Benefits of Business Intelligence
Business Intelligence (BI) software is increasingly taking more of a commanding position in the Enterprise market. But, it can be hard to know whether your business should be utilizing a BI tool or not. In the following points we give you five ways that BI can benefit your business. We’ll also round out this post with some information on whether using such high powered software is right for your business.
Simplifies Complex Data
Let’s agree that data is a complex beast to master and understand. Even with talented data analysts on your payroll it can be a real headache (not to mention time consuming) of an ordeal to not only aggregate your company’s relevant data, but to put it together in a way that can be insightful to people who aren’t data analysts. Needless to say it takes talented people to decipher what your company’s transactional, foundational, and informational data has to say about the customers that are transacting with you and what your projected growth looks like.
That being said the right BI technology can give you highly visible results more quickly. Take for example, Tableau, an analytics software that helps businesses make sense of their data by giving employees the ability to produce visual windows that look to the core of what your data has to say about your current state of affairs.
By automating the process of how you deliver highly visible data you can also empower people on all ends of your organization with the data they need to succeed. By implementing BI tools that are geared towards data visualization you ensure that everyone on your team has the opportunity to learn from the information that’s most important to their perspective verticals. Simply put, the proliferation of visible data empowers individuals to be decision makers. What’s more, the right BI tool will not only put high quality metrics into the hands of your employees, it should also offer data visualization in real time, which means that no one should have to rely on last quarters numbers to predict what next quarters numbers should look like.
Provides Social Intelligence
Your business probably already uses some type of third party social media management tool. Whether you’re using Hootsuite for social posting and scheduling, or you’re using a tool like Sprout Social which gives you the ability to analyze your performance across multiple social media channels, there are a number of applications that can help you organize the daily, weekly, monthly, and yearly mess of your social efforts. But can any of the tools you’re currently using help you visualize why a post wasn’t successful? More importantly, can any tool you’re currently using help you predict what kind of blog post will be successful at engaging users across different social channels?
Business Intelligence tools are all about helping organizations mine and make sense of data—after all, in this day and age, staying ahead of the curve is the only way for your business to remain agile. It’s only natural then that one of the biggest reasons for a business to adopt a BI system is to keep up with their social presence. Not only is there a ton of data on Social media that can lead to valuable customer insights, consumers now expect to be able to interact with brands on social media.
In fact, a recent slide share by Hubspot suggests that if your organization isn’t on four or more different social networks, then you might not be doing enough social networking to be relevant. Of course being on multiple social networks requires a lot of upkeep and a lot of strategic placement of great content. With the right Business Intelligence platform—such as Adobe Social or IBM Social Media Analytics—your company’s marketing team can be poised to learn more from the customers that are currently engaging with you, which will lead to more acquisitions in the future.
Highlights Budget Inefficiencies
Traditionally, one way that enterprise level businesses cut costs is by hiring outside consultants. If you’re trying to become lean—without sacrificing scalability—contracting a few bright 20 somethings from firms like McKinsey or Bain has been a go to move for many companies.
However, reaching out to consultants in and of itself can be an expensive ordeal, and there’s no guarantee that you won’t need their services again down the road. On the other hand a BI software acquisition can for pay for itself by helping your company’s current decision makers identify areas for cost savings. For example, if you’re a retailer, an immediate effect that the right BI software can have is providing you with clear insight into your inventory. With better insight into your inventory, you’ll be enabled to make better decisions about which products to order, and which you already have in back stock.
What’s more, BI software can help you monitor everything from employee payments, to purchasing supplies, and will overall help you understand where every dollar is going. And with better understanding of your spending cycle, you can make more effective decisions that will have a positive impact on your bottom line.
The biggest resource that you have at your disposal is time, and, considering the above mentioned benefits, implementing a Business Intelligence tool can save you a lot of it while also improving your work flow. But the time you’re saving your company by automating interpretive data charts and creating clearer insights into KPI’s needs to go somewhere. Spend it making smarter decisions for the future.
