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Lyndsay Wise

Hi and welcome to my blog! I look forward to bringing you weekly posts about what is happening in the world of BI, CDI and marketing performance management.

About the author >

Lyndsay is the President and Founder of WiseAnalytics, an independent analyst firm specializing in business intelligence, master data management and unstructured data. For†more than†seven years, she has assisted clients in business systems analysis, software selection and implementation of enterprise applications. Lyndsay conducts regular research studies, consults, writes articles and speaks about improving the value of business intelligence within organizations. She can be reached at

Editor's Note: More articles and resources†are available in Lyndsay's BeyeNETWORK†Expert†Channel. Be sure to visit today!

Looking at organization need

One of the most common concerns I hear from organizations is the ability to implement solutions quickly and gain value that can be sold as success to management. Many businesses evaluate how long a solution will take to implement along with the amount of time it takes to have it deployed and seen as a success by business users. For SMBs looking at BI offerings specifically, there has always been the challenge of weighing the benefits against the costs of deployment. Traditional solutions were seen to take many months to implement, and the level of value associated with implementations were not always easy to measure quantitatively. Luckily, the market has matured to the point that a variety of solutions exist which can be deployed in a timely fashion. But quick implementation times are only the beginning of defining value. Having any new software project up and running does not mean that its use is associated with or providing value to the people using the system. In order to truly be successful, organizations need both. 

Time to implement vs. time to value

Sometimes businesses confuse the terms time to implement and time to value. In most cases, IT will look at implementation as their main goal. Their responsibility being to develop and deliver solutions that are used by business users. Business users, on the other hand, want to take what is provided and make better decisions, address business problems, and maintain competitive edge – and do so right away. Both are important for BI and software project success.

Achieving both means making sure that expectations from both IT and business units can be met. It also means that organizations understand what those expectations should be. The IT development effort should be driven by business need. For instance, creating customer facing dashboards and analytics to let customers gain access to their data and plan better will be different than developing self-service data discovery dashboards to increase efficiencies in marketing spend.

SMB specifics

Small and mid-sized businesses are actually driven by time to value more than their enterprise counterparts. The reality for these businesses is that they have more to lose. Resource constraints and smaller budgets mean that SMBs have to get their project choices right and make sure that they can achieve value quickly. Otherwise they risk losing money and not being able to get back on track without major trade-offs. In many cases, I’ve seen expectations about both implementation times and achieving value not met because of IT resources working on multiple projects and not being able to plan accurately. At the same time, business users lack the understanding of the development efforts required and expect that their BI project will be looked at as the main priority.¬†

In order to avoid these risks, project stakeholders need to work as a team, define their goals, develop realistic expectations, and make sure that the value proposition of the solution(s) can be realized based on these aspects.

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I‚Äôve been compensated to contribute to this program, but the opinions expressed in this post are my own and don’t necessarily represent IBM’s positions, strategies or opinions.

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Posted June 22, 2014 9:56 PM
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This was my fourth year attending the Information Builders Summit and I generally come away feeling positive about the organization, its products and general direction. Normally new releases are announced and centre on some additional capabilities to the product suite. This year, Information Builders went a little bit further by showing a greater commitment to data discovery, broader integration with big data platforms, ESRI (location intelligence and mapping), and connectors to a wider variety of information management platforms. All of these announcements address three key market challenges:

  1. “Big data”: How to manage data complexities and develop platforms that are flexible enough to meet ¬†both market demands and an organization’s needs. With iWay, Information Builders provides connectors for all types of platform requirements. Organizations have the flexibility to select the right data warehouse, or develop the right data integration processes to support broader analytics. SAP Hana, Teradata, Cloudera, MapR, and NoSQL were some of the new adapters announced to provide that added flexibility and the opportunity for organizations to adopt technologies that support their business challenges.
  2. Data management integrity: Leveraging iWay provides Information Builders customers with the ability to manage data and ensure quality, validity, and reliability throughout the data lifecycle. This expands beyond selecting the right adapter and making sure that data can be viewed properly. It also involves the processes required to make sure that users trust the information they are accessing it and are able to get value from their data.
  3. Data discovery and exploration: Information Builders is starting to focus more on this area to provide broader interactivity for their customers, with new solutions coming to market this year. Data discovery, coupled with information integrity, is the future of BI interactivity and access. Although a little late to the game, because customers can leverage iWay capabilities as well, they may actually have an advantage in the long-term by ensuring that what is analyzed is valid. The ability to explore data and provide self-service BI access is only effective when the data can be guaranteed to be reliable.

