In the first post in this series, I examined the underlying trends driving the buzz around big data and its relevance for SMBs. In the second, I discussed how three IBM business partners (FYI Solutions, LPA Systems, Inc. and Waypoint Consulting) are helping SMBs take a pragmatic approach to successfully apply analytics and big data solutions to solve business problems.
In this third and final post, I’ll talk about how to determine business readiness for big data solutions, and considerations to keep in mind as you help your business move ahead in this area.
Big Data Readiness
Today, even small companies are generating and accumulating staggering amounts of data. The question is, can you turn this data into reliable, accessible and actionable information that you can apply to solve business problems and make better decisions?
Many SMBs rely on Microsoft Excel to generate information and reports. If you’re in this category, you can get ahead simply by taking advantage of analytics tools built into the financials, HR, CRM and other core systems that you use. Taking it a bit further, combining Google Analytics data from your website with CRM data can offer you fresh insights about who’s coming to your website, from where, and what they’re doing when they get there.
But as business complexity grows, data and reports are spread across more databases, spreadsheets and applications, and stored on servers, personal computers, mobile devices and in the cloud grows as well. Using disparate data sources and tools to answer key questions such as “what products can I price at a premium” and “what are the best ways to increase repeat sales?” becomes difficult, time-consuming and burdened with inconsistencies.
“When customers approach us, the top reason is because they don’t trust their data and reports. Too time-consuming always comes up as well. They are also struggling to get an enterprise-wide view of their data,” according to Joe Rodriguez, Software Practice Leader, FYI Solutions.
If you answer yes to the questions in Figure 1, your business probably needs to integrate key data sources into a central repository. As Brendan McGuire, Managing Partner, Waypoint Consulting puts it, “You need to pull data from the cloud and on-premise applications into an integrated, rationalized data store. You can do this on your own systems, or you can do it in the cloud in a subscription model.”
Figure 1: Big Data Readiness–Key Questions to Ask
With a core foundation of common, trustworthy and accessible data in place, you’ll be able to get deeper insights into operations and customer behaviors and preferences. Companies typically start out with “descriptive” business intelligence (BI) tools to dig in and get more visibility into key metrics such as those noted in Figure 1, and make better decisions. For instance, if you’re a retailer, these tools can provide analysis to pinpoint optimal locations for new stores, more accurately forecast customer demand, minimize inventory or negotiate better pricing from suppliers.
Moving Up the Curve
Until recently, having solid analytics capabilities for internal, structured data was enough to give many businesses an edge. But, with more data and different kinds of data pouring in from more places, companies are looking for new ways to help them access, analyze and use data to gain market and competitive advantages.
In broad-brush strokes, big data helps do this in two ways. First, big data technologies crunch through both structured and unstructured data exponentially faster than was ever possible before. Examples of technologies that enable this super-charged data crunching power include hardware with increased memory and parallel processing capabilities, and Hadoop and MapReduce, which harness the power of multiple, distribute computers for problem solving.
Using this kind of technology, you can run analyses that used to take days or weeks in minutes. This make it possible to analyze data that you may have collected for years, but were never able to analyze before, or to weave new, external data sources into your analysis.
In addition, new kinds of analytics tools and solutions make it easier to explore data in more accessible, actionable ways, including:
- Mobile business intelligence. Nowadays decision-making is as likely to happen in an airport or at a customer site as in headquarters. Mobile solutions let users see, share, report, and analyze data on smartphones and tablets. They take advantage of native, user-friendly mobile interfaces, such as touch screens, and give users the ability to make smarter, faster decisions regardless of location.
- Visualization. You may be able to look at a hundred of rows of data and make sense of it, but can you look at thousands of rows and figurer out what’s going on? Visualization solutions help people to see what’s happening across hundreds of thousands of data points quickly and easily.
- Sentiment analysis. Social media and digital sites have given customers and potential customers a much bigger and louder voice. Sure, you can easily tell how many followers or fans you have, but do you really know what it means to your business? Sentiment analysis identifies the user attitudes towards a brand, product or event by using variables such as context, tone and emotion.
- Predictive analytics. Using mathematical algorithms, predictive analytics helps you to spot what’s likely to happen next. With predictive tools, you can examine large amounts of historical data (internal and external, structured and unstructured) to identify hidden patterns to alert you to future trends and stay ahead of the market.
- Prescriptive analytics take things a step further, actually guiding you to a course of action, via options for what you should do next. Prescriptive analytics solutions can fine-tune themselves as they take in new data to continually improve your decision alternatives.
Choosing Your Big Data Path
Where you go next depends on where you are today, and your business goals, as discussed in Putting Big Data To Work For SMBs. Often, explains Brendan McGuire, “the greatest opportunity is to make data more consumable…making it easier for the business person to have conversations with the data, whether its structured or unstructured, through better mobile solutions, or visualization.”
Meanwhile, LPA Systems is helping hotel chains use forecasting and planning solutions to get a better idea of expected occupancy rates based on historical transactional data mixed with external information about upcoming events and other factors to optimize pricing and marketing initiatives. As Jesse McNulty explains, “Now they can better assess if they’re going to be overbooked on a weekday in July, and charge more, or if they’re going to have occupancy issues, and need to do a promotion”.
Although prescriptive analytics is still further out on the horizon for most companies, Joe Rodriguez sees customer interest in this area growing. “Just like your GPS provides you with alternate routes, tells you where to go, and what turns to make in your car, prescriptive analytics can be like a crystal ball to help predict outcomes and improve decision-making for the business.”
As revealed in the IBM Institute for Business Value and Said Business School, University of Oxford, three out of five midmarket respondents report that analytics, information and big data solutions “create a competitive advantage in their industry,” representing a 66% increase since 2010. Given the rapid rate and pace of change in business and technology, this gap will widen.
While turning information into insights isn’t easy, the good news is that vendors are increasingly recognizing that big data isn’t only for big businesses. Whether you are just starting to think about the relevance of big data for you business, or you have some of the basics in place, more vendors, including IBM, are focusing on SMB customers. Not only are they building more solutions tailored to SMB requirements, they are also developing educational materials to help you learn how more about applying big data solutions to real world business problems. As important, they are growing and training their business partners to help you get up the learning curve, implement solutions and optimize the value you gain from them.
So do your homework. Assess your company’s key challenges, we’re you’re at today, and were you want to go. Talk to colleagues and business advisors you trust. Start developing a strategy to get the wisdom you need to grow your business and stay ahead of the competition.
This is the final post in this blog series by SMB Group and sponsored by IBM that examines big data and its implications for SMBs. The first post, Is Big Data Relevant for SMBs? parses through the underlying trends and hype surrounding big data, and what is important and relevant for SMBs. The second, Putting Big Data To Work For SMBs looks at how IBM business partners are helping SMBs take practical steps to put big data to work for their businesses.