Fast-growing organisations can often struggle to look past the short term. With so much going on requiring their immediate attention,it’s no surprise that is the case, but this kind of approach can leave significant gaps in their future strategy.To add to this issue,many back-end financial and operational systems of businesses today aren’t designed with the scalability and flexibility needed to support sustained growth, despite the fact they are needed to drive new business and engagement models on a daily basis. As they say, it can be hard to see what’s right in front of your eyes…
Building for long-term success requires planning and perhaps a dose of patience, too. Remember,for every hour spent now preparing for growth, you could be saving 20 times that investment in future time, meaning your business will be in a far better position to respond to future changes in the market.
At Quantrix we’re regularly approached by a wide range of organisations looking for a fresh approach. Many of these organisations have found themselves stuck in some unforgiving ruts, with cumbersome spreadsheets and emails dominating their existing processes, wasting time, money and resources.Regardless of who we’re speaking to, our advice is usually the same:just start with the basics of efficient data best practices and principles.
Below we will explore what we believe fast growing businesses should be doing today to ensure their financial and operational systems are built to last.
There are many types of forecasting activities that take place in growing businesses: demand planning, sales forecasting, inventory planning, capacity planning and financial forecasting, to name just a few.
In the most successful companies, forecasting is the primary driver that guides strategic decision making. As such, it is critically important that forecast models are based on reliable data, encompass the full spectrum of likely scenarios, and are integrated with the rest of the business to show the full ‘cause and effect’ of scenario changes as they ripple through an organisation.
In recent years, the rise of the “Big-Data” era has seen the emergence of a new breed of technology companies, all vying to increase the speed and effectiveness at which we analyse trends in customer data, production data, macro-economic financial data, et al. Many of these companies will tell you that you should analyse all available data sources in order to identify trends and areas where you could gain efficiencies. But, beware! Conducting data analysis with business intelligence (BI) tools alone will do little to highlight the opportunities available for a business to capitalise on. Often, these opportunities are just around the corner, and it’s the companies with superior forecasting capabilities that will succeed in an increasingly competitive environment – not those on a data goose chase.
Remember, it’s not about having all the data. It’s about having the relevant data.
The most successful companies facilitate the bi-directional flow of information between their business intelligence (looking at historic data) and forecasting (modelling the future) functions. Beginning with robust basic forecasts to test assumptions, an opportunity is identified, forecasts are refined with the aid of historical data and trends, action is made to capitalise on the opportunity and, critically, the results of the action are fed back into the future forecasts to further refine their accuracy and effectiveness. The level of detail needed within a forecast constantly changes and is driven only by the key drivers of the business.
All too frequently though, companies don’t begin with accurate forecasts – and the effects can have far reaching consequences.
Single source of truth – forget eliminating silos – don’t let them form in the first place
A recent report found that over 95% of US firms still rely upon spreadsheets for financial and operational analysis and 90% of analysts said that the main tool they used for conducting advanced analysis was the spreadsheet.
These figures are hardly surprising, but they give a realistic picture of the world that many of us operate in: an inflexible, error-prone jungle of interlinked workbooks – and working in this way can bring a number of challenges for organisations.Insightful data is often initially created as a one-off exploratory project. But, these one-off spreadsheets frequently evolve into large team efforts.
In an increasingly global world, collaborators, often from many different departments and locations, will need to contribute, maintain, develop and update a single spreadsheet. It’s easy to see the problem here – and we’ve probably all seen, first hand, collaboration projects that end with different document versions being distributed simultaneously. This is called the ‘single source of truth’ problem.
When multiple versions need to be compared, contrasted and edited to create a true ‘master file’, the integrity of your data will always be in doubt. It’s also a very inefficient and time-consuming way to work. If your versions aren’t maintained,unnoticed and incorrect versions of the spreadsheet will be added to, circulated, and then returned – compounding any errors. If an error is ever noticed, the lack of controls makes it hard to determine when and where in the process any critical changes, or errors, occurred.
Traditional spreadsheets have attempted to address the collaboration problem, but the solution of ‘cell protection’ can make models inflexible, hard to edit, and also removes the capacity for ‘self-service modelling’, decreasing employee efficiency and productivity.
Start as you mean to go on
You’ve got the data and you know the questions you need to answer.But, how can you appropriately structure your model to be flexible and scalable, yet robust? We live in a multidimensional world, with many organisations operating across multiple regions, selling a variety of products.
Businesses aren’t static, they’re evolving entities, constantly changing the products they offer and the ways in which they sell these products. Your model needs to be flexible enough to adapt to these changes as they happen, with minimal effort. Failing to address this early on can often result in a huge amount of work to re-engineer a spreadsheet – giving yet more chance for errors to creep in.
Technology will continue to evolve at a breakneck speed – and it’s up to businesses to make sure they keep up. A paper filing system won’t be suitable to manage sensitive customer records, as Microsoft Paint is unlikely to be suitable for even the most talented graphic designer. To get ahead of competitors, businesses have to use the most relevant tools to meet their organisation’s needs. And yes, that might even mean giving up traditional spreadsheets.
It sounds simple, but using the right tools for the right job will ensure that efficiency time-drains such as formula writing, error checking and auditing are all alleviated through the use of professional features such as natural language formula writing, built-in audit trail and a visual dependency inspector. Collaborative, multi-dimensional modelling tools are leading the way in financial planning and forecasting, because when you’re spending thousands of pounds on capturing and analysing data, it’s too costly to have a spreadsheet let you down.
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