Blog: Lyndsay Wise http://www.b-eye-network.com/blogs/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. Copyright 2014 Fri, 19 Sep 2014 13:32:56 -0700 http://www.movabletype.org/?v=4.261 http://blogs.law.harvard.edu/tech/rss Why are organizations still struggling with their data? This is a question I’ve been asking myself for a while. The data infrastructure exists to support Big Data, operational data streams, data quality practices, and the list goes on. Best practices exist for organizations to follow to achieve a strong information management framework and tie data to business processes enabling decision makers the ability to take actions on the insights they’ve gleaned. A variety of solutions exist in the market place providing BI access to any type of user and that are geared towards a strong IT infrastructure or small business with little to no internal IT support. Additionally, organizations understand the value their data brings to the table. Yet, many companies still struggle with silos of data, lack of visibility, the inability to consolidate information assets and develop the essential correlations between the data they need to drive strategic business value.

 Despite all of these facts, the answers are still elusive to me. Sometimes I think that nowadays project sponsors think data management should be easier than it is and cut corners to ensure quick implementation times without weighing the facts surrounding how this will affect time to value. I have seen it many times with organizations that don’t conduct in depth requirements gathering or identify how business and technical requirements are developed to work cohesively together. I have also seen organizations select products based on marketing hype and end up with a subset of the capabilities they require. Within SMBs, there is also a mistake whereby organizations don’t take into account the expertise they require to develop a strong BI initiative and either do not want to invest in the right skill set or feel that the resources currently available can be used without the proper training.

All of these areas contribute to the confusion, but so does the market itself. There is very little that is available in the form of a series of best practices or guide that can be used on a broader level to guide organizations through the transition from traditional BI infrastructures and other traditional models towards agile solutions that help support organizations in this transition. After all, the complexities of data integration haven’t gone away despite the promise of automated processes, more APIs, and easier to use solutions. Luckily, as the market matures, businesses can start to benchmark against those with successful implementations. At the same time, it seems like an integrated approach to data management is still needed across the board to really help organizations support broader data management. Solutions are still piecemeal and full stacks are not always accessible.

Hopefully as the market continues to mature and as more organizations move towards an agile approach to their data management, there will be more success with data management as a whole. But this still requires better planning, knowledge of IT infrastructure options, and an understanding of the value data can bring to the organization if leveraged well.

This post was brought to you by IBM for Midsize Business and opinions are my own. To read more on this topic, visit  IBM’s Midsize Insider. Dedicated to providing businesses with expertise, solutions and tools that are specific to small and midsized companies, the Midsize Business program provides businesses with the materials and knowledge they need to become engines of a smarter planet.

 

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http://www.b-eye-network.com/blogs/wise/archives/2014/09/why_are_organizations_still_struggling_with_their.php http://www.b-eye-network.com/blogs/wise/archives/2014/09/why_are_organizations_still_struggling_with_their.php Fri, 19 Sep 2014 13:32:56 -0700
Leveraging information assets and the need for collaborative decision making The struggle between business units and IT seems to be a challenge that will never fully be solved within some organizations. In a recent study by IBM Global Analytics, 79% of respondents stated that cohesion does exist between business and IT within the organization, while 50% said that most decisions were left to IT or individual departments. These responses highlight a disconnect between a collaborative approach to working and actual decision making. Additionally, 29% (click here to access the InfoGraphic referenced) admit to a disconnect between business acumen and analytics know-how, meaning that gaps definitely exist with the current approach towards analytics. All of this makes sense because, until more recently, analytics and BI implementations were driven and managed primarily by IT resources. As business units start to take more responsibility for their data assets, departmental struggles are more likely to occur. Additionally, employees who were solely focused on the business side of things have to become more involved in data. Understanding analytics and being able to interact with data to get answers to business questions is becoming more essential – not only for organizations on a whole to become successful, but for individuals as well.

