Business Intelligence - top 5 trends

Pervasive Business Intelligence and Data Democracy

In a recent survey, Information Week found that for businesses that had adopted a BI tool, only 25% of employees in those businesses had access to that tool. Expect this trend to change over the course of the next few years as organizations begin adopting cloud and mobile BI dashboards. Certainly in some respects, traditional BI tools have been too bulky and technical for that other 75% of employees to use, rather than being a case of not needing that information.

The common thread throughout the trends listed here is the idea that business intelligence is heading towards simpler, more straightforward methods and tools. The way organizations are using BI tools is changing to provide people throughout the organization with access to KPIs (key performance indicators), not just limiting it to end of month meetings in a boardroom. And that's a good thing, because every job has some degree of decision making associated with it. Consider the warehouse worker wasting time looking for an out of stock item when they could simply check their KPI dashboard and save time and money

Operational or Tactical Business Intelligence

According to Gartner, operational or tactical business intelligence (BI) is growing at a rate of 13% CAGR. That's an impressive number, especially when one considers that analytical or traditional BI tools are growing at a rate of 9% CAGR. This is the result of tandem developments in BI over the last few years. Increased adoption of agile BI tools like cloud and mobile BI encourage individuals to access their KPI dashboards more often. Daily performance metrics — the ones more likely to fluctuate on an hourly basis — are much more relevant to mobile users because they can use that information in a constructive, actionable way. As mentioned above, pervasive BI is also influencing this shift towards operational BI, since analytical BI is more often used by decision makers like executives.

An operational dashboard works much like a car's dashboard. As you drive, you monitor metrics that indicate the current performance of your vehicle and make adjustments accordingly. When the speed-limit changes, you check your speedometer and slow down, or when you see you are out of gas you pull over and fill-up. Likewise, an operational dashboard allows you to make tactical decisions based on current performance, whether it is chasing a red-hot lead or ordering an out-of-stock product.

Simplicity and Self-Serve Business Intelligence

Self-serve business intelligence (BI) is about simplicity. In turn, simplicity is about accomplishing your goals without being completely taxed from the effort. The reason self-serve BI is so attractive — and why it is projected to increase throughout 2012 — is that it offers end-users the ability to apply their knowledge of what metrics and ratios matter, and share this expertise by building dashboards without IT support. As more organizations demand self-serve and user-friendly BI tools, vendors will need to continue (or start!) to work on putting non-technical users in the driver's seat of their BI dashboards.

One of the most frequently touted promises of providing simpler, more self-serve oriented BI tools is the dramatic reduction of IT involvement. Whether that goal is attainable or not is irrelevant. The important thing is that in attempting to reach that goal, BI tools will evolve to be more user-friendly and will encourage everyone to start monitoring important metrics and KPIs (see #5. Pervasive BI and Data Democracy).

Cloud Hosted Business Intelligence Solutions

Cloud deployed business intelligence (BI) tools are becoming more popular each passing year. As vendors continue to develop better tools, business units forge ahead and capitalize on the simplicity of deploying their BI tools in the cloud. According to a June 2011 survey by the BI Leadership Forum, more than one-third of organizations have a cloud-based BI tool. Even more telling, is that 65% of those organizations are planning to increase their use of cloud BI in the next 12 months. These statistics are a promising indicator of what many analysts and vendors have been predicting for the last few years — increased adoption of cloud-based BI solutions.

Throughout 2012, expect to see the adoption of cloud BI tools to be driven by a number of important factors. First, cloud-based solutions offer the advantage of being relatively simple and convenient to deploy. Second, cloud tools are more easily scalable to provide access to key performance indicators (KPIs) to everyone in your organization, no matter where they are or what device they are using. This in turn fuels pervasive BI and improves decision making across the organization. Lastly, continually improving security measures will put to rest any reservations businesses have with storing their sensitive data in the cloud.

Mobile Business Intelligence and Accessibility

Mobile business intelligence (BI) tools have long been touted as the future of BI and for good reason. In a revealing survey conducted by Gartner, it was found that by 2013 one-third of all BI usage will be on a mobile device, such as a smart-phone or tablet. This is a remarkable figure that points to another year where mobile BI adoption continues to chip away at desktop-only solutions. In part, the changing dynamic of many work-places is fueling adoption of mobile BI. This was reflected in a recent survey conducted by the Business Application Research Center, which found that while adoption is currently at about 8%, over the next 12 months 30% of respondents planned to deploy a mobile BI tool. Gartner is reporting mobile BI to be growing at a staggering 40% CAGR.

This trend is easy to tie in with the 4 preceding predictions in this article. Mobile BI is increasingly being seen as a tool for providing on-the-go workers with access to KPIs — imagine a warehouse worker knowing the exact amount of stock, or a sales rep able to monitor territorial performance while away from the office at a tradeshow. Operational BI and mobile tools synergize to create an environment where performance can be managed effectively and from any location. By necessity, organizations deploying and vendors developing mobile BI tools need to consider the implications of working in a remote environment. In other words, a traditional BI dashboard laden with juicy KPIs just doesn't translate from the desktop to a mobile phone in a way that is user friendly.5 trends for business intelligence in 2012

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Strategic Importance of Business Analytics and Business Intelligence determines BI Mission

At the most strategic level, companies need to determine how important BI is to their ability to execute their business strategy and effectively compete.  We can refer to this as the strategic importance of BI, which then determines the appropriate mission for BI.

