Our benchmark research on business analytics in more than 2,500 organizations produced unprecedented information about business and IT usage and competency with analytics. It confirmed that effective use of business analytics requires a balance of people and skills, processes, information and technology not just to provide capabilities, but also to engage business analysts and users across the organization. The research also identified significant challenges facing organizations in terms of inefficient analytics processes and ineffective technology.
Making the most of business analytics means enabling the business analysts who support the departments and processes of the line of business. These individuals and teams may be found in finance, operations, the supply chain, sales, customer service, marketing and other areas; in each they are the ones accountable for using analytics to determine the metrics and key indicators that they need to present to management and collaborate closer together. These individuals usually work with their IT organizations for data access, but in some larger organizations they work with line-of-business technology groups. In recent years businesses have hired data-focused analysts to support their thirst for analytics across a range of data and sources.
Unfortunately, many IT departments are unable to provide automated data feeds fast enough to support the analysts, and that creates gaps in the analytic process. Our research found this to be a serious issue, as people spend 69 percent of their analytics time in data-related tasks, not only preparing data and reviewing it for quality and consistency but also just waiting for the data. This leaves too little time for analytic tasks such as determining root causes of issues, assembling scenarios for analysis and determining the impact to business from planned changes.
The best path forward is to ensure that these data-related activities are automated or streamlined to meet the business analytic needs. In addition, IT should spend less time trying to dumb down and standardize delivery of data through business intelligence and spend more cycles helping business analysts get the data at the frequency they need. In other words, IT needs more focus on data governance, which our benchmark found to be critical to bring data integration, data quality and master data management into a single, standard process.
Beyond the data gap in business analytics, the analysts have to deal with the issue of what technology they use to conduct analytics. As technology spending has gotten more controlled, centralized and standardized in IT organizations, fewer organizations have purchased specifically tailored analytics tools.
Instead, our research shows more use of spreadsheets; they’re the most often used technology in 60 percent of organizations, followed by business intelligence in 49 percent. Line of business or analyst-specific software is used in less than 20 percent of organizations. It is clear that this has to change, as more than half (55%) of organizations are dissatisfied with their analytics process, saying it is hard to build and maintain, and too slow. Well, that is what you get with spreadsheets, along with disorganized business processes.
What do business analysts need from their analytics technologies? Our benchmark research found the top request was access to source data for analytics (52%), followed closely by the ability to take action on the outcome of analytics (47%), the ability to design and maintain the business model (42%) and to quickly generate presentations and other analytics reports (41%). These might sound straightforward, but it’s not if you are using Microsoft Excel, and it’s even worse in a shared work environment. A growing base is looking for analytics to be delivered in an on-demand, software-as-a-service mode (27%), though more than half (52%) of organizations still prefer the status quo of buying and installing software on-premises.
All of this leads me to urge analysts to stand up and demand the tools they need to be more efficient in their analytic modeling and planning. Ask yourself how easily can you make changes to your analytics model and recalculate a forecast that links to the integrated business plan? Can you adjust and decrease a metric such as days sales outstanding (DSO) by one day to see the impact on cash flow in the business? Can you adjust the sales and operational plan by adjusting the forecast by one day? You should be able to make these and other model and variable updates in minutes, not days, and be able to share the results with others to determine actions and outcomes. Knowing that you can do the what-if and planning based analytics should be easy and straight forward.
At the same time, the speed at which analytics get computed and information generated needs to improve, and the assembly and deployment to business users must be made more efficient. Our research found that businesses want the basics; searching for specific answers was the top priority of 83 percent, who deemed it important or very important. Also important is exploring the data underlying analytics through drilling and navigation, cited by 78 percent of organizations. These are not standard functionality in spreadsheets, presentations and documents, and not what you get in reports or most dashboards.
Our research indicates that the more innovative the organization, the more sophisticated the results. We performed our own root-cause diagnostic on these mature organizations and found that they have automated the data aspects of business analytics from data access to data quality. They also are able to generate more sophisticated analytics and metrics, and perform more frequent reviews. These organizations also foster great relationships between their analysts and their IT teams, which work collaboratively on business analytics. These organizations are also the ones expanding their deployments to smartphones and tablets, integrating forecasting and planning and using predictive analytics.
The time has come for business analysts to lead the fight to improve business analytics to ensure their organizations have the information they need. Instead of having silos of reports, dashboards, spreadsheets and other data points, organizations need unified analytics and planning capabilities built into a common set of technology using a sophisticated modeling for representing the business and integrating data efficiently. Our recent business intelligence and performance management benchmark research found that this need to bring analytics and planning together is a top priority in more mature, sophisticated organizations.
So put the uncontrolled use of spreadsheets into the box it came out of and focus on working together to ensure that business analytics is like any business process – documented and automated to meet the majority of an organization’s needs. Look for simple and sophisticated means for analysts to work together on the business analytics journey and ensure you vocalize your needs for better investments. If you are not sure if you have the business analytics you need, let me know. The self-assessment is easy, but planning to adapt and change, well, that might take some work.
Sofia