As information becomes more important and businesses collect more diverse data, the way decisions are made will also shift. Silos are no longer acceptable. IT acting on its own can only act from its perspective. The same exists for individual departments. Even decisions that seem to be limited to one department require broader analysis. For instance, increasing sales requires knowing more than previous sales. To be successful, the organization needs insights into customers, competitors, products, supply chain, weather patterns, etc. Much of this information may be made available to one department, but people with a variety of experiences are required to make decisions that will effect the broader sales channel. 

What all of this means for mid-sized businesses is that companies seem to be making headway towards the right direction:

  1. Cohesion between IT and business does exist within many SMBs.
  2. Half of identified businesses seem to have organization wide decision making strategy.
  3. 70% of organizations have resources that can link business and data related insights to leverage analytics successfully.

As data becomes more widely available to more employees within more departments, organizations will begin to share information with each other and increase collaborative efforts. After all, working in silos or relying on IT will only limit the benefits that can be realized by analytics. Big data is just an extension of the fact that organizations need information from a variety of sources in order to gain the visibility required to remain successful. The reality, however, is that data only represents half of what is required to maintain success. People and departments collaborating more broadly and sharing data across the organization are also required for data to remain valuable.

This post was brought to you by IBM for Midsize Business and opinions are my own. To read more on this topic, visit  IBM’s Midsize Insider. Dedicated to providing businesses with expertise, solutions and tools that are specific to small and midsized companies, the Midsize Business program provides businesses with the materials and knowledge they need to become engines of a smarter planet.

 

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http://www.b-eye-network.com/blogs/wise/archives/2014/08/leveraging_information_assets_and_the_need_for_col.php http://www.b-eye-network.com/blogs/wise/archives/2014/08/leveraging_information_assets_and_the_need_for_col.php Mon, 25 Aug 2014 17:12:58 -0700
With all of the data available – why do companies still fall short? It is slowly becoming easier to tie in business analytics with real world value to enhance customer experiences. Technologies support diverse data collection, storage, management, analytics, and delivery. Organizations can identify trends, customer preferences, and customer satisfaction levels by looking at a variety of factors and information sources. Algorithms can be defined to take into account a variety of scenarios and identify outliers. Advanced analytics, big data storage, and the like seem to be the answer to many company challenges that exist in a competitive marketplace where customers can choose similar products and services from multiple providers. If this really is the case, then why does it seem as if many businesses are missing the boat?

Case in point: Although I normally don’t use personal examples, this one jumped out at me. I am in the middle of a move and after an unhappy journey with my telecommunications provider I have decided to use a different provider. About a week after giving notice, I received a lovely letter in the mail inviting me to call their office to see if anything could be done to win me back. Although a very nice gesture, the reality of the situation is that had they evaluated me as a customer over the past several months, they would have realized that I was lost to them before formally cancelling. Therefore, the after the fact letter was just a waste of paper and stamp. If this service provider really cared about keeping me as a customer, they would work towards identifying dissatisfied customers, the reasons they are not happy, and which ones have a potential high customer lifetime value to know which ones to invest in trying to retain. If I fall into that category, then sending a letter after I’ve already cancelled is too little too late. 

This situation reminded me of a case study presentation at a conference by a leading North American Bank that was worried about competing with other large financial institutions and their struggle with customer satisfaction ratings. A trend was occurring whereby long term customers with good standing would want to deposit a check and withdraw money automatically without having the bank hold the check. What ended up happening is that there was a higher than average turnover rate with these customers who were looking to other banks to provide them with immediate transactions. In order to maintain high customer ratings, the bank began to analyze what was happening. The results of the analysis were that the customers with large investments in the bank were the ones who decided to leave because they weren’t being serviced the way they wanted, as opposed to a number of customers who complained a lot but didn’t leave. It was found that the customers who stayed didn’t have as much invested with the bank. Consequently, the bank decided to take the risk and provide the long standing, high investing customers with immediate access to their funds because they were low risk. The result was higher satisfaction and less turnover. The lower investing customers would be addressed based on their individual situations, but the main effort was placed on the customers the bank felt would do more business with the bank over time.

