Principal Business Solutions Manager,
Going forward in business requires creating added value or in general stuff or content you can sell to somebody. But how does one know what to make or create? How and when? This is where data comes handy. The more data the better, right? As long as you’re not faced with big and fast data. Then the data might not be your friend anymore as it makes everything more difficult – difficult to store, analyze and manage in general.
Making sense of data requires analytics. But analytics only represents a tool – you still need smart people to ask the right questions. These can be business professionals or data scientists. There is advanced analytics as well – more advanced tools can lead you in the directions which questions you should be asking – as they see more and more complex connections and trends in the data. Tune it up a notch and there are technologies such as machine learning and artificial intelligence. Feeding them a bunch of data they can take over »sorting« and »sense making« and in the end simplify and automate decision making. And this is by no means only a »yes/no« type of decision making it can take on more complex forms as well.
Once your company or business users receive sorted and analyzed data or the ability to drill down, explore data - or ask straightforward questions and receive answers - they can also deliver better decisions. This leads to creating clear business advantage over competitors that are not using the data they are sitting on.
Every company has data. Some have little, some have plenty, some have too much. In order to use it best for business you have to sort and clean it first. Then you build models. You might even have to train them with your data. One of the things people that work with analytics rarely talk about is the time it takes to clean the data – they often manage, sort and clean the data about 80 % of the time and only perform analytics for the rest of time. This approach works just fine as cutting corners can be costly – you might end up with poor or simply wrong results because you didn’t put in the time to purify data. In the end the only data that matters is the data you can trust.
Business is a constant race to get ahead of competition. Fall back and you might lose for good. And it is usually better to lead than to follow. To the winner go the spoils. Therefore companies do not choose the means that can get them ahead of the competition. Modern analytics offers a plethora of tools to do so, extracting value from data and delivering it to business users. So they can make fast and right decisions, based on data they can trust. Soon every business decision will be backed by data, nobody will be making it by gut feeling anymore. At least not for a long time. This is why any serious company out there cannot afford not to use analytics.
Soon there will be no excuses. Digital Darwinism takes no prisoners. Moaning about costs and lack of skilled workforce are not going to get you anywhere. Analytics will. If you use it the right way.
When CFO or CEO comes to you and asks why data management and analytics is so costly and what can be done about it just ask him or her the following question: how much do wrong or poor decisions cost our company? I believe you won’t have to justify further investments in analytics anymore (or at least anytime soon).
I hope I did manage to explain the title of this article in full. In case I wasn’t clear about something, you can still approach the SAS team at Data Science Conference and we will go into more detail what can, should and will be done by SAS or your analytics environment.
Rosanda has more than 10 years of industry experience gained on complex projects provided for the largest banks and telco operators in the region. She is specialized in Marketing, CRM and Analytics domains and acts as trusted advisor when working with organizations from C-levels to consultants, bridging the gap between management, IT and business lines in order to define solutions and help increase value by mapping business requirements to the correct skills, technology, resources, data and processes.