To build an in-demand business intelligence (BI) product we must first do justice to its proper definition by concept, areas of use, why is it important, and overall, how they can be implemented even to the most minute scale.
Business Intelligence (BI) is the concept of delivering fact-checked solutions to business issues using technology. BI comprises the strategies and technologies used by enterprises for the data analysis and management of business information. BI tools are used to handle structured, unstructured, and semi-structured data sometimes in large amounts (big data) to help in their processing, analysis and finally developing insights. Although many aspects of BI can be automated as we will see shortly, there is however a need for human inputs to reach a consensus while implementing the insights from the reports generated by a BI tool.
Why is BI so important to organizations?
Insights from BI tools help organizations tell a better story about their well-being or general activity. This goes a step further in shaping their decisions and helping them increase revenue amidst a host of other benefits. Without BI organizations cannot use factual data for insights, they tend to rely on experience or historical data which at best may not give a holistic view of the issues.
Apart from driving revenue, BI tools can help an organization optimize its internal business process by ensuring that resources are mapped out in the correct proportions when needed. Processes that do not seem to flow into one another properly due to some unknown bottlenecks are easily greyed out. Businesses can easily spot problems that are not usually visible because with a BI tool management has a bird’s eye view of the entire line of business no matter how large an organization is. This is because a lot of the performance indices or data have already been captured in real-time or near real-time. This accounts for a quick assessment and affords the least cognizant some in-depth knowledge of the situation.
It increases operational productivity and efficiency when all factors necessary for success are considered simultaneously. Businesses whose products are underperforming can easily use BI to engage sales and marketing to get an insight into how consumers perceive the products and find out areas that need to be further explored in terms of emerging businesses through market trends.
Areas of use
Business intelligence can virtually be used in almost all forms of business. As long as a business leaves a footprint daily and needs to drive profit or find out ways it needs to improve as explained above then it needs BI.
It can be found in different industries as can be seen below
- Manufacturing: Business intelligence is used to gather data about the machinery, workforce, Inventory, supply chain, target KPIs, and organizational milestones. From these sets of data maintenance schedules are made, the workforce is well managed, and the raw materials needed for production and maintenance activity are well stocked. A lot of activities happening on the shop floor can be monitored using some IIoT (Industrial Internet of Things) enabled devices that in turn send the data captured to an on-premises data warehouse or data cloud. These insights can be derived or arrived at using expertise in BI tools.
- Hospitality: The hospitality industry is comprised of travel and tours, hotels, leisure, and recreation. The hotel industry alone operates large sets of data ranging from housekeeping, distribution channels, and customer behavior to direct customer experience. BI tools exist to help in capturing these types of data. This can be used to drive insights into the need to increase the workforce, make adjustments to accommodate customer preferences, and explore other areas of emerging business.
- Aviation: some processes may appear complex in the aviation industry such as the number of passengers available for a flight viz a viz delayed flight and subsequent rescheduling. BI tools can be used to harness the power of data by ensuring the reasons for delayed flights are captured and analyzed over several similar cases. A lot of data can be captured using the sensors aboard an airline for scheduling maintenance, data available from the front desk can be used for flight scheduling based on historical data, and data available from community inputs can be used for crew scheduling based on crew availability. All these are used by a BI tool to drive insights extensively.
- Agriculture: BI tools can be used to track crop performance using weather forecasts and this in turn helps farmers plan for additional needs such as labor, and fertilizer interventions. Using modern sensor technology large sets of data can be generated from the field, farm steads, animal husbandry, etc. These kinds of data collected by farming organizations are virtually impossible using conventional methods. Adopting BI systems makes these herculean tasks much more easier and decisions that are mostly based on forecasts are reached quickly.
- Food and Retail: the food industry is densely populated and equally rewarding for the majority of its players. Major key players in this industry are already harnessing business intelligence data and stats in untapped niches and are using the same to make informed decisions. Restaurants can take advantage of the BI tools in managing inventory for effective procurement strategy, and streamline services to meet a line of business by gathering specific data. Large retail chains can make use of BI tools in planning for the workforce, gathering information on the best-performing goods based on geographical area so that proper reallocations can be made.
- Oil and gas: this industry will not be termed a latecomer to the BI space as most of its critical decision-making is entrenched on lots of available data such as more technically oriented data such as seismic, mud density, flow rate, temperatures, etc. Other necessary data usually collected in this industry include geographical data, workforce, machinery or assets, operations monitoring, vendor operations, etc. The aforementioned are some of the data required by a very robust BI tool to give the forecasts of events necessary in making key decisions in this industry.
As we can see from above a lot of the industries mentioned above require extensive use of BI tooling to remain in business and perform better. BI is of essential purpose and will continue to remain a key player in any organization’s decision-making.
Steps to implementing BI
To implement BI in any organization the following steps are taken into consideration
- The possible sources of data are first identified. For example, an organization looking to cut down on overhead costs must ensure data on inventory is well maintained. Also, the organization in question must be able to identify key performance indicators that are essential to its success rate.
- Data Gathering: The second step of implementing a BI solution is to gather the data based on the agreed KPIs already established in step one above. The data gathered must be uniform, clean, and clear. To achieve this management must ensure all stakeholders are updated on the new policy or guidelines for data gathering. This will ensure its promotion and eventual success.
- Storage: a lot of storage modes are available for organizations looking to implement BI in their organizations. The storage mode includes On-Premises data warehouses and data cloud warehouses. While the former is a bit rigid and prone to other associated risks such as theft, hacks, or sabotage, the latter makes up for it by being very flexible, and more secure, with less risk of theft or ransomware hacks, etc. Following the high cost of implementation, a host of options exists for organizations to make a worthwhile choice.
- Data Analytics: This involves the cleaning, transformation, and eventual visualization of the data using a BI tool that can do a host of these activities. Most often the data to be gathered require that the BI tool is integrated into an existing CRM and ERP etc. The overall goal here is to have the data analyzed using the BI tool and a visualization generated.
- Reporting and Decision: This involves a seamless presentation of the visualization generated in step four to the management. Through this visualization decisions can be arrived at.
- Implementation and Adoption: The implementation of the decision reached in step five is crucial to every BI project. This requires making sure all stakeholders are present when decisions are made so that implementation can be successful.
In conclusion, we have seen those BI drives business growth and makes up for ease of decision-making, it goes without saying that the implementation of BI into any business or organization is a delicate affair and must be handled with clear intentions and objectives.
