Financial analysis as the basis for long-term forecasts for a market leader on the real estate development market
One of the largest residential developer in Poland, a company operating on the market for over 20 years and listed on the Warsaw Stock Exchange, it is constantly developing and taking over new entities. At some point, the consolidation of data on subsequent investments and the financial analysis based on them became a priority. It was the only way to responsibly plan the next business moves. Incube CPM with which cooperating with client for over 10 years, has started to modify the existing system to meet the client's new challenges.
IBM Planning Analytics (TM1) is a tailor-made solution
It is our regular client. We are currently working on the third model of the solution created 12 years ago. The last implementation took place 8 years ago. Among other things, the real estate market situation and the company's structure have changed during this time. Both of these factors forced the changes that the company is now benefiting from.
As a base, we consider a data warehouse that contains information on the number of: apartments, garages, stores, storage units - along with key descriptive information including, among other things, dates of sales and bookings. Such an Investment Base is used for further analysis. The current model created in IBM Planning Analytics has three input points from which external data flows in. The first is information on costs, both those incurred and those planned for the entire investment. The second is revenue. Those of performance, i.e. payments from customers, and future ones, depending on the selected schedule. The third point is investment information. So we have all the data: how many apartments there are, what size they are, what standard they are, how many garages there are, what type, how many storage units there are, whether there are stores, what their prices are, prices per meter, sales value, booking dates, sale dates, handover dates, etc. An important difference between this model and the previous one is that we get more information from outside, and the data is more integrated. As a result, employees can efficiently navigate the analytical model created in TM1 within the limits of their assigned rights.
As a base, we consider a data warehouse that contains information on the number of: apartments, garages, stores, storage units - along with key descriptive information including, among other things, dates of sales and bookings. Such an Investment Base is used for further analysis. The current model created in IBM Planning Analytics has three input points from which external data flows in. The first is information on costs, both those incurred and those planned for the entire investment. The second is revenue. Those of performance, i.e. payments from customers, and future ones, depending on the selected schedule. The third point is investment information. So we have all the data: how many apartments there are, what size they are, what standard they are, how many garages there are, what type, how many storage units there are, whether there are stores, what their prices are, prices per meter, sales value, booking dates, sale dates, handover dates, etc. An important difference between this model and the previous one is that we get more information from outside, and the data is more integrated. As a result, employees can efficiently navigate the analytical model created in TM1 within the limits of their assigned rights.
Sound financial analysis requires homogeneous data
The most important aspect of the modification is the collection of data from all companies in one place, which enabled faster and more accurate analysis and online access to the data by the company's headquarters.
As Ewa Kaczmarczyk, Team Leader at Incube CPM, who is leading the project, explains, we aimed to make the data verifiable and controllable on an ongoing basis. And it worked.
– We have all the sales information. We get information from wholesalers on how many apartments have been sold and we calculate the average price per square meter, discounts and other information that must be reported to managers or owners. Then, from this information, the system creates overheads, company-wide costs on investments, fed from the data warehouse. And then generate from them per company: financial reports like cashflow, balance sheet, income statement, which will be accessed immediately, the expert enumerates.
As Ewa Kaczmarczyk, Team Leader at Incube CPM, who is leading the project, explains, we aimed to make the data verifiable and controllable on an ongoing basis. And it worked.
– We have all the sales information. We get information from wholesalers on how many apartments have been sold and we calculate the average price per square meter, discounts and other information that must be reported to managers or owners. Then, from this information, the system creates overheads, company-wide costs on investments, fed from the data warehouse. And then generate from them per company: financial reports like cashflow, balance sheet, income statement, which will be accessed immediately, the expert enumerates.
Real estate is a long-term business
Buying a plot of land, designing investments, selling apartments - these are activities that take years. A lot of time passes from the idea to the finalization, which is why the analysis and planning department is strategic for the client and should be supported with appropriate systems. The tool implemented by Incube CPM in the form of IBM Planning Analytics develops data that is used to make forecasts and plans for the coming years. Based on the schedule of inflows, it is known what the investment income will be, how much should be spent on costs, and on this basis the forms of financing the company's activities are determined.