Archive for category information management
While the buzz in the big data market is around massive amounts of data and what you can do with that data, in truth companies are more interested in the small stuff. Let me explain. One of the greatest benefits of getting hold of lots of data is that a company can see patterns and anomalies that would have gone undetected with a smaller set of data.
Companies are interested in big data not so much because of what that data represents in terms of volume, variety and velocity, but what the analysis of that data can do for the business. As business decision makers begin to recognize the potential of big data, they realize that the biggest insights and hidden gems of knowledge are found when big data actually becomes quite small. However, the analysis must start with very large volumes of data. Exploring the world of big data takes business leaders beyond the data found in their organization’s traditional databases. Researchers, data scientists, and marketers, are analyzing very large volumes of unstructured data from previously untapped sources such as e-mails, customer service records, sensor data, and security logs.
Now that companies have the ability to deal with so much more data, they are free to incorporate a greater variety of data into the mix. For example, they are incorporating social media, mobile phone location, traffic, and weather data into more traditional analysis. But what is the goal? Add more data and more elements so that those patterns emerge. Armed with the insight from analysis, business leaders can take a more precise set of data and compare it to data from a data warehouse or a system of record. As a result, the research becomes more targeted and directed to fit in with the context of the business.
Why do companies need to take this targeted approach to leveraging big data? In essence, companies want to use big data analysis to make a personalized offer that is just right for the customer when that customer is ready to buy. In some cases, the answer may be related not to selling but to diagnosing problems with a manufacturing system or a patient with an unexplained illness.
How do you move from big data analysis to small data insights and personalized action? You need to consider three elements: defining your business problem, defining and analyzing your data sources, and integrating and incorporating your big data analysis with your operational data.
Defining your business problem. Companies are beginning to ask the traditional questions about customers, products, and partners in new ways. For example, are you looking to manage your customer interactions armed with in-depth and customized knowledge about each individual customer? Companies with a focus on driving continuous improvement in customer service are asking, “How can I delight this customer and anticipate their specific needs?” These are important goals for businesses competing in today’s fast-paced, mobile-driven market.
Defining and analyzing your data sources. What information do you need to make the right offer to your buyer when he deciding on a purchase? What information can you glean from outside sources such as social media data? What big data sources do you have available internally that were previously underutilized? For example, can you use text analytics to gain new insight about customers from call center notes, emails, and voice recordings? One important goal with big data analytics is to look for patterns and relationships that apply to your business and narrow down the data set based on business context. Your big data analysis will help you find the small treasures of information in your big data.
Integrating and incorporating the analysis of you big data with your operational data.
After your big data analysis is complete, you need an approach that will allow you to integrate or incorporate the results of your big data analysis into your business process and real-time business actions. This will require some adjustment to the conventional notion of data integration. In order to bring your big data environments and enterprise data environments together, you will need to incorporate new methods of integration that support Hadoop and other nontraditional big data environments. In addition, if you want to incorporate the results of very fast streaming data into your business process, you will need advanced technology that enables you to make decisions in real-time.
Ultimately, if you want to make good decisions based on the results of your big data analysis you need to deliver information at the right time and with the right context. In order to make the results of your analysis actionable, you need to focus more on the small – targeted and personalized results of big data – than on the large data volumes.
You say you already have a plan in place to guard your company’s data? Are you sure it has you adequately protected? While you certainly understand the need for data security – your sales challenges are tough enough without exposing your customer’s credit card information to a security breech, for example – the chances are good that in 2010 you will consider various options for improving the security of your data. If you are going to protect your company’s most valuable asset — your data — you will begin to view data security as a component of a more comprehensive information governance strategy.
The risks of internal or external threats to your company’s data are becoming more complex as the depth and breadth of your information expands rapidly and your data is shared with business partners, suppliers, and customers. In addition, as companies begin to take advantage of cloud services for some of their workloads, additional complexity is added to the multitude of security concerns. Many companies have deployed a disjointed approach to securing, controlling, and managing its data making it hard to anticipate and prepare for constantly changing security risks. There are lots of different ways that unauthorized users may enter your network or otherwise steal your data. Many companies typically have a distinct solution to combat each one individually and typcially can’t each of themprotect against all of them and. For example, access control, data encryption, network traffic monitoring, vulnerability testing, and auditing may all be monitored with independent applications.
