Business intelligence is no longer a thing of the future. Organizations striving for long-term growth and success realize the future is now, and that digital transformation is a critical component to their growth strategy. In fact, a recent study conducted by MuleSoft indicates that 74% of IT decision makers have started the digital transformation integration process. And what were their top initiative objectives? Improving operational efficiency, leading at 83%, enhancing customer experience was second at 71%, and increasing business efficiency came in third, at 70%.
By adopting a BI approach, leaders are able to make more data-driven decisions, gaining a competitive edge and further elevating them to success. Spreadsheets are now being replaced by more accurate, actionable data, keeping executives up-to-date in a business landscape that is changing at a rapid rate.
Leading decision-makers across the globe weighed in on today’s most discussed business intelligence trends. Whether you are an entrepreneur just starting out, or a facility executive, these strategies should be a top priority as you position your organization for success.
1) Predictive and Prescriptive Business Analytics Tools
A successful business intelligence strategy focuses as much on what will happen tomorrow, as what is happening today. As a result, prescriptive and predictive analytics are at the forefront of every BI professional’s strategy.
Predictive analytics is the process of extracting data to identify and forecast future probabilities. Because it uses past data to estimate future data, there is a margin for error. Historical data is used to gain a better understanding of products, partners, and customers. It can also be used to identify potential future risks, as well as business opportunities.
Each industry harnesses the power of predictive analytics in a different way. Bankers can use it to generate a credit score and forecast a potential client’s ability to pay back a loan. Hotels use it to adjust room rates based on predicted occupancy rates.
Artificial Neural Networks (ANN) and Autoregressive Integrated Moving Average (ARIMA) are the two predictive analytics methods that are currently attracting the most attention. Without delving into the complex details, ANN discovers regularities and irregularities and makes connections from a large pool of data that contains a great number of variables and diversity. ARIMA brings offers a clearer understanding of behavior within the data series. It identifies underlying patterns, helping decision-makers predict future anomalies. While both tools are complicated, the added value to an organization’s predictive strategy makes a compelling argument for investment.
Prescriptive analytics helps organizations predict the future on a deeper level. It helps C-suite understand what effect future decisions will have on the enterprise and how to adjust decisions accordingly. Because it considers the big picture in its analysis, decision-making is enhances significantly. It is most useful when optimizing processes associated with inventory, production, supply chain, and scheduling.
2) Data Governance
Data governance is defined by the DGI (Data Governance Institute) as being “the exercise of decision-making and authority for data-related matters.” Despite popular opinion, data governance does not focus solely on data breaches.
Organizational leaders are now refining their efforts to collect data, increasing their focus on both quality and governance. The goal – to strike a balance between security and access, while still remaining flexible in an ever-changing business landscape. With higher-quality and collaborative processes, enterprises are now maximizing the value data analytics adds, without sacrificing security.
3) The Multi-Cloud Strategy
44% of IT decision makers polled by MuleSoft are adopting a multi-cloud strategy in 2018. As organizational needs become increasingly more specific, so, too, have the business tools available on the market. Businesses now have the option to invest in a variety of different cloud-based solutions, each designed with their own needs in mind. Cost, speed, complexity, and risk should also be taken into account. A diverse set of BI tools stands to significantly reduce risk, increase flexibility and, in turn, enhance workforce engagement.
“By 2019, the cloud will be the common strategy for 70% of the companies.” –Gartner
4) AI/Machine Learning
Read any business journal or blog and you are guaranteed to find something about the topic of artificial intelligence (AI) and what it can do. While many predict AI will replace a majority of our jobs in the near future, its current business value and intention is to assist analysts. With the right machine learning tools on their side, they are able to be more precise in their analysis and, as a result, make a more positive impact on their organization.
Machine learning adds value on multiple levels. First, it automates mundane tasks that are typically labor-intensive, such as basic math, for example. By freeing up this time, analysts are better able to focus on the task at hand – looking at their analysis in broader terms. A more intricate analysis allows them to better plan for future needs, further enhancing overall efficiency. Additionally, analysts now have access to real-time data that helps uncover the deeper questions they should be asking. With a clear set of defined goals, AI serves as an invaluable tool for today’s business analysts and decision-makers.
As news reports are filled with an increasing number of large companies experiencing data breaches, security continues to move up in importance for organizations seeking to enhance their business intelligence strategies. If a global corporation is vulnerable, where does that position the small businesses?
As organizations seek out new BI tools to invest in, database security will continue to be a leading concern for business leaders across the globe. Organizations must align themselves with software vendors who offer the most secure solution, going to extreme measures to secure client data.
Stay tuned for next week’s blog, as we discuss the second part of our series, Top Business Intelligence Trends of 2018: Part 2.