A Clear BI Mission Provides Context for Business Intelligence and Business Analytics Strategy

Consider the example of a hypothetical packaged food company that makes and distributes thousands of products to hundreds of retail customers who operate thousands of stores across the country, and who operate in different distribution channels.  Further, end-consumer demand patterns are not completely visible to the manufacturer, making it difficult to optimize inventory, replenishment, and customer service.  All these moving parts create a complex business environment generating an incredible amount of transactional data.  

Making sense of all this information, through business intelligence and business analytics becomes strategically important, which is a motivation for the company to achieve at least competitive parity via Stage 3 BI and analytics capabilities.  Taking advantage of available research about best practices BI for the food/CPG industry, this company could then focus its strategy on delivering business intelligence and business analytics such as:

• Performance scorecards and dashboards
• Trade spending analytics
• Customer service analytics
• Inventory analytics
• Financial and cost analysis capabilities
• Supply chain and operations analytics
• Purchasing analytics

The link between strategic importance and business intelligence and business analytics strategy sets the stage for productive discussions within the executive suite.

A Clear BI Mission Builds Executive Buy-In and Momentum for Funding

Once executives understand how important business intelligence and business analytics are for successfully competing, and once they see that there is a rationale for a stated BI mission and strategy, they are much more likely to move beyond considering BI an “IT initiative” and embrace sponsorship. 

Absent a clear understanding of the strategic importance of BI, it is difficult to get business executives to move much past the lip service stage of BI – the stage where you hear such statements as “we know we need BI, but the time is not right.” Once they see that BI can make a difference in future profit streams, they are much more likely to fund BI at a level that is commensurate with its importance. 

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What is Business Analytics?

What is Business Analytics?

Simply put, business analytics – or “analytics” for short – is a term for data-based applications of quantitative analysis methods in use in businesses for decades. In the mid-1980s, I read “Quantitative Methods in Management,” which was written in 1977. There are dozens of books that apply various quantitative analysis, operations research and discrete mathematics methods to specific business domains, ranging from sophisticated customer segmentations and predictions of customer lifetime value to demand forecasting and supply chain optimization. So the field of analytics, per se, is not new. Rather, tried and true quantitative analysis methods have been implemented as packaged software applications that can be leveraged to build a wide range of company-specific analytical applications that address common business challenges.

Business Analytics and BI – What’s the Difference?

We define business intelligence as the use of business information (data) and business analyses to support business decisions in the context of core business processes that drive profit and performance.

BI has always been about analysis, and business analyses come in a wide range of types and uses, from simple analyses such as accounts receivable aging reports to the sophisticated anti-fraud analytics used by major credit card companies. Our focus for this article is on the BI subcategories advanced analytics and predictive analytics – which we will refer to as business analytics or analytics.

Business Analytics Opportunities

There are a large number of potential opportunities for leveraging analytics to create competitive advantage – and ultimately to drive profit improvement. Analytics can be used across organizations for such purposes as:

• Customer segmentation.
• Category management.
• Risk analysis.
• Inventory optimization.
• Demand forecasting.
• Sales trend analysis.
• Statistical process control.
• Cash flow forecasting.
• Market analysis.

Business analytics are essentially a toolkit that sophisticated business analysts can use to glean insight regarding a wide range of business decisions in different parts of companies – all with a goal of increasing revenues, reducing costs or both. And while these opportunities are many, so are the potential pitfalls.

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Business Intelligence and Business Analytics

In a world that’s awash in data, assembling the right information about customers and business conditions has never been more difficult. It’s a paradox that Jay Dittmann, vice president of marketing strategy at Hallmark Cards in Kansas City, Mo., knows all too well. Having 13 million loyalty program members who purchase thousands of different greeting cards and other items makes tracking trends a daunting proposition. “There are mountains of data to sift through and limits to our marketing budget,” he explains.

About two years ago, Hallmark deployed a business intelligence (BI) and business analytics (BA) initiative to better understand buying patterns at more than 3,000 Hallmark Gold Crown stores across the United States. The company wanted to better nurture its relationship with its frequent buyers and, through predictive modeling, determine how to market to various consumer segments during holidays and special occasions. As a result of this initiative, Hallmark has boosted sales, while also simplifying and improving the analytics process.

Business intelligence and business analytics aren’t new concepts. The idea of understanding the relationships between bits and bytes of data extends back to the late 1950s, and BI has been around in earnest since the late 1980s. However, today, the ability to aggregate, store, mine and analyze data can make or break an enterprise. As a result, BI and BA have emerged as core tools guiding decisions and strategies for areas as diverse as marketing, credit, research and development, customer care and inventory management.

In fact, BI and BA are evolving rapidly and meshing to meet business challenges and create new opportunities. Although nearly all Global 5000 organizations already use these tools, 35 percent of them fail to make insightful decisions about significant changes in business and market conditions, according to IT consulting firm Gartner. What’s more, the task isn’t getting any easier as data streams become more intertwined, and mashups and other Web 2.0 environments pull data from multiple sources.

The bottom line? “Business intelligence and business analytics are on the cusp of a major change,” observes Joseph Bugajski, senior analyst at Burton Group. “There is a shift toward providing deeper insight into business information. And there is a growing emphasis on better tools and putting more powerful and better software in the hands of business decision makers.”