All of these themes provides the basis for a strong analytics framework. Leveraging data, sustaining integrity, and providing access to analytics to all those who need it are the goals of this level of integration. In addition to those general themes, I also spent time speaking with current customers to get their insights. These were the most sited reasons for selecting Information Builders:

  • Privately held company
  • iWay enables organizations to manage their data more thoroughly without having to look for additional products through a “one-suite” approach (as opposed to looking at Informatica or other data integration products to move and manage information)
  • A continued feeling of partnership with Information Builders, even long after implementation
  • Easy to install upgrades

All customers were satisfied with their solutions. Some areas to take note of are:

  • Professional services (PS) expertise with version 8.0 as it is a new product and the PS staff is still getting up to speed. If using this approach, it is important to make sure that adequate support is available with the PS team onsite
  • What solutions ¬†to take advantage of that are not on the market yet, and what (if any) the implications of adding or switching products will be
  • The data warehouse platform to select – guidance may be required to make sure that an organization chooses the right offerings to complement their business and not simply because of brand recognition, etc.

Although I came away from Summit feeling positive about the product and customer value associated with adoption, this year it seems as if Information Builders is starting to expand their market offerings to provide additional value by integrating broader trends in adoption within their products.

Posted June 16, 2014 2:26 PM
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Business Intelligence has been a top priority for many CIOs and other project sponsors for years and most organizations perform some level of analytics on a daily, if not intra-daily basis. Many organizations, however, are looking for more up to date technologies or ways of bringing their BI use to the next level. This blog tends to address a lot of how to’s and steps for success. What it rarely talks about are some of the mistakes I’ve seen organizations make that end up turning the promise of BI into a failed project. So here are 5 things that I see regularly that cause organizations’ BI projects to fail:

  1. Lack of scope: Sometimes organizations know they want to implement BI but it is more of a directive based on an article read as opposed to a direct business need. When this happens, organizations can either identify the challenges within their business or simply look to implement a tool that will replace current reporting and spreadsheet use. Although, replacing older tools and spreadsheets can be a positive step towards building up organizational efficiencies, a lack of a business-focused scope can lead to project failure. A lack in project scope generally leads to failure because of a lack of adoption, poor development, or the inability to develop metrics tied to business pains.
  2. Trying to do too much too soon: This can be considered the opposite of not having a proper scope. Sometimes organizations try to do everything at once by including everything under the sun in their BI project scope. They want to address all needs in the organization with the same solution and expect that it is possible to do so with a single project plan and implementation. The reality is that a centralized BI approach is possible, however, it needs to be planned for. This means developing an iterative project plan to take into account the different phases of data acquisition, solution development, and rollout using an iterative approach. Additionally, even if using a centralized approach to BI development, rollouts need to be incremental in nature to assume small wins before moving forward. 
  3. Being unwilling to take the time to evaluate internal requirements against the market: Software selection tends to be a challenge for many organizations as the market is flooded with solutions that sound like they meet most business needs. The reality, however, can be different. Depending on the platform used, how information will be delivered, and what type of analytics required, different business challenges may need separate solutions. The reality is that researching the market is time consuming at the best of times and requires an understanding of product roadmaps, potential implementation hurdles, and capabilities, and match that to the business requirements of the organization. Additionally, this has to happen after the business and technical requirements have been gathered, making it a long process. Many want to skip this process, but in the end, taking the necessary steps can make the difference between selecting the right solution and having to conduct a new product search after implementation. 
  4. Bad project planning: BI is a project like any other that requires a strong project plan and management. Although most organizations have some project management in place, some are not prepared for the level of involvement it requires to build a BI solution. In most cases, failure ends up occurring when organizations try to do everything at once by bundling their BI implementations with other IT projects. Whether new Website builds, updating customer applications, or developing a new service, most BI projects need to be managed independently without having to compete with many other projects at the same time. Unless enough internal developers exist to manage all of these projects simultaneously, organizations need to make sure that their BI project can be managed from start to finish, with an understanding that additional support may be required. 

These are the top 4 that I see regularly, but are not an exhaustive list. Let me know what other mistakes you’ve seen in the market – whether from the prospective of organization, consultant, or implementer.¬†

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I‚Äôve been compensated to contribute to this program, but the opinions expressed in this post are my own and don’t necessarily represent IBM’s positions, strategies or opinions.

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Posted May 27, 2014 6:06 PM
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Organizations are constantly looking for ways to meet the needs of their customers. Better service, customized products, and price guarantees are just some ways that organizations try to ensure customer loyalty. For service and data providers, however, it is not always easy to provide added value beyond the service or data provided. The promise of more data and better visibility help ensure customer satisfaction by giving customers the tools they need to gain added insights. This gap has led to organizations providing analytics as part of their offerings to ensure that customers can access broader insights automatically without having to download data or change formats and apply their own business rules to gain deeper insight. 

