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5 Business Intelligence Myths Debunked

Article by Scott Yates, Senior Director, Operations at HGS 

Taking a passive approach to Business Intelligence (BI) is a mistake many companies today make. Their competitors mine data related to optimize their stake in the marketplace starting from their customers, and products all the way to market share and patterns of growth. But why are so many companies still so fearful of BI? Here are the top five myths debunked:

1. MYTH: Only structured data is valuable.

FACT: Structured and unstructured data are equally valuable.

BI is not black and white, in terms of structured and unstructured data. There are gray areas, in which unstructured data can be structured with simple analytics tools. For example, Excel, is a basic yet effective tool with the right procedures in the front end. A company can even take simple strategy on the front lines like using notes in Excel to delineate using pre-determined words or the seasonal product/campaign for a platform like Twitter. With this simple and unstructured coding, teams can measure feedback with a formula that parallels the coding taxonomy on which the Twitter platform works. This approach is not burdened by structured data organization, instead delivers the precise accuracy and minimal error rate of more costly structured BI tools. There is such a thing as over-analyzing your data—which can drain resources and raise costs. This solution works in the “gray area” of data, to mine unstructured data in a simple and cost-effective manner.

2. MYTH: Good business intelligence is mined from only digital solutions.

FACT: There is no one-size-fits-all solution for business intelligence. According to IDC, communication channel preferences vary depending on the type of interaction customers are seeking. If 76 percent of respondents select voice call as one of the top two ways to report a problem with a product or service. That company then needs to meet their customers halfway—mining the insights across channels. For example, despite the on set of digital solutions like social media in the spotlight today; voice is still a key player, providing the same level of potential as social media and website insights. BI solutions should be deployed based on intended audience (for example, dashboard for agents, analytics for Marketing). 

3. MYTH: Data is good no matter when it’s used.

FACT: Data is a moving target, and real-time dashboards provide the best opportunity to capture and act on your data. Insights can depreciate at an alarming rate. What happened yesterday isn’t as valuable a week from today. As such, time to address important issues is fleeting. Data can be devalued if not capturing relevant data points in real-time using a single dashboard. Text analytics can decode what’s being said and the sentiment of topics, through social media conversations, product rating and reviews, chat logs, idea portals, and customer online community discussions. Understanding customer intelligence will help customer care centers proactively identify a crisis waiting to happen, capture new ideas, and uncover quality or warranty issues. Most importantly, real-time tools can personalize engagement with the customers.

4. MYTH: It takes a data scientist to build robotic process automation (RPA) to mine your data.

FACT: Business intelligence tools are not so highly technical and complicated that you need a qualified IT specialist. It’s not just about building an algorithm—the creative process starts with a business’s stated vision. With the right starting point, translation, and toolbox, a custom report can be designed. Collaborate with your clients as partners to ensure that they are actively engaged, so their vision is 100% true to their brand and objectives. Together, you and your clients can build custom report, teaching your clients how to move forward with the BI results and be more involved in future creative process and a longer-term strategy to optimize insights for results.

5. MYTH: Business intelligence is only valuable for major corporations.

FACT: Today big and small companies should be deploying available tools and expertise to drive company decisions. Data size is equally unimportant—in today’s world, no business or data size should prohibit use of good BI to sharpen operations. There’s no denying the reality of market competition and the likes of the current product landscape, which leans heavily on feedback, ratings, and reviews. You may be a one-person shop, but you’re competing with Amazon. To this point, don’t assume that BI is too costly. BPOs can and will help with fast-based models and shared resources, for a cost-effective approach. There are tools for less than $1,000. Some of these tools are as simple as an SQL web server on an Amazon-hosted web server or a Google-hosted web server or database. BI investments vary considerably—and in terms of ROI, remember that handling BI manually can, in fact, be the most expensive option. With a cost-benefit analysis, you can appropriately start and scale your BI to help bridge maturation of your business. And make sure there are enough a-ha moments along the way to justify expense level—in terms of product development, decision-making, and overall strategy.

Source: InsideBigDATA