Organizations Need go-to Strategies for Isolating Actionable Data By Mindgrub The unique and highly lucrative insights associated with advanced analytics has pushed big data into the spotlight for numerous industries where managing supply chains and complex business processes dominate daily operations. But simply expanding an organization’s data monitoring strategies is no longer sufficient. Businesses must acquire the tools necessary to efficiently analyze and present relevant data as well. Once these capability requirements are met, businesses can effectively use the data generated in-house as an actionable tool for reducing risk, holding departments accountable for compliance, creating instant performance feedback and scheduling operations with greater efficiency. Considering the major advantage gained by organizations deploying business tools capable of turning massive archives of information into actionable data, it makes sense for operations managers and executive decision-makers to get a clear sense of what they’ll need from their updated data strategies. Advanced reporting tools provide managers with accurate overviews One arena where organizations experience a great need actionable data tools is in daily reporting. With the right analytics tools in place, decision makers will receive daily updates that offer not just a snapshot of operations but also real-time data points pertaining to key performance indicators. Streamlined access to these resources also allow decision makers to update operations immediately when new market trends begin to make a major impact on their respective industries. Without access to actionable data, accurately predicting an industry’s next direction becomes a considerably more difficult challenge. Custom alerts keep decision-makers up to date 24/7 In order for data resources to be considered truly actionable, they must be capable of driving positive change for organizations above and beyond daily updates, both in terms of frequency and scope. Analytics can make this possible by helping users make sense of huge data sets collected from the supply chain and determining the key indicators that most closely reflect the efficiency and performance of the process. Major changes to these key indicators likely represent abnormality in an organization’s process, for good or ill, that requires immediate attention. Data tools should be able to collect information and update users on how this information changes over time with equal ease, according to Supply Chain Digital. Otherwise, companies will need a new solution that produces actionable data as soon as possible. Better business intelligence turns monitoring into risk reduction One hurdle that holds back companies leveraging business intelligence is the key performance indicators themselves. Often these benchmarks are generated from data acquired and analyzed before an analytics tool and actionable results were readily available. As a result, these indicators may be unresponsive to changes in the process that actually generate considerable value. Actionable data is the key to taking the next step. Performance indicators designed prior to analytics deployment generally depend on data monitoring to make corrections to undesirable outcomes. However, this reactive data strategy is limited. Contrarily, dynamic performance indicators designed from predictive analytics data allow companies to be more proactive about their problem-solving and turn monitoring tasks into risk reduction. Companies need a new solution for actionable data as soon as possible. Actionable data is critical for generating ROI from information resources At times, the biggest obstacle preventing companies from collecting actionable insights is the culture of the organization, according to Forbes. Despite major investments in analytics programs and business intelligence resources, it’s not uncommon for managers to continue trusting a gut feeling or processes born from tribal knowledge over the data compiled and analyzed by an analytics platform. These scenarios compromise the ROI potential for analytics investments. Even worse, this type of internal culture limits the organization’s competitiveness compared to companies that have embraced these insights and are now making process improvements based on actionable data. Thankfully, there are several ways to adjust operations to maximize the value of information resources. Selecting a change driver within the company to lead the transition and communicate the value of actionable insights will certainly help the process along. Leveraging external resources can also be a smart strategy to this end as experienced analytics professionals can recommend new strategies for turning data collection into problem solving. These solutions can only be effective with buy-in from the entire company, so decision-makers may need to address bad employee habits with new policies to turn analytics adoption into a success.