Types Of Data Analytics To Improve Decision Making
Data Analytics is a powerful tool for managers looking to track progress and to chart the predictable future.
Think about the challenges you might confront in any given week. What do you want to know? Analytics-driven from the data you already collect could make your job easier. Imagine having metrics at your fingertips either to predict future growth, quantitatively or to validate any of a hundred hunches you may be having. Perhaps we should explore how Data Analytics if properly used, could work for you. See if Data Analytics can be a game-changer for you.
Data Analytics is a powerful tool for organizations that can help you make informed business decisions. Data Analytics can be used, for example, to; track a given decision’s impact, or to empower you to take continuous timely decisions to meet your business goals. How? By extracting trends, patterns and actionable insights from historical data.
Once you become enabled to make sense from patterns and trends you might have not had at your fingertips you can arrive at insights which aid your organization makes data-driven decisions. Imagine, no longer relying on opinions instead of decisions based on your gut alone.
Data analytics, when used effectively, can improve the productivity of your company. Used properly expect to cut your costs, Optimize Existing Processes, Deep dive on Risk Analysis, and achieve a high ROI (Return on Investment).
Let’s take that deeper dive with terms you might know:
As the name suggests descriptive analysis can process huge volumes of raw data and can give valuable insights by uncovering patterns hidden in the data. Support your gut feelings with data you believe is there but is difficult to validate quickly. Descriptive Analytics plows through the data.
By the way, this type of analysis will confirm what is happening often without explaining why. So, companies that are highly data-driven don’t just depend on descriptive analytics. Those firms prefer these other types of data analytics mentioned below.
The next question for your company is why your analytics occurred the way they have happened. What are the trends? What are the future trend possibilities? Diagnostic analytics does exactly that. This is the tool used to help you and your analysts to dig deeper into the existing environment. Validate actions and results. Identify the source of your problems.
Explore this example: You have financial data for different states in the country where you are doing business. You would like to know-how at each state is doing compared to the others. Where are your best customers? You are looking for trends. You are validating results. Maybe you are looking for your top sales producers.
All of these are Key metrics and can correspond to your business KPI’s (Key Performance Indicators). Let your systems do the work for you. The data will be collected. Then the data is presented in easy to understand information. How? A simple, customized, dashboard designed using Diagnostic analytics can be tailored just for you. Your counterparts can see what they need to see too. That is the value of Diagnostic analytics.
Automate your ability to Look Ahead. You will want to have this capability most of the time. Alluded to before, staying current, or ahead of trends may be important to your organization. Your systems, as we noted, capture the data which you already collect. Convert that raw data into useable information which can move your firm ahead.
Any business that wants to leapfrog the competition and increase customer satisfaction levels needs to drive foresight. By foresight I mean a company should be able to estimate what is likely to happen well in advance of actual results. Those results come from your Descriptive and Diagnostic analytics. Collectively, with these tools, you will be able to forecast future trends for your business, by region, or by market, even by customer.
This type of analysis reveals what actions should be considered to eliminate possible future problems. This state-of-the-art type of data analytics requires not only historical data, but also external information due to the nature of statistical algorithms. This can be your future. This can be where your competitive advantage waits for discovery.
This can be a great return on your investment if you define the value of using this tool. Not every case for Prescriptive Analytics is warranted. All of this can involve huge investments. Your company should compare required efforts vs. an expected added value before plunging down this road.
Example: Let’s say I am Analytics Director of a Music Streaming Organization and my Analysts have identified a customer segment who are more likely to churn in the next couple of months then I have to decide what should be the next promotion that I can offer to this customer segment so that they will continue to use my services.
The summary is simple. If you have resisted deploying and maintaining analytics-driven from data you might already collect, then you are being foolish. In modern-day business requirements, it comes down to the needs of the organization. Do your systems support the business processes which you have in place? Or do you calculate and guess manually? The question is simple: Can you easily dive deeply into your data to answer questions?
Can your company use a proactive approach where Predictive and Prescriptive Analytics would assist you in making data-driven decisions?
Can you create better and better information for your most complex decisions? Without Data Analytics you are slowing down the growth of your company. However small the delay may be the effect is cumulative. Providing the tools to manage the past performance metrics as you aggressively set new KPI’s is critical to keeping customers satisfied and increasing your revenues.
If you would like to know more about data analytics and how you can leverage it to its potential reach us at firstname.lastname@example.org