Because Business Intelligence offers cutting edge accuracy on historical and real time data you’ll have greater effect at using that data to forecast future trends in a predictive manner. Any good BI tool will find patterns and identify future opportunities that your business can take advantage of.
For example, if you run a subscription based income model, BI software can help you identify which users are more likely to renew their subscriptions when their current contracts are over—which would obviously give your sales and marketing team an edge on retaining customers that are the least likely to renew their subscriptions.
At the end of the day, there are many BI software packages to choose from. Depending on your business size you may only need a BI tool like HubSpot which is specifically geared towards helping marketer’s see the full picture of their digital based efforts. If you’re a larger company you may want to take a look at tools like SAP Business Intelligence which can give you a top down view of every vertical within your business. Before contacting the sales department of any BI firm make sure you take cost into account. A tool like Hubspot can start at as low as $200 a month, while more advanced and in-depth BI tools Like SAP can easily cost thousands of dollars a month to operate. Before making a foray into the Business Intelligence solutions realm you should also understand what it is that you want your current data to be telling you.
Predictive analytic tools don’t solve just one thing. Instead, by utilizing predictive analytics software, your company can more easily solve many of the most common problems that face businesses today. Think of this post as a “predictive analytics for dummies” in terms of how you can apply this technology to different verticals within your field.
Preventing Future Threats
The name of the game in predictive analytics (as the name would suggest) is in analyzing historical and real time data and then putting that data to use in a predictive manner that can help you fulfill the various business goals you need to complete. One vertical in which predictive analytics can impact your business in a major way is security. If your company doesn’t focus as much attention on security as you think it should, then you’re not alone. Most executive level members of a company will defer to the CIO when it comes to matters of security (and in worst case scenarios, the CIO will defer to his/her managers), but the reality is that security should be on the forefront of every company’s mind—no matter how big or small that company is. Just one look at a 2012 chart from Price Waterhouse Cooper’s (PWC) show’s how important security is to a company’s scalability.
These statistics are sobering to say the least, but the good news is that predictive analytics can help sure up your company on all fronts should any kind of attack occur. To begin with, a predictive analytics tool such as IBM Watson will allow you to mine the millions or billions of data points that your company collects from online transactions to surveys questionnaires to emails.
Why would this be important to security? Say you’re an online publication like Forbes or Business Insider. You would rely on people giving you their information so that they can be updated via email on the newest content that your publication has to offer, right? Let’s also say that your email marketing system gets hacked and sends out spam to all of your subscribers. Your value—in the consumer’s eyes—immediately drops, and so do your subscription rates.
It’s no longer tenable to wait for a malware attack to hit your company, fix the problem internally after it happens, and then send an apology to those affected. And it’s in the area of security, in particular, where a predictive analytics software system can really earn its salt. By having the power to analyze old data such as user information you can spot where security breaches have happened in the past and put that information to use in stopping future attacks. Essentially a good predictive analytic tool will allow you to constantly monitor you business’s digital environment while staying ahead of the curve in terms of when the next attack will happen.
Moving on to a much sexier topic than security, talent acquisition is always going to be a vertical that businesses need to do their due diligence on—otherwise, strong companies can take a hit by hiring the wrong people. Another look at a PWC report from 2012 states that, “Rising external recruitment [due to an improving market] appears to be placing a burden on the hiring process, evident in a decrease in quality of hire.” In other words, with the economy on the rise, companies are recruiting outside talent in order to increase the head count of people who work for them—the only problem is that with an uptick in new hires also comes with a down swing in quality of hires.
Simply put, having the cash flow to hire new talent shouldn’t also lead to a spike in hiring the wrong people, and companies that are big enough to invest in predictive analytics could see their money put to good use in terms of employee retention. Just as with every other vertical that you put a predictive analytics platform to work on, you can also use predictive analytics software to create a data framework that highlights a road map of which hires will have the best future results.