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5 Strategies for Implementing Data Analytics in Hospitals

Since the advent of the Internet, people have been able to access a significant amount of information with the click of a computer mouse. As technology becomes more ingrained in healthcare delivery, providers are facing the quandary of how to glean useful information from the enormous amount of data available through electronic health records, computerized provider order entry and other databases. Steve Nitenson, RN, BSN, MS, MBA, PhD, adjunct professor at Golden Gate University, San Francisco, and senior healthcare solutions architect for Perficient Healthcare, shares five strategies hospitals can use to implement healthcare data analytics. 

Goals and challenges

"Healthcare analytics is the Holy Grail with respect to healthcare," Dr. Nitenson says. The conversion of loosely net patient data — data that is loosely associated with other data — into meaningful, actionable trends holds the promise of increased coordination of patient care, patient safety, quality of care and cost-efficiency for not only individual patients, but also for patient populations at large. Gathering and using meaningful information on patient populations is one of the major goals of accountable care organizations. "Part of the accountable care organization model requires the ability to analyze healthcare data," Dr. Nitenson says. However, turning patient data into usable information is challenging; furthermore, once healthcare providers can access the information, determining how to act upon it poses more problems.

Dr. Nitenson differentiates between data — the facts entered into a database — and information — the interpretation of the facts in a meaningful context. "Just because you have a lot of healthcare data doesn't mean you can do anything with it. It becomes mission critical, especially today with all changes occurring in healthcare, to get as much data converted into information that is actionable," he says. According to Dr. Nitenson, the healthcare industry is currently able to access 80 percent of available healthcare data and can convert only 20 percent of that data into meaningful information.

Strategies 

1. Establish a governance structure. Hospitals should set up a governance structure to manage implementation of healthcare data analytics capabilities. The CEO, CMO, CNO and CIO should all be involved, Dr. Nitenson says. The CMO and CNO need to communicate the kind of information they want to the CIO, who has the IT knowledge to conduct the actual implementation. "You need to have a governance structure [in which] the CIO takes the lead but has the [CMO and CNO] to always ensure that whatever he or she is doing is going to meet their needs," he says.

Hospitals should also consider partnering with a professional organization experienced in data analytics, Dr. Nitenson says. In this situation, the IT organization would develop analytics and the CIO would implement it with the support of the CEO and guidance of CMO and CNO. "[Providers'] business is delivering healthcare, not developing healthcare analytical data models for themselves," Dr. Nitenson says. He says the learning curve would be much steeper and the time to implementation longer if the providers try to create an analytical toolset on their own. "It's a major undertaking that takes time and a good deal of effort. [If providers do it on their own] it usually ends up on the back burner and never gets done." 

2. Define the desired information. Due to the large amount of healthcare data available to hospitals, from everything from lab data and physician notes to insurance claims to medical records, hospital leaders need to define what information they want. "You have to be able to filter what's really important to you based on the hospital and specialty [you're interested in]," Dr. Nitenson says. Leaders should also determine when they want the data, how they want it presented and who they will share it with.    

3. Format the data appropriately. One of the keys to analyzing healthcare data is presenting it in an appropriate format. For example, Dr. Nitenson says if the hospital wants to understand the lab data for someone whose blood is drawn twice a week for five weeks, simply looking at the 10 data points would not yield any useful information. "It's meaningless if there's no reference point," Dr. Nitenson says. Instead, the hospital would need to trend the data and benchmark it against the demographics of the region the hospital is located as well as national averages. 

4. Secure the information. Once hospitals have converted the healthcare data into meaningful and actionable information, they need to decide who to grant access to and establish security protocols to ensure access is available only to those individuals with "a need to know," Dr. Nitenson says. He adds that at this point, sharing healthcare data becomes an ethical question. "The more information you get, the higher order of ethical behavior one has to have." For example, he says exposing the information to insurance companies could have consequences for hospital reimbursement. Access to information does not have to be all or nothing, however. While patients should be able to obtain their own information, hospitals should consider what information might be inappropriate. "Some information may be deleterious to patients without understanding the context," he says. 

5. Share information effectively. Even if healthcare data has been converted to information and the information has been secured, data analytics cannot produce benefits of improved quality and reduced costs if the information is not shared effectively. Dr. Nitenson suggests using a "push" rather than a "pull" technique for sharing information with physicians and nurses. "Push the information to the professionals," he says. "Present it to them in their daily work. Don't [make] them try to find it." The difference between "push" and "pull" is similar to opt-out and opt-in systems. In a "push" environment, physicians would be automatically presented with information that they would have to consciously ignore or dismiss — or opt out of. In contrast, a "pull" environment would require physicians to find the information themselves, or opt in. The former method increases the likelihood that the healthcare professional will be aware of the information they can use to improve patient care.

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Do you need Business Intelligence?

It’s a classic question that has a classic answer – companies need to translate data into information in order to make strategic business decisions.

Companies continuously create data whether they store it in flat files, spreadsheets or databases.  This data is extremely valuable to your company.  It’s more than just a record of what was sold yesterday, last week or last month.  It should be used to look at sales trends in order to plan marketing campaigns or to decide what resources to allocate to specific sales teams.  It should be used to analyse market trends to ensure that your products are viable in today’s marketplace.  It should be used to plan for future expansion of your business.  It should be used to analyse customer behaviour.  The bottom line is that your data should be used to maximize revenue and increase profit.

