With Connecticut facing a growing state budget deficit, many residents and business owners are uneasy about what’s to come in terms of taxes, spending and the overall economic strength of the state. Addressing these concerns, Governor Daniel Malloy noted in his State of the State address on January 4, 2017, how the government should try to ease this uncertainty.
“Predictability allows businesses to expand, to make new hires, to put down new roots right here in Connecticut,” he said, as quoted by the Connecticut Business & Industry Association (CBIA).
“This is what companies and their workers are looking for. They deserve it, and it’s on us to provide it.”
The governor’s comments were welcomed by CBIA President and CEO Joe Brennan, who noted that “Predictability is key to economic success for both employers and individuals.”
While the state figures out how they will balance taxes and expenditures, businesses can create more predictability internally by using analytics to gain more certainty on their own revenue and expenses.
Analytics for Accuracy
Accurate financial forecasting and cost control is critical to the success of all businesses. In the event that the revenue or cost side of the equation is off, then they might not reach their profitability goals. For example, a company may decide to add new products or hire more employees, thinking that these moves will be cost-effective due to an increase in revenue. Yet without strong financial analysis, these expenses could end up costing more than they result in revenue increases.
Luckily, advancements in analytics make it possible to create more accurate forecasts and adjust along the way.
For example, one forecasting firm used data from web searches to predict auto sales with increased accuracy, as Harvard Business Review (HBR) writes.
Stabilizing Costs
Not all business may be ready or have the means to create in-depth revenue forecasts using predictive analytics, but there are certain ways to stabilize the cost side of the equation without too much effort.
For example, as HBR notes, “Executives in asset-intensive industries often state that the primary operational risk to their businesses is unexpected failures of their assets.” So, to reduce this risk, businesses can use Internet of Things devices that provide data on how these assets are performing. With this real-time information, businesses can get a better sense of when machines are likely to fail, thereby lessening the unpredictability of asset maintenance.
Even without adding smart devices that predict maintenance issues, businesses can use energy analytics software (EAS), to determine how different machines consume energy. If the energy diagnostics show that a piece of equipment is using an unordinary amount of energy, it could be a warning sign that the machine is starting to fail.
Plus, businesses can use EAS to set energy budgets to help them save energy, rather than dealing with the uncertainty of not knowing their costs until utilities send monthly bills. With the budget set and the data available to better determine energy costs, companies can take steps to stay on track, such as syncing their EAS with a building automation system to curtail energy usage during periods of increased cost.
These steps can help businesses get a better handle on what previously might have seemed out of their control. While analytics can’t lower taxes, they could be used to forecast how different tax rates would affect profitability. At the very least, CT businesses can add more predictability to the processes that are directly in their control, which could help offset the political situation that is more of a question mark.
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