you're looking for additional info and to connect with people like yourself.
So highly recommend checking all of those things out.
And with that, thank you everyone so much for attending. I hope you have a great weekend, and thank you, Taylor.
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