All companies produce reports from the data they collect from their business activities.  Every manager has a manager who needs reports unless you’re the CEO in which case you just need reports.

Some important questions you need to ask are:

1. How much resources (i.e. people, time, dollars) does it take to produce these reports?

2. Am I sure that the data in these reports is accurate?

3. Am I concerned with the security of these reports?

4. Am I receiving these reports in a timely manner?

If the answers to these questions are too much, no, yes, and no then you need a Business Intelligence solution.

IT are the first people to begin the process of creating a report.  They need to extract the required data and pass it to the person creating the report.  That person then has to spend time manipulating the data to create the required report.  This process can take many hours, even days, of effort.  And this process needs to be carried out for each and every report that the company requires.

Business Intelligence solutions automate the process of extracting data and producing reports thereby eliminating all of the manual effort of IT and the people creating the reports from raw data.

A number of studies have been conducted on spreadsheet errors.  An often cited report, What We Know About Spreadsheet Errors by Raymond R.Panko of the University of Hawaii, concludes that “every study that has attempted to measure errors [in spreadsheets] has found them and has found them in abundance”.  If decisions are made based on inaccurate reports then these decisions are more than likely the wrong decisions.  This could lead to disastrous results for the company involved.

A Business Intelligence solution produces reports using data that has been automatically extracted from a cleansed data source (typically a database or data mart) to produce accurate reports.  In order to make important business decisions, for example, as to what new products to carry or what products to drop, it is vital that managers have accurate data in the reports on which they base these decisions.

Data security is a very real problem.  As soon as data is extracted to spreadsheets the potential for abuse is greatly increased.  Spreadsheets can be “lost”, private corporate and sensitive data can be copied onto a number of portable devices, and laptops can be stolen or misplaced.  Cases where private data is made public through negligence occur daily. Think Wiki.

Business Intelligence solutions take advantage of existing security infrastructures to keep private data secure and within the company.  Data within reports is typically presented to employees via the company’s intranet and employees are given access to only the data they require to carry out their specific job functions.

Without a Business Intelligence solution companies may have to resort to dumping vast amounts of data into spreadsheets from their databases.  This in itself is a manual and, in most cases, an extremely time- consuming task.  The spreadsheets then have to be delivered to the person creating the report.  Spreadsheets then have to be consolidated and the data manipulated manually to produce the desired reports.  All this takes time and the data within the reports may be days or weeks old by the time the reports are complete and delivered to the manager.

A Business Intelligence solution provides real-time reports directly to the manager on-demand from any location.  The data in these reports is typically as recent as the data in the data-source it is being extracted from which allows the manager to monitor the business in real-time.  The manager can then base decisions on what is happening now and not last week or even yesterday.

There is a reason that Business Intelligence continues to show up on CIOs’ priority list.  The amount of data being stored by companies is growing exponentially and it needs to be managed.  It needs to be secured and distributed efficiently to enable employees to make important up-to-date business decisions. CIO’s are beginning to understand the realities of this problem and are working to implement Business Intelligence solutions that fit their particular company’s requirements.

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Comparing self-service BI and traditional BI

When used successfully, self-service BI tools address one of the biggest frustrations users experience with traditional tools: the lag time between a request for a report or dashboard — or even a simple change to an existing report — and the response to that request from IT or the BI team.

“It’s not just that companies are short-handed on the BI IT side, but it’s also the fact that users increasingly want to do more things with data,” said James Kobielus, senior analyst at Forrester Research Inc. in Cambridge, Mass. Self-service BI is the “hottest segment of the BI market” among his client base, he said. It “gives users their own tools to pull data from source applications directly, or from an intermediary database that IT sets us for users.”

Data Analytics for Hospitals with Ideal Analytics

When IT is taken out of the report and dashboard development process, the BI process is more agile, meaning companies can put their insights into action faster, Kobielus said.

Self-service BI not only puts the power in the hands of the user, but also opens up new ways of analyzing data, Kobielus said. Many users have been exposed to visualization, reporting and modeling to a degree in Excel spreadsheets, but they haven’t been given easy access to predictive analytics tools and statistical modeling. “These self-service BI tools are embedding predictive modeling and statistical modeling in self-serve, highly user-friendly drag-and-drop user interfaces,” he said.

Of course, IT still does a lot of things behind the scenes, as Spott’s approach demonstrates — integrating data, developing templates and showing employees how to use self-service BI tools’ drag-and-drop wizard-driven interfaces.

For Spott, the power of self-service BI is not in its GUI — which he believes is pretty much the same across the available tools — but in how well it handles metadata to connect to multiple data sources. In his view, that is the biggest challenge for IT groups when they choose a data tool. “What I was looking for was a tool that could make dynamic connections on the back end to multiple data sources across multiple platforms,” he said. “That’s where the challenge usually comes in: being able to join different data sources simultaneously.”

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Top six BI trends for 2012

Gartner’s 2012 predictions for business intelligence focus on the challenges around Cloud, alignment with business metrics and a balanced organisational model between centralised and scattered. Forrester has looked toward 2012 with everything from the rise of individualised BI tools to Cloud to mobility to Big Data. At the recent Gartner BIIM Summit, industry panellists discussed issues such as BI spending under IT and finding the right people with BI skills.

