Power of Forecasting

  • January 22, 2022
  • Blog

Business is a highly risky ball game altogether. Additionally, when you have multiple stakeholders pumping in money worth billions, and reposing trust that is priceless, you know that you can hardly afford to make blunders in your judgements and operations. Hence, operating a business needs an acute sense of discernment, fortitude that can see any hindrance that may come one’s way eye-to-eye and the flexibility to adapt oneself to withstand the challenges and get molded.
One of the biggest obstructions that the modern day business, especially the supply chain domain is facing is that of unpredictability. COVID-19 has unearthed all the loopholes that existed in the domain’s fabrics and have shown how the very backbone of the world economy can receive brickbats if the said industry does not brace itself for the worst to hit. We all have seen how the world came to a standstill; we all have witnessed how the financial and social trends across the world underwent a sea-change; we all have experienced how the world became a different place in terms of how we dealt with things. The pandemic has put the consumers at the center of the entirety of the operations and every single step that is taken, veers towards making a happy base of customers. There are empowered consumers who have the whole world at the tip of their fingers, there are goods that are worth a fortune, there are stakeholders who have realized the importance of interdependence in a very pragmatic way. And the bottomline reads, ‘You cannot go wrong’.
Therefore, it is time to make use of the technical and the scientific know-how that have been overlooked for the longest of time. Leveraging infallible data and the ensuing analytical trends is no longer a matter of the distant past. It is here to stay and it is going to be the pivot of change for the decades to come. Describing data, predicting what may come and prescribing corrective measures have become indispensable aspects of running a business successfully. And when it comes to a domain that sits atop a perilous sea as the logistics industry, data analytics seems to be the only way out to gauge the circumstances and to be more agile.
Data analysis renders greatest of help in taking key decisions which are based on facts and trends. It helps in closely monitoring the socio-economic paradigms and its shift through indicators that have been proven to yield accuracy. Businesses must have a few solid key performance indicators (KPIs) that act as their short and long term objective and utilize data analysis to align themselves to those goals. In the context of the supply chain domain they are mainly getting hold of the impacts of disruptions, wriggling out of their negative effects and making a more resilient value chain.
The fundamentals of data analysis lie in data. Data is the new gold. Data is everywhere. The competence of an organization or an individual rests on their ability to procure, track and document data as efficiently as possible. In this modern data-driven world, it may come from any horizon; be it through the surveys and the observations made by private/public agencies or through the real-time trends that are collected over time with the help of ultra-modern gadgets. In this huge vortex of data, it is the company’s job to seath the cream out of the milk and strike a balance between all that has come across intersections to strengthen the prospects of better outcomes.
Benefits that May be Yielded
The whole discussion of this article points towards the fact that data analysis and predictive analysis in particular can result in massive yields for the supply chain industry. Let us sum these up through some of the points that are listed below:

  1. As it has been mentioned, customer satisfaction is the end goal of any business. Thus, data analysis helps businesses cater to the changing patterns of customer demands.
  2. It helps manage landed costs especially in a scenario when the latter may get volatile enough to spiral up and down.
  3. It helps in striking balance between trade-offs
  4. Makes the process of converting inventory into revenue faster.
  5. Optimizes all the cogs of the supply wheel, right from the planning to the execution.
  6. Helps in avoiding disruptive situations such as stockout, delays and excessive inventory.
  7. Companies get to know of the effects that ensue due to capacity crunch and work towards mitigating them.
  8. In the process of optimizing the entire value chain, data analysis brings all the stakeholders closer.

Steps in Implementing Successful Data Analysis into Company System

  1.  Collection of Data: The very first steps in forecasting and meting out prescriptive measures are the collection of data and setting achievable KPIs. Companies must work upon the points of measurement that need to be calibrated so that at a regular interval of time these points can be reviewed and assessed. In this process, companies must get themselves attuned with its stakeholders as well so that actionable data can be gleaned from any source and error-free decisions are made in favor of all.
  2. Experiment, Prioritize, Set Alternatives: A successful data analyst has various financial models in his/her grip. He/she experiments with them by experimenting the data and coming up with various solutions and perspectives to look at the same problems. Alternatives are set, partners are brought into confidence and the best route to cut down on the problem is sought.
  3. Finetune: The final and probably the most important step is probably observing, analyzing, adjusting before coming to a conclusive idea. The insights that turn into data need to be reviewed, revised, refined and remodeled before they are brought decisively on the table. And this task of reviewing must be done as a team, in its entirety.

This brief discussion highlights the invaluable and indelible impact data analysis has left on the supply chain verticals. In order to let the supply chain flourish and stand resilient against the disruptions, we need a powerful tool that can accurately forecast trends and provide corrective steps. Data analytics seems to have reached that pedestal and it is going to remain so for years to come It is becoming of the companies and the industries alike that they cope up with the changing demands and embrace this innovation for betterment of their operations, for achieving customer satisfaction and for making the cash cycle agile.