When it comes to transforming raw data into an effective information that can be used for sales projection, market research (like we are using it in data-driven marketing) and other predictive analytics, the first thing that comes to mind is: “Which Business Intelligence Method will be more suitable for this?”
Business intelligence (BI) is accelerating and encompasses nearly every aspect of the business, from sales to human resources. It applies across all industries around the globe.
According to a 2016 report, Business Intelligence and data analytics were listed for the fifth year in a row as a high-level priority for top CIOs.
Honestly speaking, now is the best time to adopt a BI tool into your daily business affairs as a startup entrepreneur. The methods listed can be applied by any SMB, even those with minimal existing data.
1. Diversify Your Data Source
Modern BI tools can mine data from a diverse array of sources. This even includes unstructured data, such as information acquired from sources like email, social media posts, word processing documents, and even uploaded videos.
Diversifying your data also means going beyond data from sales and customer retention.
Companies have a natural tendency to focus almost exclusively on these areas, which is understandable considering the fact that this is the department where revenue is made.
However, BI tools also exist for other areas, such as those for detecting fraud and those that gather data on employee retention.
Why do these areas matter? With employee retention, for example, one study showed that it costs $20,000 to $30,000 to recruit for a job vacancy that pays an annual salary of $40,000. But having business intelligence, BI in human resource HR can help identify trends that may reduce turnover rate.
Data mining from various departments helps entrepreneurs cut back on overhead spending. This is why BI needs to be relevant in all departments.
2. Let the Software Handle the Number Crunching
BI tools handle much of the data collection. Let the software handle this aspect. This needs to be pointed out because many companies still lean on manual data input entry via Excel spreadsheet. Some even still log data using pen and paper.
This method leaves open the possibility of human error. One analysis reveals that as many as 88% of Excel sheets contain errors. With manual entry, it’s all too easy to input a wrong number, enter the same number twice, or input the number in the wrong cell. All it takes is a single error to throw the entire data off.
Think about the overall effect of that on your business… Think.
Automated number crunching is a basic feature in most BI tools; put this feature to good use. No startup entrepreneur should be losing when the solution they need could be automated using simple software.
3. Mobile Access
BYOD environments are commonplace these days. This is perfectly acceptable and encouraged as long as there are strict policies in place regarding access rules and rights. This is pivotal for security reasons.
Staff will quickly familiarize themselves with the company’s BI tool when they could access it on their own device, in and out of the office.
Most BI systems also have a mobile version that is optimized for smaller screens. Users can access the system and check the latest data updates in real-time. They can also submit comments and notes to other users just as easily as sending a social media post.
4. Define Your Metrics
Even the top-of-the-line BI systems are useless if you don’t give it the right data to compute. Metrics have to be specific.
A metric that evaluates overall sales for a given month is too broad and should be refined. Here are a few examples of specific metrics for the retail industry:
- Loyalty program sign up among customers who purchased a specific product within X number of days or weeks
- Organic traffic results within 24 hours of promotional offer announcement on social media
- Referral program sign-ups among customers that have used your latest Twitter hashtag
These examples show how to formulate a metric. It should never just be “loyalty program sign-up.” Rather, it should be “loyalty program signups that …”
This enables you to determine the behaviors and patterns of a very distinct and small demographic group.
5. Data Storytelling
BI tools go beyond data mining and computing. It collects the data and converts the information into a visual format that is easy to interpret by a human reader. Formats include a number of visual aids, such as the standard bar graph or pie chart.
This may also include Venn diagrams or whatever makes the accumulated data readable without looking through a near-endless excel sheet of numbers. You can even turn your data into maps.
Determine which type of visual format works best for each data type. You can also have two or more visuals side by side. Perhaps you want two bar graphs to look at month-to-month sales from this year and compare them to month-to-month sales from the previous year. Maybe you want a pie chart to look at the breakdown of loyalty program enrollment by geo-location and compare it to a line chart showing the sales fluctuation of a certain product.
Whichever way you want it, using these business intelligence methods outlined here can help you achieve that seamlessly.
Business intelligence is the new forefront for critical decision making in the office. With BI tools more accessible than ever, now is the time to integrate them into a daily part of your office ritual. Is your company already using business intelligence? Or you are waiting until your competitors knock you off your balance with these tools.
Any startup entrepreneur that desires to step up their game will surely value this article.
This is a guest post written by Lucy Boyle. She’s a mother, a blogger, and a freelance business consultant; currently a regular contributor to Allocable’s blog. Follow her on Twitter, @BoyleLucy2.