There’s no doubt that 2012 will be an exciting time for business intelligence and information management. While there are many factors that will continue to influence and shape the industry—data quality, rising storage and network requirements, IT capabilities and business requirements—we’ve identified what we think are the top six BI trends for the year ahead.

BI in the Cloud

As Cloud computing continues to dominate the IT landscape, so too does the discussion of BI in the Cloud. Gartner is sceptical of Cloud BI take up, predicting that cloud offerings will make up just 3 per cent of BI revenue by 2013 as user adoption will lag far behind the expectations of vendors, according to CBR. In his top 10 BI predictions for 2012, Forrester analyst Boris Evelson believes that Cloud BI will continue to chip away at on-premises BI, but it’s still a long road ahead.

What we’re finding is that decision makers are still questioning the Cloud. The greatest challenge for organisations is the logistical issue of moving data into the Cloud initially. They need to look at the security network and bandwidth, the quality of the data they are transferring and planning to analyse and think about a usable interface.

Once data has been transferred to the Cloud, there are numerous cost-effective BI and big data tools available for organisations to take advantage of. CIOs need to approach discussions with management and the organisation with the benefits of BI in the Cloud and we should see an enthusiastic uptake.

Mobile BI

Forrester’s Evelson believes 2012 will see mobile BI go mainstream, based on the need to make decisions when and where they need to be made. We agree.

Mobile business intelligence offers huge advantages for Australian organisations, particularly those with increasingly mobile and remote workforces. It means that staff and management are never disconnected from the tools that help them make business decisions.

Mobile business applications have become a vital part of most organisations. The increase in maturity and adoption of mobile technology has created a workforce reliant upon instant access to information. Business intelligence is no exception.

For those that rely on business intelligence to make important decisions and define future direction, Mobile BI is a cost-effective and sensible addition to the organisation. Due to the ease of consumption, more C-level executives will see the value of better business decision making, more often, when and where they need it.

Analytics

Analytics is the next progression of modern BI. It uses algorithms to search for patterns and explanations. It looks at historical data to predict future activity for better business decision making. A recent MIT Sloan Management report found that organisations using analytics are more than twice as likely to substantially outperform their competitive peers.

Analytics will help companies differentiate themselves, it will allow them to run more efficiently, make the most of their customers and increase profitability. Analytics provides organisations with actionable intelligence. While BI has traditionally been hard to create a business case for, analytics has a direct correlation to an organisation’s top or bottom line.

Analytics has certainly already taken off, and we can only expect this area to continue to grow at a dramatic pace. The three biggest trends surrounding analytics the industry is likely to see are: Optimisation—the combination of business rules for optimised decision management; consumable analytics—the visual presentation of increasingly complex data; and new data analytics—the analysis of new types of data, such as social media, location information, etc.

It is important to bear in mind that, as with any business intelligence system, the companies reaping the rewards and gaining true value from analytics are the ones that have made a suitable investment, in particular establishing a stable, enterprise-grade solution.

In-memory analytics

As memory becomes cheaper, we’ll continue to witness the increasing popularity of in-memory analytics. In-memory analytics tools—such as Qlikview, Spofire and Tableau—allow for the querying and analysing of data from a computer’s RAM, resulting in quick and simple data exploration for BI and analytic applications.

Rather than relying on centrally controlled, monolithic data warehouses, users are able to download large amounts (up to 1 terabyte) of data onto their own computer and explore that information for proving theories and making business decisions throughout an organisation. Given the speed, ease and affordability with which these tools can put power back into the hands of the users, we are already seeing the adoption of in-memory analytics and can only believe its popularity will continue to grow at a similar pace.

As its popularity and adoption grows, however, it’s important to remember that ‘quick-fix’ and ‘short cut’ tools are no substitute for quality data. To ensure an organisation’s BI and analytics are accurate, in-memory analytics tools should be used in conjunction with a structured, quality data warehouse solution.

The Agile approach to BI

Those who work with us know that C3 Business Solutions is a huge supporter and advocate of the Agile development approach, and we’re currently witnessing its growth in popularity. An Agile approach can be used to incrementally remove operational costs and if deployed correctly, can return great benefits to any organisation.

Agile provides a streamlined framework for building business intelligence/data warehousing (BIDW) applications that regularly delivers faster results using just a quarter of the developer hours of a traditional waterfall approach. We’ve seen Agile cut project costs in half and drive project defect rates toward zero.

It leverages the 80/20 rule in many ways, such as allowing you to start a project after doing 20 per cent of the requirements and design that deliver 80 per cent of the project’s value. The remaining details are filled in once development is underway and everyone has a good look at what the challenges actually are.

Unlike the traditional waterfall methodology where planning is all done upfront, agile BI delivery folds 80 per cent of planning into the actual program deployment. This not only gets projects off the ground faster and gives the business results sooner, but yields much better requirements, so the effectiveness of the development team increases dramatically.

Big Data

Forrester analyst, Evelson, believes that 2012 will see Big Data start to move out of silos and into enterprise IT and that the IT department will start to learn how to live with it.

The way we see it, Big Data is set to change the information landscape and, for those who embrace it, will provide strong competitive advantage and insight previously impossible.

The major BI vendors are all announcing support for, or solutions using Big Data technology based on the most widely accepted tool, Hadoop. In Australia, National ICT Australia (NICTA) developed ‘Scoobi’, a productivity framework for the Hadoop big data storage and processing platform.