There is a good reason why many companies find they need to deploy lots of different solutions to effectively govern its information. Some of the most innovative solutions have come from emerging companies who have built a niche around a particular vertical market or some segment of the information security market. So you deploy the best solution for you biggest challenges and move on. However, as you begin to think more holistically about your needs for information governance, you will want to ensure that information security solutions are well integrated. This is one reason why emerging companies with an information security solution have become desirable acquisition candidates for larger software vendors.
Guardium, a privately-held company based in Massachusetts, is one of the most recent examples of this trend. When IBM announced its acquisition of the company in the last week of November, Guardium moved from a fast growing startup to one of the pillars of the IBM information governance strategy.The company’s technology helps clients with some of the most challenging issues around unauthorized access to critical data. Their solutions provide secure access to enterprise data – across many different database environments such as IBM, Oracle, Microsoft, Teradata and others. In addition, customers can reduce operational costs by automating regulatory compliance tasks. While many companies may have the ability to monitor one database at a time, Guardium brings added value by enabling companies with complex environments to monitor databases across their organization.
This acquisition aligns well with IBM’s strategy to provide customers with a well-integrated and comprehensive approach to information management. IBM has spent in the range of $12 Billion over the past five years to add software assets that will help companies to make more intelligent decisions and realize more business value from their information.
After just returning from IBM’s Information on Demand (IOD) Conference in Las Vegas, I would like to take this opportunity to virtually whisper just one word in the ear of a current day Benjamin Braddock, “analytics”. Many businesses have spent the past 25 years or so automating and streamlining business processes in order to drive improvements in efficiency and productivity. But now, it is becoming apparent that these businesses expect their future success will increasingly depend on how skillfully they manage, govern, and analyze information. Businesses are applying analytical techniques to business information to help reduce risk and increase the certainty that they are making the right decisions.
IBM has, in fact, spent $12 Billion in software investments (both organic multiple acquisitions like SPSS, Cognos, Filenet, iPhrase, and Ascential Software, just to name a few) over the past 4-5 years to ensure it will be able to support its customers in their quest to unlock the business value of information. In addition, in April of 2009 IBM announced a new organization comprised of 4000 consultants focused on advanced business analytics and business optimization – teams with skills in applying business intelligence technologies like mathematical modeling, simulation, data analytics, and optimization techniques.
In an era of intense competition, tight credit, and cost concerns across global and vertical markets, this focus on getting the most value from the information you have makes a lot of sense. Companies find they are processing more information than ever before, but less of this information is being accurately and adequately used. The quantity of available data that a business needs to manage and understand has skyrocketed along with the increase in instrumented and intelligent products. For example, RFID tags that are embedded in manufactured products, plants and animals generate an enormous amount of data in efforts to control inventories and improve security and safety. Trying to make decisions with inadequate, inaccurate, or untimely information is like driving a fast sports car down the highway with a very large blind spot impeding your view of the truck approaching on your side. You need to know about the obstacles that might appear in your pathway before you try to make a “real-time” correction and steer your car (or your business) of a cliff. So, students and business leaders alike please take note, I see some “analytics” in your future.
I attended the HP Analyst Meeting in Boston a few weeks ago and had several discussions with the business intelligence (BI) group. It is clear to me that HP is struggling to try to figure out the best way to sell in this type of down market. Obviously, this isn’t easy for anyone. HP’s approach to solving this problem for its BI, data warehousing, and analytics solutions was to create a BI solutions group consisting of consulting (based on the 2006 Knightsbridge acquisition) and technology (Neoview, an integrated hardware and software platform for enterprise data warehousing). One of the best articulations of the approach HP has adopted came from a discussion by a sales executive who is on the front lines of trying to convince customers to part with cash. What struck me was the coordinated effort that was necessary to sell to a large global organization with huge data management challenges. This got me thinking about what it takes to sell in a very tough market.
To be successful, this sales person went all out. The Neoview product team and BI consultants all pulled to together to provide the right solution for the customer. Over the course of about ten weeks they conducted at least 100 interviews with the company to build strategy, roadmaps, and ROI estimates. The team worked with the customer to create a master plan that showed how HP could help the company with its goal of transforming its business.