For example, you can begin by linking the hiring process to current employee information such as performance, engagement survey info, and other data points that are relevant to employee life cycle, and in doing so, you can more accurately predict which hires will have more long term success before you hire them. What’s more, if your company relies on 3rd party recruiters you can link a recruiting firm’s success in a similar way to how you would link individual candidates to your company’s employee data framework. This will help predict which firm will offer the best results, and which is a waste of time and money. At the end of the day implementing predictive analytics into your hiring process won’t take the place of person to person interactions, but it will certainly help you streamline your efforts so that you can more easily focus on prime candidates, and hire them more quickly.
Much like with a good Business Intelligence Tool, predictive analytics can help any company up its social media game. Your business’s marketing team knows what it means to think on the fly, and with the proliferation of social media, marketers across the world can have a field day when it comes to trying out new initiatives, as well as exploring new channels for promotion. But with all that freedom also comes to burden of competition. Today’s marketer has a virtually unlimited number of ways to reach potential customers, but because the playing field is so wide open, the competition to get your name out there is fiercer than ever—and one thing you can’t afford to be with your marketing spend is inefficient.
So where do you begin when it comes to implementing predictive analytics into your social media strategy? To start, just like with every other aspect of predictive analytics, mining old and current data statistics is key to creating a predictive framework. Only with social media—instead of figuring out which candidate is a good hire, or identifying where there are weaknesses in your security system—predictive analytics can help you identify quality leads that are likely to convert, as well as help you understand the types of stories they want your company to promote.
The most on the ball companies tend to identify and participate in social discussions where a good number of likely constituents are already discussing topics that matter to their conversion goals. This could come in the form of posting your blog updates to Facebook in order to build awareness about, say, your ad-marketing software. It could also come in the form of contributing informative Tweets to on-going conversations such as #marketing. But, in a marketing world that’s constantly shifting at the speed of real time, how do you determine where quality leads are presently? What’s more, how can you efficiently create collateral that’s proven to be effective in getting people to engage with you?
Predictive analytics tools essentially tie together disparate pieces of information provided by social media users, and puts that into a roadmap for how marketers can best engage with people likely to convert. For example, let’s say, for the sake of argument, that you’ve just started a new fast food chain and your key competitors are McDonalds and Burger King. A Predictive Analytics tool would help you pull all the conversations that are currently happening around those companies in order to help you (1) identify constituents who already enjoy talking about fast food, and (2) it can give you a clear view of the types of offerings you can give these constituents to buy from you.
Examples of BI Dashboards
With the proliferation of BI (Business Intelligence) tech it should come as no surprise that many different industries now rely on building competitive BI dashboards to stay relevant and drive growth. From Education to Retail to Manufacturing BI technology is now an everyday part of the business milieu. And because every industry’s BI needs are so different, we thought we’d highlight what and ideal dashboard looks like for three different industries.
It’s hard to imagine a market space that has changed more in the past decade or so than retail has. With the rise of digital marketing and social shopping experiences, the old way of shopping retail has irrevocably changed. In days past the path to evangelizing a customer looked somewhat like this: a new customer walks into your store because they’ve heard of you through word of mouth, you treat them well, and, hopefully, they convert.
Today, however, people are optimizing their time by shopping online more and are sharing their experiences via social media. What’s more, brick and mortar locations are beginning to match the digital experience of their online E-Commerce fronts by adding in store technology that adds to the customer’s overall shopping experience. There’s a trade off though that comes with transitioning from face to face interactions to more technological interactions, and that tradeoff is that customer data becomes much more abundant, while also becoming much more convoluted.
