February 9, 2021
The aim to create, developing ideas, products, and processes to solve our never-ending challenges is a human urge. Despite challenging circumstances, we find opportunities to assess, learn, and grow every day. With the current global landscape, businesses have changed and we’ve been pushed out of our daily routines and professional comfort zones. Now that we’re starting to get a chance to catch our breath and get back on our feet, many businesses are faced with the massive amounts of information we’ve generated and collected during the pandemic as we’ve transitioned and adjusted to our new working worlds. So let’s take a look at how we can use what we’ve learned from 2020 and apply it to the landscape of data and analytics going forward.
What is Decision Intelligence?
There were significant strides in Artificial Intelligence (AI), Machine Learning (ML), and Data Science (DS) technologies this past year. Many bright minds found time freed by reducing commutes gave them opportunities to develop algorithms and tools that will help make use of the data businesses collect en masse every day. Therefore, Decision Intelligence (DI) refers to applying AI analysis results to decision making, management, and support. Decision intelligence offers a framework of best practices in organizational decision-making while also focusing on the needs of the business and incorporating the results of tailored machine learning algorithms.
As the demanding business environment begins to pick up pace, decision-makers in complex situations need to quickly come up with scalable solutions. Instead of coming up with a quick-fix, they are expected to provide long-lasting solutions across vast resource-intensive data sets that can be difficult to calculate and account for alone. Businesses who maximize their AI and ML resources when making decisions will see far greater long-term security than others who use them for simple insights.
That’s not to say that adopting decision management and modelling technology is not without its own considerations. Your team will have to consider how many logical and mathematical techniques you want to invest in, whether they must be automated or semi-automated, or must be documented and audited. It’s important to have a proper understanding of business needs and critical problems and the company should have a platform that can handle complex datasets.
Decision Intelligence in the Legal Department
The legal industry might have been slower in adopting AI technology but more and more law firms and legal departments are working towards automating their processes and gathering valuable business intelligence for better decision making. Now with Decision Intelligence options such as Counself Insight in the market, organizations that step up and take advantage of an intelligence-based decision making framework can transform their decision models and see effective ways to solve their problems.
Decision Intelligence is a newer discipline in the field of AI, but it is still highly regarded for its significance and is included in Gartner’s Top 10 Trends in Data and Analytics for 2020. This report is based on the aftermath of the pandemic, using the data collected during the peak of the pandemic to help identify best practices and make better future decisions. Gartner predicts that two years from now more than 33% of large organizations will have analysts practicing decision intelligence, including decision modelling. Do you want to be the firm or legal department left behind?