We expect to see banks take up Big Data technology in the coming months, alongside other organisations with truly enormous datasets in highly competitive markets such as telecommunications, government agencies and retail.

Successful business intelligence projects will need to consider Big Data as part of their data landscape for the value that it delivers. More and more organisations will look toward statistics and data mining to set strategic direction and gain greater insights to stay ahead of the pack.

Big Data will help organisations better manage risk and improve the customer experience, fundamentally changing the way information is managed and used.

We believe these six areas will converge and grow over the next few years. Organisations will embrace the Agile approach, utilising new tools and technologies to decrease delivery times and demonstrate substantial business value. As we put more data into the Cloud, big data will become standard, which will in turn drive more sophisticated analytics back out of the Cloud. Data itself will be delivered to satisfy the desires of users, so access from mobile devices will lead over desk-based consumption. This entire process is cyclical; as users become more demanding of their mobile interfaces, the process will start again, prompting more agile development, more data into the Cloud and more analysed data out of the Cloud.

The businesses that embrace these new business intelligence trends, and take steps to change and adapt the way data is hosted, analysed, utilised and delivered, will be the ones that grow and prosper in 2012 and well beyond. They are the ones to watch.

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Business Intelligence and Business Analytics, Big Time

In a world that’s awash in data, assembling the right information about customers and business conditions has never been more difficult. 

Business intelligence and business analytics aren’t new concepts. The idea of understanding the relationships between bits and bytes of data extends back to the late 1950s, and BI has been around in earnest since the late 1980s. However, today, the ability to aggregate, store, mine and analyze data can make or break an enterprise. As a result, BI and BA have emerged as core tools guiding decisions and strategies for areas as diverse as marketing, credit, research and development, customer care and inventory management.

In fact, BI and BA are evolving rapidly and meshing to meet business challenges and create new opportunities. Although nearly all Global 5000 organizations already use these tools, 35 percent of them fail to make insightful decisions about significant changes in business and market conditions, according to IT consulting firm Gartner. What’s more, the task isn’t getting any easier as data streams become more intertwined, and mashups and other Web 2.0 environments pull data from multiple sources.

The bottom line? “Business intelligence and business analytics are on the cusp of a major change,”. “There is a shift toward providing deeper insight into business information. And there is a growing emphasis on better tools and putting more powerful and better software in the hands of business decision makers.”

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What’s Driving Business Analytics?

Advances in analytic technologies and business intelligence are allowing CIOs to go big, go fast, go deep, go cheap and go mobile with business data.

Current trends center as much on tackling analytics challenges as they do on taking advantage of opportunities for new business insights. For example, technologies for managing and analyzing large, diverse data sets are arriving just as manyorganizations are drowning in data and struggling to make sense of it. Still, many of the cost and performance trends in advanced analytics mean companies can ask more complicated questions than ever before and deliver more useful information to help run their businesses.

In interviews, CIOs consistently identified five IT trends that are having an impact on how they deliver analytics: The rise of big data, technologies for faster processing, declining costs for IT commodities, proliferating mobile devices and social media. 

Technology Costs Less

Along with increases in computing capacity, analytics are benefiting from falling prices for memory and storage, along with Open Source software that provides an alternative to commercial products and puts competitive pressure on pricing.

Ternent is an Open-source evangelist. Prior to joining Island One, he was vice president of engineering for Pentaho, an Open-source business intelligence company, and worked as a consultant focusing on BI and Open Source. “To me, Open Source levels the playing field,” he says, because a mid-sized company such as Island One can use R, an Open-source application, instead of SAS for statistical analysis.

Once, Open-source tools were available only for basic reporting, he says, but now they offer the most advanced predictive analytics. “There is now an Open-source player across just about the entire continuum, which means there’s tooling available to whoever has the gumption to go and get it.”

HMS’ Nustad sees the changing economics of computing altering some basic architectural choices. For example, one of the traditional reasons for building data warehouses was to bring the data together on servers with the computing horsepower to process it. When computing power was scarcer than it is today, it was important to offload analytic workloads from operational systems to avoid degrading the performance of everyday workloads. Now, that’s not always the right choice, Nustad says.

“With hardware and storage so cheap today, you can afford to juice up those operational systems to handle a BI layer,” she says. By factoring out all the steps of moving, reformatting and loading data into the warehouse, analytics built directly on an operational application can often provide more immediate answers. Hackney observes, however, that although the price performance trends are helpful for managing costs, potential savings are often erased by increased demands for capacity. “It’s like running in place,” he says. While Hancock’s per unit cost for storage dropped by 2 to 3 percent this year, consumption was up 20 percent.

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When Users Hate Your CRM: What to Do

Most organizations try to take on too much, too quickly and without enough planning when they roll their CRM solution out.

Start with asking yourself (and others involved in key positions in the company) the question "If there was just one thing that we could do to improve our sales/ pipeline/ customer satisfaction, (or whichever area of the business needs focusing on).....What would it be?"

Keeping CRM simple is one of the great challenges because usually there are just so many things we want to fix in our business and we have no patience for waiting and working it.

Often a company will wait until the pain is so great before they embark on a CRM implementation, when there is a pent up need for fixing too many areas of the business. Even so, it's important that you focus on one to three things for the beginning phases of your new CRM.

