Story Homes case study

Story Homes drives profitable business growth by connecting operations with finance on the Anaplan platform

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Twenty-five years of building experience has made the Story Homes name synonymous with superb design, beautiful properties, and livable locations throughout Cumbria, the North East, Lancashire and Southern Scotland. Today, the business is driving a 60 percent year-on-year increase in the number of homes built. To accommodate this growth, Story Homes required a rapid deployment and flexible solution that could match the fast rate of business change whilst collating vast quantities of data. Their chief objective was to deliver rapid, accurate, and interactive data analytics so that executives could drill down on cost allocations to reveal which house types and sites were operating profitably.

“We’ve become aware of what makes us money and what doesn’t make us money. Where we’re efficient and where we’re not efficient.”

John Story Story Homes


In 2011, when Story Homes went in search of a loan to fund a new growth strategy, the bank asked them to produce a cash flow forecast going out three years. John Story (whose father founded the company) was brought on board to create the projection. To do so required him to sift painstakingly through the cash flows of thirty different build sites. The resulting forecast provided the necessary information, but it couldn’t be updated without significant additional input. Instead of repeating the effort, the company’s new Finance Director suggested John take a closer look at a cloud-based platform called Anaplan that had just been implemented at his previous employer, the market leader Taylor Wimpey.


When John first joined the business, there had never been a three-year cash forecast. “There was a lack of discipline,” said John. “Information was coming out in different formats.” Even simple conversations around start dates began to unravel when John realized that one site defined a start date as digging a hole, another as selling a house, and a third as finishing a plan.” It was an immediate need to put an end to these diverse modeling processes by bringing the company’s data into one place. They also hoped to improve upon Excel’s limited ability to handle scale, multiple versions, and basic collaboration.

Selection Process

Story Homes approached Anaplan with a model that was giving their sister organization, Story Contracting, some trouble. The model was meant to allocate fuel and maintenance charges across customers for a network of one hundred vans, but there was so much data it took their servers a week to produce a single report.

Anaplan’s proof of concept ran reports off the 10GB model instantly. “From one week in Excel to a few seconds,” said John. “That was impressive.” But it wasn’t just processing power that grabbed his attention: “In Anaplan, when someone does a CPI (Consumer Products Index) report to evaluate spend costs on a site, that report can also be used on a forecast or in a site evaluation.” The platform not only reduced the duplication of data, it ensured everyone was working with the same reference points. “I could see that in Anaplan, it’s all connected,” said John.


Working with two other team members, John had created a ready-to-go model by early December 2012—just three months after contacting Anaplan. Compared to his previous experiences with other systems, John was impressed that “there were no limitations with Anaplan – you worked out the solution, what information you wanted out of it, and started writing. It was very fulfilling.”


“We now collect a lot more information, and we’re much more aware of what makes us money and what doesn’t make us money, where we’re efficient and where we’re not efficient,” said John. “We’ve put the proper systems in place.” Those systems have driven a new discipline about how people produce numbers or refer to items at Story Homes. Now, when a user talks about a sales rate, it has a commonly understood definition across all reports.

In addition to purified data, Anaplan has enabled significant increases in levels of detail as well. Forecasts are generated from the plot level up, helping to produce accurate regional and national sales predictions to an extremely granular level. This has in turn enabled the team to ask better questions up and down the chain of command. At the weekly operational meeting, figures are practical; bills and sales interests are discussed. At the monthly financial summary meeting, managers drill down on exceptions in costs and revenues. At the strategic quarterly meeting, always up-to-date reports enable the board to make informed land asset management decisions and improve the selection of sites.

“It’s helped to distill away the noise,” said John. “We’re getting live updates at levels of detail that just weren’t possible before. Now we can talk about what’s holding us back and what we need to do to make our strategy happen.” With Anaplan, Story Homes has also extended its ability to plan for the future. The long-range land assets forecast has increased from one to fifteen years.

Going Forward

Story Homes is now focused on expanding Anaplan down to the operational level. “By the end of this financial year a lot of operations will have their own reports,” said John. He will also use Anaplan to continue the refinement of data collection processes internally.

The Anaplan platform has given Story Homes an interactive platform that connects everybody into a single process, delivering dynamic reports across the enterprise to ensure the success of the company’s growth plan. Before Anaplan, those processes were trapped in siloed spreadsheets throughout the business. Now, with everyone on the same page, Story Homes is driving productivity and operational performance while eliminating inefficiencies that have dogged them for years.

Use Cases
  • Financial Planning
  • Operational Planning
  • Inability to deliver data analytics to match the fast rate of business change
  • Existing servers could not handle vast quantities of data
  • Unable to collate data feeds from disparate systems
  • Non-standardized modeling practices across thirty different build sites
  • Replaced spreadsheets with a single data model on Anaplan
  • Wide range of new reporting capabilities for weekly financial, monthly operational, and quarterly strategic level meetings
Results at a Glance
  • Single, always up-to-date data source enables accurate regional and national sales predictions
  • Team trained in three days and self-sufficient in building plans and models in three weeks. Single data model for entire organization implemented in three months
  • Real-time reports at the required level of granularity drives strategic planning
  • Long-range forecast extended from one to fifteen years to enable strategic land asset management
  • Cloud-based process connects Operations and Finance teams for higher levels of accuracy, collaboration, and productivity
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