Non-profit, education, and government are examples of industries that have posted demographics or other analytical data online for public consumption. When dealing with for-profit companies, most provide analytics in the guise of embedded analytics. What this means is that organizations develop applications that are embedded within their solutions that can be provided as a service to customers. This access to analytics helps provide customers with broader insights into their accounts, customers, trends, reporting needs, etc. In many cases, businesses add these additional reporting or analytics capabilities as an add-on to the services or information already provided.

For organizations considering this added level of analytics access, the first step is to understand end user requirements. What data is currently being looked at, where are their gaps in visibility, what information do customers need to give them that added advantage, and what needs to be done internally to make all of this happen. These questions represent the starting point. Luckily for organizations going this route, there are many solution providers that offer embedded BI as a key aspect of their offerings. Therefore, when organizations look at evaluating software vendors, one of the things they have to do is make sure that the capabilities they require are also provided within an embedded environment. 

Once software is selected, the process of acquisition and integration will mirror a traditional analytics implementation, with one key difference – the opportunity to monetize use. Organizations need to identify whether they will provide this new service at a premium, as pay per use, or develop some other cost model. Overall, organizations want to do more than justify their expenditures; they want to transform this new operating expense into revenue.

The ability to provide analytics to others as part of a new or added value service is one of the reasons more and more organizations are looking towards embedded analytics. Aside from added revenue, though, the reality is that as customer expectations grow and analytics become the norm, more and more businesses will start to take advantage of embedded analytics to be able to provide their customers with greater information visibility. Currently providing a level of competitive edge will no longer be the case when customers start to expect this level of insight into their data.

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I‚Äôve been compensated to contribute to this program, but the opinions expressed in this post are my own and don’t necessarily represent IBM’s positions, strategies or opinions.

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Posted May 22, 2014 12:31 PM
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The business intelligence market is diverse. Many organizations try to decipher which solution will work best in their environment but find it challenging because of the number of vendors and similar marketing campaigns. Although there is no easy way to simplify the BI landscape, decision makers can break out potential solutions based on their needs to identify which offerings are on target. It should be noted that some vendors fall into more than one category, while others are niche vendors that do one thing well. In the latter case, an organization may have to develop a piecemeal approach to make sure that all business and technical needs are addressed. 

The following are overviews of product categories based on business challenges being faced within organizations. Technical infrastructure and data management are also taken into account because any successful BI offering also requires the management of data assets:

  1. Reporting Рorganizations need reports and many still use standardized reporting solutions. Some BI vendors have reporting modules or specialize in reporting, while others are focused specifically on visualizations. 
  2. Dashboards – represent a big trend as they provide data representations and metrics in a visually interactive way. Many organizations like dashboards due to their highly interactive nature. Vendors offer varying levels of analytics within their dashboards. Some only visualize the data meaning that it needs to be stored with associated business rules separately, while others also offer analytical capabilities.
  3. Operational intelligence – some organizations require near real-time access to information. In these cases, operational intelligence becomes important so that relevant metrics can be updated on a regular basis with the flexibility to reflect the needs of the business. This means that different use cases will have different latency requirements.
  4. Advanced analytics – this is a broader category and could be divided further but for the purposes of this overview, it can remain a single category. A variety of analytics exist. Some organizations have complexities that require the management of many business rules and statistical algorithms while others want predictive and what if? capabilities. Certain solution providers provide targeted analytics while others are considered generalists – meaning they offer general capabilities but not many niche analytics.
  5. Data Warehousing – although some businesses are moving away from traditional data warehousing, the reality is that companies require a way to consolidate, centralize, and manage their analytical infrastructure. In some cases, a data warehouse is the most effective way. Even if it’s not, every organization evaluating BI should look at their data to identify how it needs to be managed.
  6. Data integration – helps transition data from one source to another. Within BI applications, it also serves as a transformation engine, can help provide quality control, and work towards providing a cohesive view of information assets both internal and external to the organization.

Some or all of these areas may apply when looking at advancing a BI initiative. The reality is that selecting the right solution means first getting the category right – selecting a reporting solution when advanced analytics are required will only lead to failure. Organizations need to be prepared to identify what their business and technical requirements are and how the market can best serve them – otherwise the risks for failure are too high.

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I‚Äôve been compensated to contribute to this program, but the opinions expressed in this post are my own and don’t necessarily represent IBM’s positions, strategies or opinions.

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Posted April 30, 2014 9:51 PM
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