|
|
|
|
Basics
 |
Industry:
IT
|
 |
Location:
Turkey
|
This large IT company’s strategy included investing in many new projects each year. To support this strategy, they needed improved efficiency and improved quality in financial modeling. Better models would make for better decisions. However, a legacy of bad models was tangled up in the silos of the business, with little consistency, uncertain accuracy and diminishing confidence in the financial models produced. Moshe was engaged to help create an optimal financial modeling process across the business.
The Challenge
|
|
No consistent, coherent approach for projecting financials
|
|
|
At best, models were extremely complicated. At worse, unusable as they were overly simplistic to the point of meaningless
|
|
|
|
|
Models not designed from onset to drive decision-making, with little regard to how they would be used
|
|
|
Models couldn't adapt to changes in fast-changing environment
|
|
|
|
Staff doing the modeling lacked the right skills or the right perspective
|
|
|
|
|
Either people were very technical (number-crunchers) or too superficial
|
|
|
No one was focused on the process; attention was lax
|
|
|
|
Lack of a single process driver led to mistakes and project failures
|
Giving the right people, the right tools, to do it right
As is often the case, the company had well-meaning staff that lacked the right tools to do financial modeling right. The characteristics of the models weren't relevant to the business needs.
The situation led to management giving the green light to projects with insufficient understanding of financial characteristics. And that situation soon became unworkable. The result: projects lost money, succumbed to risks that would have otherwise been identified. Had a more accurate picture been available, 20% of projects would never have been launched; the remaining 80% would have been better managed with a clearer picture of the risk opportunities and resources needed, resulting in fewer surprises.
How We Approached the Challenge Identify
|
|
Key drivers of business model, such as market demand and production costs, from larger range of metrics that tends to cloud thinking
|
|
|
Linkages between the variables and drivers
|
|
|
Who, what, and when of people involved, and linkages between them
|
Understand
|
|
Resource or other constraints and reflect these in the modeling
|
|
|
How financial models support strategic decision to enter into new projects
|
Apply
|
|
Dynamic modeling to reflect a range of scenarios
|
|
|
Complete competency transfer
|
Value Delivered
|
|
Customized, tailored models to meet the particular, immediate needs of the business
|
|
|
Dynamic model could change as the project progressed, circumstances changed
|
|
|
Model's staying power made it valuable management tool
|
|
|
Staff understood how to approach financial modeling from a need-based perspective
|
|
|
Managers had greater visibility to risks and challenges
|
|
|
Decision-makers had greater confidence when going to market; models gave more accurate predictions of outcomes, risks, and resources required
|
|
|
|
|
|