The HP sales team leveraged many different resources to make sure they had an excellent understanding of the customer’s needs and that the company understood how HP could help. HP made sure to get executive sponsors in key leadership positions at the customer organization. They also brought in some of HP’s top thought leaders and made sure that happy customers were available to discuss their experiences. In addition, HP leveraged its partner network (including Ab Initio, SAS, and SAP Business Objects) to provide a complete solution.
Neoview was a good fit for the customer’s data management challenges. Problems with inconsistent customer information and disconnected IT systems were so hard to manage that it was becoming impossible for IT to adequately support the business. This customer’s top priorities were to regain control of its existing analytics data store and revamp enterprise customer intelligence and enterprise risk management. They liked the way Neoview was built. It is based on HP’s NonStop engineering expertise that has been used for over 30 years in industries such as financial services (stock exchanges) and telecommunication (switching) where the management of vast amounts of data is essential. Neoview is designed to support hundreds of terabytes of data and over one thousand processors. The customer also had some concerns about issues like getting its team up to speed on the product. HP stepped up to meet their concern by offering training and help with Neoview’s operation to ensure a smooth transition..
As I stepped back from this discussion, it occurred to me that successful technology sales in this type of complex market is incredibly challenging. It is simply not enough to make an announcement and hope for the best. On the one hand, the ingredients for a successful sale sound pretty simple – you need to understand the customer’s pain and provide the right solution at the right price. Easy? Try telling that to a team that just implemented a full-scale, coordinated sales push, made all the right moves, and beat out formidable competitors to win the sale. It’s not so easy, particularly with a complicated IT solution in a market where the business demands fast and cost effective results.And, if it takes such a coordinated effort to win one sale, how realistic is it to expect to sustain these efforts over the long term?
There are three main requirements for selling IT products and solutions in today’s market:
Get the basics right.You need to provide good technology at the right price. Your marketing plan needs to be based on clear and concise messages and your sales team needs to be able to articulate those messages in a way that is just right for your customer. This sounds like a good plan in any market. The difference today is that you can’t count on some of the sales that might previously have been considered “low-hanging fruit”. For example, assume you are preparing a proof-of-concept for a prospective customer and several of this company’s developers know you and your product from their work at other companies. Although it is helpful to have strong supporters of your product on the prospect’s IT team, their support can not overcome a product or solution that doesn’t solve real business problems. Today, the business is demanding more from IT – more business value, more trusted data, more control over costs, and more control over project time lines.
Understand your customer’s needs. You need to understand your customer’s challenges and expectations in order to make sure your product/solution is a good fit One of the most common mistakes that software product marketing teams make when preparing marketing materials is to focus on the outstanding and differentiating features of their product from a product-centric instead of a customer-centric point of view. You need to understand what problem you are solving for your customer and how your solution will solve this problem faster-cheaper-or with more flexibility for future changes than your competitors products. An understand of customer needs should happen at two levels. First, it helps to look at customers in a vertical market so your solution and marketing strategy account for industry specific complexities and challenges. Second, you need to understand the requirements of the prospect at hand -within the context of its industry as well as unique situations such as a recent acquisition or internal changes that may impact their sales decision.
Develop a coordinated and well organized approach. The difference between a good sales effort and a great one is in the way internal teams and business partners collaborate to put knowledge about customer needs and product/solution capabilities together to find the right fit for the customer. For many software vendors, the services or consulting team (internal team or external partnership) has a large role to play to help close the deal. For example, regulatory requirements in industries such as health care and financial services industries are continuing to change making significant demands on IT environments for companies in these industries. Although, you may have a great solution for handling vast amounts of data and improving data security and governance, you may not have the opportunity to prove it to your prospect without a coordinated sales effort. By bringing your product and sales teams together with a consulting team with deep experience in the regulatory and data requirements for health care and financial services you will be better equipped to show the business value of your solution.
As you try to finalize your deal, it often comes down to very similar issues across different types of customers. They are all looking for quick, inexpensive fixes to hard problems! The reality is that there are no easy solutions to closing deals in this economy. Understanding what the customer needs is hard, but what is even harder is making all of this scalable.