I like to compare rolling out a CRM system to getting in shape: we simply want that slim, trim body and we don't want to work for it.

Putting all your energy (and that of your team) into the biggest and most problematic areas of the business to fix will give you the biggest return. And returns on investment are just what the CEO wants to see.

This applies to companies that have an existing CRM system that has fallen into disuse and desolation. Simply applying some focus around resolving "one thing" will re-energize the CRM within the company, giving the users something concrete to rely on ... and grow to love.

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10 CRM Buying Issues

It is important to remember that failure rates around CRM implementations range between 40% and 80%.

The fault tends to be with the company that is buying the software rather than the company that’s selling it. The three categories of mistakes include:

1. Driving CRM

Many companies fail to identify the reasons why they need a CRM in the first place. Many executives see the need for a CRM as a response to failures on their behalf in the business arena. The result is that business problems tend to get downplayed.

2. Technology and Adoption Rates

Companies often focus too much on the technology issues and not the business issues that need to be solved. However good the technology is, if it doesn’t map onto the business problem, there will be considerable user adoption problems after implementation.

3. CRM Goals

Failure to clearly define the goals of a CRM implementation means that the goalposts will often change over the course of the implementation and lead to a situation where the original set of problems have not been dealt with. Goals need to focus on immediate problems and near future problems. The objectives need to be nailed down.

By following these ten steps, Enterprises can not only expect to benefit from a successful CRM implementation, but also avoid the worst excesses of the identified problems.

STAGE ONE: Know Yourself

1. Look at Your Own Business

The first thing a company needs to do is to map processes. Companies need to know what processes are working and which ones aren’t, and which ones can be fixed by a CRM, and which ones can be dealt with without software of any kind.

The easiest place to start this is to examine the processes that aren’t working and see how changing those processes might fix a problem, but also affect other processes that may be already working. It is important to identify processes that are working to ensure that they are not negatively affected by changes made elsewhere.

Your CRM solution should map to the strengths and weaknesses of your organization. It should not demand that you alter your processes to suit it.

2. Human Resources

While executives and IT decisionmakers will clearly be involved in the decision process, enterprises should also make sure that before it is implemented, a representative of the people who will be using it should also be consulted.

Bucholtz argues that, in far too many cases, these people are not consulted, with the result that adoption rates are often not as high as might be hoped for. It’s also important to learn about any concerns, objectives and fears that could impede adoption down the line.

3. Regulatory Realities

CRM systems do not operate in a vacuum. CRM systems, like the majority of other software systems, operate using data. Enterprises need to consider their CRM in the context of compliance codes in the vertical they are operating.

4. CRM Budgets

There is in the CRM space now two ways of paying: Cloud, or on-premises. It has been the case until relatively recently that smaller companies that were less cash-rich would go for SaaS offerings, while larger companies were able to take a longer-term view and invest in on-premises offerings.

That appears to have changed now, though, with even larger companies heading for the cloud where it is feasible. SaaS subscriptions offer the benefit of pay-per-month where the CRM systems and its integration costs are handled as an operational expenditure.

In the same way, smaller companies in fields where regulation makes the cloud difficult or impossible to use need to go with on-premises solutions.

STAGE TWO: Know Your Requirements

5. Integration Requirements

Enterprises need to ask how deep and far down the CRM system will integrate. Will it be departmental, or will it be used to improve customer relationships right across your enterprise? Enterprises should also note the integration can be expensive and time-consuming. They also need to consider the complexity of the solution: If it’s too simple to integrate with existing systems, it’s not the system for you; if it’s too complex, the chances are it is not for you either.

6. Support

The level of support offered by vendors should be one of the make-or-break factors in your decision. It is likely that users are going to need support to get themselves trained and using the system. Support can be costly, so needs to be factored. There are also some vendors that are better than others and it is usually a good idea to note who is using what systems in the vertical you are operating in.

7. Vertical Markets

Are there CRM products tailored for the vertical that you are operating in, or are you in in industry that operates off unique kinds of data with a non-standard buying path? There are many industries with tailored CRMs, but it is also advisable to look at solutions that are horizontally targeted, as it may be that, with proper customization, they will work better for your company than vertically targeted offerings.

8. Feature Requirements

While features are important, all CRM systems should have the same basic features. After that, the rest can range from the interesting to the exotic and all with the same common aspect to them — they are never used. Enterprises need to ask the people who will be using the system what features will make their work more effective and life easier and choose a feature set based on this.

9. Financial

Having cut your list down to a manageable number, you need to look at the real costs. Remember you need to count in integration costs, upkeep costs or customization costs where needed.For on-premises applications, you need to add about 22% into the equation, while with SaaS you need to calculate recurring fees. You also need to cost the software over its life, and not just the initial startup costs.

10. Vendors

Once you have cut your list down further again, you need to assess whether your vendor has over-sold itself. Your enterprises need to do an independent assessment of track record and examine whether the chosen vendor will be in business next year, whether the product will still be about next year and whether you still are able to get support in the future.

Buying a CRM solution involves a complex series of decisions, but it also requires an intimate understanding of your own business, which in itself is a useful exercise. If you are interested in more on this, check out the full paper ; there’s a lot in it and its well worth a read before starting down the road to a CRM deployment.

