Organizations and enterprises must design an effective analytic and reporting framework to realize a comprehensive business intelligence platform. This strategy entails the end-user being able to effectively consume and use integrated data for decision-making and competitive positioning.
Performing sophisticated and innovative analytics and reporting is becoming critical for enterprises. Gathering the relevant data, processing, and reporting enhances evidence-based decisions and drives business growth. Businesses can use processed data to shape decision-making in areas such as; sourcing, supply, marketing, research, contract management, and development.
The right analytics and reporting have the desired impact on performance and productivity, fundamentally changing how people perform their jobs and make business-oriented decisions. Some of the few benefits of a successful reporting strategy include:
- Increased productivity
- Targeted delivery of reporting and analytic capabilities
- Employee satisfaction
- Improved decision-making and analysis
- Increased collaboration and organizational communication
Despite the growing significance of data analytics in business operational processes, there are major reporting challenges faced by enterprises. It's with no doubt that management reports drive business decisions, meaning that bad reports lead to poor decisions and innovative reports deliver business value. However, reporting problems can inhibit efficient data use and affect business decision-making. Three reporting challenges that teams and departments consistently face include:
- Painful Data Gathering and Collation. Data exists in many different formats. Most times, these data sources are owned and managed by different departments. Too much time is spent during data gathering and collation, leaving less time for mission-critical operations like processing and reporting.
- Incorrect, Stale, and Old Data. By the time teams collect huge datasets and layer them into different digestible formats, it's usually out of date. New customers are renewing monthly, sales are closing daily, and business opportunities are opening at every turn. With static and outdated datasets, it is difficult to cope in such a dynamic environment.
- Numbers are Misleading. The story behind data entails the information and details that drive business intelligence, and data must tie up into a narrative. One simple error can cast doubt across your entire report – and put your team in the hot seat.
Tips for Getting and Using the Analytics That You Need
Do you want to get the best out of your data and reporting? Here are the top tips:
1. Consider your work a search for hidden treasure
You must view data analysis as a search for hidden treasure. Data mining resembles gold mining. You’re sifting or pounding your way through the complexity in search of valuable nuggets.
2. Collect more data
You should work to generate more data. However, in some cases, useful data can be generated easily and economically. For example, ask your customers how they came to know you, and you'll obtain insights into your marketing efforts to build on your outreach campaign.
3. Run experiments regularly
Data collection methods such as pilot studies and experimenting via AB testing can economically generate data of exceptional value. For example, you can use pay-per-click to gauge product visibility. This technique will result in a more accurate analytical conclusion than focused groups.
4. Go big with databases
It’s advisable to work with huge datasets and bigger samples to obtain a comprehensive view. Using bigger samples and datasets enables you to broaden your focus and narrow your scope on what data matters to your enterprise.
5. Do not delegate data management
Having a young tech-savvy intern is the best approach to handling data analysis for most SMEs. But if you talk to the professionals handling data analytics, you're likely to hear something different about your data management strategy. That is why most enterprises outsource managed service providers to manage their IT environment.
6. Protect proprietary data sources
You want to protect data assets because proprietary data sources have enormous value. So, this means that you regularly want to store and backup the data. But that's not all. Protecting your proprietary data means that you want the data to remain proprietary and that any insights contained in the data must remain internal.
CSIFLEX – Your Leading Partner in Analytics Reporting
Big data analytics has taken the world by storm. Big data is shaping business intelligence, and enterprises that are using big data are reaping enormous rewards. The benefits of big data include: increased efficiency, improving pricing, competitive positioning, business focus, and improving sales. But for you to analyze big data, optimize reporting and reap these rewards, you need to identify your business issues and solve them using data analytics.
Contact CSIFLEX to streamline analytics reporting and business efficiency.