What-If analysis can also be referred to as sensitivity analysis, which is a self-explanatory technique to assess the outcome of a process when parameters are altered. Naturally, what-if analysis find its application in scientific research and business & financial risk assessments. The end objective of a what-if analysis is to make an informed scrap-it or let’s-roll-with-it decision.
In business, what-if analysis is used to determine things like
- How sensitive a forecast might be to changes? What would be your cash situation if sales were to fall by 13%?
- What if your supplier increases raw material costs by 5%?
- What would be the impact of your razor thin margins on profitability if international crude prices go up by 2%?
What-if analysis can be done as often as possible to keep your business in the best possible position vis-à-vis the competition.
What-If analysis is particularly handy when you want to go beyond the scope of standard BI reports. Think of it as a way of validating your gut feeling. As a business leader you have been in the business long enough to know how it ticks and you obviously have intuitive tendencies, it’s best to support them through a scientific approach.
Business analysts routinely use MS Excel for what-if analysis as it is provisioned with tools like Scenarios, Goal Seek and Data Tables. That being said, for a company gearing itself for a data driven work culture, Excel is less than ideal. This is primarily because it requires a high level of proficiency in using Excel.
Secondly, Excel’s what-if capabilities are redundant in a database environment, much less in a non-relational big data environment which is much more feature rich and incredibly complex. The biggest argument against MS Excel is that it is against democratisation of data. This is because not every business user can be expected to be exceedingly proficient in Excel to wrangle with raw data gathered from each source. Plus, using Excel is counterintuitive to daily decision making needs of business users.
The answer to your data wrangling woes is a self-service BI tool like DataScout which effortlessly prepares all your data. DataScout tackles the issue of data wrangling through automation, intelligent algorithms skim raw data to keep everything clean and organized.
DataScout is a cutting-edge tool that enables you to see beyond what’s visible on the surface. It’s important to take cognizance of this as most use cases in the business world are stacked like a pyramid where –
- High net worth cases are on the top. The ROI for them is well defined with Inventory, Cash Situation, Orders, Line Items and so on being the usual suspects for channelling investments.
- Middle of the pyramid businesses struggle with accurate ROI visibility. It can make a lot of difference to how they spend money if they can clearly see where their money is going.
- Ground breaking fortunes of most companies lie just below the top and further down the pyramid.
DataScout provides a refreshing way of conducting what-if analysis. You know your business, you have the context, just point & click the sources you want and start tinkering with key figures. Want to know how much more sales traction you can get if you increase your advertising budget? Just increase the budget and DataScout will reveal cascading figures based on your historic performance. Want to know the impact on sales if you had fewer sales reps but gave more incentives? No problem, DataScout has got you covered.
DataScout is an advanced analytical tool that goes beyond the scope of a self-service business intelligence tool. You and your analysts will never have to go looking for the best what-if analysis techniques, DataScout makes it easy for you.