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Assessing Custom CRM Solutions

When deciding on a custom CRM solution, it is important to know what you really need before you begin looking. Failure to do so may lead you down the wrong path, obscure the initial objective of your customer relationship management strategy, and cost you a lot of money. How do you prevent this from happening? It’s a matter of determining which areas of the business are lacking and which are successful but could be doing even better.

In general, a CRM solution is meant to provide a turnkey solution that you can switch on to improve the systems and operation of your business processes. After all, it is much more efficient and cost-effective to substitute human resources with computer systems if the two are comparable. CRM solutions can easily organize and arrange your information in a manner that humans cannot.

A good way to identify deficiencies in your business model is to analyze the individual business units separately (i.e. sales, marketing, customer support, operations, etc…). Doing so will allow to locate bottlenecks, holes, and areas in need of improvement. Subsequently, you can rank the business units in order of how much attention they need. As a rule of thumb, you want to target areas where the biggest ROI gains can be achieved in the shortest period of time. These are “quick wins” and a customer relationship management system can help you accomplish this. Secondly, you want to look at areas that may not be as vulnerable or weak, but do provide some opportunity and room for improvement. These will play into the longer term role of the CRM strategy.

Once you establish your priorities and rank your business units, it will quickly become clear how you will want your custom CRM solution to shape up. Bringing this research and due diligence to the table will till ultimately simplify the development planning and implementation. In the end, your custom CRM solution should streamline business processes, increase productivity, enhance loyalty, and… make you more money.

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Spectranet reinforces sales force and marketing campaign with installation of Sage CRM

Spectranet reinforces sales force and marketing campaign with installation of Sage CRM

Company now confident in achieving high rate of business growth with advantages of better lead generation and sales follow up

Sage India, a leading supplier of Enterprise Resource Planning (ERP), Customer Relationship Management (CRM) Solutions to medium and large organizations, has revealed that the successful implementation of Sage CRM across the operations of Spectranet, a leading Internet Service Provider in India offering private network convergence services. The implementation has given Spectranet new found confidence to achieve a higher business growth rate; driven in by CRM advantages like improved lead generation and sales follow up. This has led to the creation of a stronger sales team and the development of a more strategic marketing campaign.

According to Spectranet senior executives, the company was in search for a highly reliable sales force automation system accompanied by marketing management campaign system that would seamlessly integrate with other existing data systems. Also, Spectranet detailed a demand for a workflow based system, which in turn would provide the company’s operations with escalations and notifications based on criterions and time.

WoodApple, Sage’s India based implementing partner, recommended the use of Sage CRM, an easy-to-use, feature-rich, wireless and Internet-based suite of applications that provides enterprise-wide access to vital customer, partner and prospect information anytime, anywhere. Once implemented, Sage CRM would give Spectranet more control, choice and information than ever.

“When we were told about Sage CRM, we thought it was almost made for us,” said Sunando Bhattacharya, Head of Marketing & Business Technology, Spectranet. “We realized that Sage CRM is basically a web technology platform, which provides certain standard functionalities of sales force automation, marketing and customer support as default while the rest can be customized or built on the platform. This is what gave us the confidence that we can now able to have a single system as the interface to majority of our customer facing team and the other specialised applications can be in the back office talking to Sage CRM either to fetch or push data."

WoodApple supervised the installation and implementation of the Sage CRM solution suite, which comprised of a 178 user pack of Sage CRM and is currently using Activity Management, Lead Management and Opportunity Management modules. The implementation of the software suite includes key functionalities like leads processing, opportunity progress, campaign management and case logging / management. The installation process took nine months to complete, which included the need to fine tune the applications and integrations before starting the first trial run. The implementation was performed through phases, starting with sales and marketing and was later followed by customer support. As a result, Spectranet has reported an increase in both efficiency and productivity, followed by improved operations as driven in by the key automation of processes.

“Working with Spectranet, which is widely known as one of the leading internet service providers of India, was a real privilege for us. During the post-implementation process, we were able to get a better understanding of what they needed in their operations and how they could improve and at the same time, integrate key processes. Implementing Sage CRM not only gives them the advantage of being one step ahead of their competition but also consolidates their relationship with customers and partners,” said Debajit Roy, CEO, WoodApple UnikSolutionz.

“We are glad that Spectranet has expressed their satisfaction in using Sage CRM. Now equipped with a world class fully reliable CRM solution, one of India's leading ISPs has the advantage to keep a more integrated approach in collecting data. We applaud Spectranet's strategic move in taking a bold step towards automation and we are committed in helping them succeed by leveraging Sage CRM's broad suite of solutions across their operations,” concluded Vikram Suri, Managing Director for India & Middle East, Sage.

-ends-

About Sage Group:

Founded in 1981 in North East England, Sage Group PLC is a global company with 6.1 million customers, 13,500 employees and more than 25 years of experience working with small and medium sized businesses. It has built its success on understanding and meeting the needs of customers in their local markets, which has driven its growth as a world-leading provider of business management software and services. While its heritage is in the small business market, it also has the experience and expertise to meet the needs of specific industries and larger organisations. Its products and services are developed and supported locally, thereby ensuring their relevance to the customers and that they are supported by local experts.

For more information, please contact:

Debajit Roy

CEO, WoodApple UnikSolutionz

Bangalore, India

Tel: +91 80-42289006; 42289191-92

Mob: +91-9900093129

Email: deb@woodappleunik.com

Website: www.woodappleunik.com