Data analytics: From studying the past to forecasting the future
To compete in today's competitive market place, it is critical that executives have access to an accurate and holistic view of their business. The key element to sifting through a massive amount of data to gain this level of transparency is a robust analytics solution. As technology is constantly evolving, so too are data analytics solutions.
In this blog, three types of data analytics and the emerging role of artificial intelligence (AI) in processing the data are discussed:
As the name suggests, descriptive analytics describe what happened in the past. This is accomplished by taking raw historical, whether from five minutes or five years ago, and presenting an easy-to-understand, accurate view of past patterns or behaviors. By understanding what happened, we can better understand how it might influence the future. Many businesses use descriptive analytics to understand customer buying patterns, sales year-over-year, historical cost-to-serve, supply chain patterns, financials, and much more.
This is the ability to accurately forecast or predict what could happen moving forward. Understanding the likelihood of future outcomes enables the company to better prepare based on probabilities. This is accomplished by taking the historical data from your various silos such as CRM, ERP, and POS, and combining it into one single version of the truth. This enables users to identify trends in sales, forecast demands on the supply chain, purchasing and inventory level based on a number of variables.
This solution is the newest evolution in data analytics. It takes previous iterations to the next level by revealing possible outcomes and prescribing courses of actions. In addition, this solution will also show why it will happen. Prescriptive analytics answers the question: What should we do? Although this is a relatively new form of analytics, larger retail companies are successfully using it to optimize customer experience, production, purchasing and inventory in the supply chain to make sure the right products are being delivered at the right time. In the stock market, prescriptive analytics can recommend where to buy or sell to optimize your profit.
All three categories of analytics work together to provide the guidance and intelligence to optimize business performance.
Where AI fits in
As technology continues to advance, AI will become a game-changer by making analytics substantially more powerful. A decade ago, analytics solutions only provided descriptive analytics. As the amount of data generated increased, solutions started to develop predictive analytics. As AI evolves, data analytics solutions are also changing and becoming more sophisticated. BI software vendors are currently posturing to be the first to market with an AI offering to enhance prescriptive analytics.
AI can help sales-based organizations by providing specific recommendations that sales representatives can act on immediately. Insight into customer buying patterns will allow prescriptive analytics to suggest products to bundle which ultimately leads to an increase in the size of an order, reduce delivery costs and number of invoices.
Predictive ordering has enabled companies to send products you need before you order them. For example, some toothbrush or razor companies will send replacement heads in this way. They predict when the heads will begin to fail and order the replacement for you.
Improving data analytics for your business
If you are considering enhancing your data analytics capability and adding artificial intelligence, we encourage you to seek out a software vendor that offers you industry-matched data analytics that is easy and intuitive for everyone to use. This means dashboards, scorecards, alerts developed with the standard KPIs for your industry, pre-built.
Collaborating to customize the software to fit your business and augmenting with newer predictive analytics and machine learning-based AI happens next.
Source: Phocas Software