In order for retail companies to keep up with the constantly changing industry they need to be able to diversify their sales channels, but with diversification comes the added burden of keeping track of how various channels are adding to the overall development of a given company. It is for this reason that BI dashboards are becoming an industry standard for the retail industry. Let’s take a look at the snap shot below in order to get a better read on how BI dashboards can be implemented in a retail setting:
The above example clearly shows relevant KPI’s such as new stores that have opened within the past year, total sales (both overall and in new stores only), total number of stores, a graph comparing the previous year’s sales, and sales per sq feet. The overall result is a high level look at the overall health of this particular company’s brick and mortar output. By being able to drill down into relevant channels such as the dollar amounts of sales per new store location, managers are given a better view at what’s working and what’s not working on a store by store basis.
This can help a company decide what needs to be done to increase customer loyalty for the stores that have just opened, and it can also be used to optimize profit margins by increasing the company’s understanding of product demand per unique location.
The standard college admissions office might seem like an unlikely place for a BI dashboard to take up residence, but apparently, according to EdTech Magazine, BI software has been used by higher education since the late 1990’s to help fine tune college admission selections. As we all know, it’s extremely important to colleges that they identify which students will thrive on their campuses, and which ones won’t. In that regard colleges and universities aren’t so different from businesses who need to identify which leads are qualified, and which aren’t.
For example, if a B2B company were to spend time, money, and energy, courting another company that’s not an ideal partner (or simply one that has no interest in converting) that would pretty much be the business equivalent of beating your head against a wall. Likewise college campuses can’t spend time, money, and energy, accepting students on a whim. If that were to happen student dropout rates would increase, university prestige would plummet, and the cost effectiveness in acquiring new students would skew badly. Let’s take a quick look at the following dashboard example to see how BI can be implemented in higher education.
As you can see the above dashboard shows the University of East London’s current acceptance offerings broken down by Unconditional Offer, Conditional Offer, No Decision, and Reject. This easily allows the University to compare the current year’s acceptance numbers with last years, and that data can be cross referenced with other disparate data including retention data, student details, and awards information. Gathering all this information can then allow the school to become better at predicting how many students it should accept on a yearly basis as well as which students are more than likely to be ideal students.
All companies in all different types of industries need a quality return on information to thrive. If you rely on improper data your next move towards driving growth can essentially boil down into taking a shot in the dark. What separates the manufacturing industry from other industries, however, is that manufacturing companies rely on an extensive network of suppliers and customers to meet demands—and the more extensive the network, the more important it is to keep track of and capture data. From the amount of raw materials your business owns, to tracking your supply managers’ effectiveness, to evaluating the consumer market, the data trail grows and grows, and it’s due to the sheer extent of data that the typical manufacturing business generates that BI tech has become an industry standard.
Add in the fact that manufacturing businesses across the board are currently faced with intensifying global competition, and it becomes clear why manufacturing companies need information management solutions that allow them to make better business decisions. Let’s take a look at our final example and break down the important points.
The filters that this BI dashboard is looking at breaks down into four buckets: Passed Vs. Rejected Inspections of the supplier’s raw material; a breakdown of this same information over time; a graph that details product defects; and the overall supplier product statistics.
If you’re not in the manufacturing business the above graphs may be a bit confusing, but that only highlights why BI software is such a crucial tool for any business in the manufacturing industry. If you’re in the Manufacturing industry and contemplating acquiring a BI dashboard we suggest you keep the following in mind:
Any BI software should first help improve operations by giving you a detailed look of current sales and operations plans.
Good BI software should also allow you to target areas where you can reduce costs, risks, and maintenance issues.
And finally you should be able to achieve visibility across many business verticals from one window. Any BI software tool will allow a certain amount of customizability when it comes to adding and removing filters, but before choosing a vendor make sure that you’re able to easily achieve cross functional visibility into disparate business operations.
At its core BI software is meant to offer even the least technical users with a road map to where improvements can be made, and how to maximize company growth. And, while we’ve only detailed three different industries that can benefit from implementing BI tools into their business there are any number of industries that can benefit from implementing some of the same software developments into their own workflows.