The digital transformation of production and business processes has made data a key player in the digitization cycle.
Organizations’ information systems have accumulated exponential amounts of data and now is the time to take advantage of them and obtain from them information that optimizes day-to-day decision making. Now, understanding what to do with them and how to deal with them is the priority.
How to approach a data project
Business objectives aligned with your business strategy will determine the scope of your data project phases, which include:
- Generation and capture. Identify what data is available, so you know what technology solutions to implement to process it, drive the digital generation of new data and continue to capture much more of it in real time.
- Modeling. Now it is the turn to analyze, transform and structure the captured data, i.e. to shape it into useful information.
- Exploitation. With the data already structured, the time has come to process them in order to take full advantage of their potential.
Data mining
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Identify deviations in real time
Data mining, through dashboards, shows the end user the KPIs of the business. However, this user must now analyze them to draw conclusions. But data mining seeks to take us one step further. To do so, it considers data as proactive, i.e., it can speak for itself when aided by Artificial Intelligence (AI) and Big Data. This will build intelligent models that help detect deviations. Continuous analysis of data sets will make it possible to identify common and persistent patterns over time, as well as indicate when something is not right, going beyond the information provided by a predefined KPI and alerting about anomalous behavior. This is an excellent way to uncover hidden problems or bottlenecks. -
Self-learning
By combining data analytics with Machine Learning components it is possible to create highly reliable predictive models on production parameters, which can help optimize the organization's business strategy. Feedback and learning on these predictive models will help you anticipate errors, deviations or interruptions in business processes. -
Dashboards
This is ultimately the most widespread mode of data mining. The main benefit it brings to business management lies in showing the end user, at a glance, information that helps him to determine whether the processes under his responsibility are working properly or not. But a good dashboard that produces effective results needs content that is aligned with the objectives of the user for whom it was created. This is the only way to avoid information overload and work with specific data that facilitates decision making for that particular user. On the other hand, dashboards must also be consistent with business objectives so that they can indicate the status and evolution, over a given period of time, of specific and representative KPIs. At the end of the day, this management tool must be simple and visual enough to emulate a snapshot of the organization's processes in real time. Whether you need one, two or more dashboards is up to your business objectives.
Data science and exploitation
As we have said, data mining, as part of data science, facilitates intelligent decision making and enables the generation of effective business strategies in the short, medium and long term.
It is important to maintain the systematic use of data science, either under Business Intelligence (BI) or Business Analytics (BA). Both terms sound similar and can be confusing, however, there is a big difference between them.
BI is the analysis of captured data. For example, if you are looking to improve internal operations in your supply chain, uncover process flaws and identify potential indicators, a BI solution is the perfect way to achieve this.
On the other hand, if you need to predict the future behavior of your organization, establish trends, find out why things happen, then a BA solution should be included in your business strategy. This way, you will be able to solve problems even before they occur!
In short, with both models, collecting, analyzing and generating visual dashboards simply changes the approach to analyzing the data to make decisions in the organization.
Business Intelligence o Business Analytics. Which one is better?
Making the decision between BI or BA does not have to be a complex or lengthy process. It depends entirely on your business objectives. Just ask yourself several questions, such as:
- What do you need to solve?
- Who will use the tool?
- How much visibility do you require in the process?
- Do you care more about understanding why your business is where it is or rather where your company should be headed?
- What's more valuable? Knowing who your top 10 customers were last year or who your top 10 customers will be next year.
In short, data analysis has ceased to be an option and has become a must for any organization. The business that does not adapt to the new way of valuing and treating data will simply disappear.
At CeleriTech we are aware of this reality and therefore, we have created tools for you to decide the future of your organization based on data. With Keenlog Analytics and Keenlog Predictive, you can take advantage of data from your SAP Business One and other sources, so you can react and act faster, make informed decisions in real time and drive profitable growth.
More than 16 years of experience in the industry allow us, as a technology solutions provider, to work hand in hand with your organization and help you make intelligent decisions based on your most valuable asset:The Data. A free DEMO of our tools is available for you today. Contact us!