These examples are simple and yet highlight the value of information insights. Organizations may struggle with their BI investments, but the reality is that BI can no longer be a separate tool set within the wider organization. Businesses need to understand the fact that they risk losing business and missing opportunities without the insights they require to identify trends and opportunities. Broader access to information is key, and now the market is flooded with solutions that can address the variety of needs that exist. All of which can help align organization goals with higher customer satisfaction.

This post was brought to you by IBM for Midsize Business and opinions are my own. To read more on this topic, visit  IBM’s Midsize Insider. Dedicated to providing businesses with expertise, solutions and tools that are specific to small and midsized companies, the Midsize Business program provides businesses with the materials and knowledge they need to become engines of a smarter planet.

 

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http://www.b-eye-network.com/blogs/wise/archives/2014/08/with_all_of_the_data_available_why_do_companies_st.php http://www.b-eye-network.com/blogs/wise/archives/2014/08/with_all_of_the_data_available_why_do_companies_st.php Tue, 12 Aug 2014 16:47:42 -0700
Understanding User Expectations Self-service access to analytics is becoming a key component when trying to expand BI and analytics access throughout the organization. For SMBs, this is especially important. Organizations need access to information that is relevant to business pains being experienced and to plan for the future. Analytics can also be used to identify trends and whether the right steps are being taken to move to the next level. The reality however, is that data and the use of analytics are only as good as what’s done with them. Information is required on a daily basis within most, if not all, job functions. But simply having BI doesn’t lead to business value. Organizations need to implement solutions and integrate them within business processes so that they can be acted upon. From the perspective of users, this means meeting end user expectations and delivering solutions that are easy to access, interact with, and reliable. A good starting point is to look at the following:

Data access

Most business users do not have the expertise to join tables, identify the fields they need, apply algorithms, and defined business rules accurately without guidance. In addition, many users struggle with the fact that they are interacting with information they don’t fully trust. Therefore this needs to be done for them by developing a front end whereby the data layer is taken out of the equation. At the same time, the information being acted with needs to be governed in some fashion to ensure its accuracy and validity over time. Anything less means that information over time cannot fully be trusted. In cases where two levels of users exist and there are people within the organization who understand the data layer, there needs to be more flexibility in the way in which data is interacted with.

Data discovery and interactivity

Once data is prepared, business users need to be able to explore the data the way they see fit. Interactivity needs to be valid, in the sense that users need to be able to ensure that their data is joined properly (in the way that makes sense for their business questions, etc.). The challenge with this is granting users enough access allowing them to explore data without having to determine a predefined set of pathways, while making sure that they are unable to develop analytics based on wrong assumptions. Organizations, therefore, need to balance these two aspects to make sure that solutions are designed with a high level of flexibility to sort through data, but not too much that allows people to make the wrong joins or develop conclusions based on inaccurate assumptions.

Self-service and ease of use

Self-service takes this one step further by making sure that the tools used to support decision making and analytics are easy to use and match the level of expertise of the user. Within organizations this might mean having more than one type of access to ensure that decision makers can access data in the way that best meets their needs. One of the challenges of “ease of use” is that solutions are generally developed by IT developers. What this means is that not all user friendly, self-service solutions are actually self-service for everyone. To really achieve self-service it becomes important to make sure that implemented solutions are intuitive to those interacting with them.

Although BI users have many expectations, these three areas provide the basic requirements when developing interactive BI and analytics access points that support broader decision making across the organization.  

This post was brought to you by IBM for Midsize Business and opinions are my own. To read more on this topic, visit  IBM’s Midsize Insider. Dedicated to providing businesses with expertise, solutions and tools that are specific to small and midsized companies, the Midsize Business program provides businesses with the materials and knowledge they need to become engines of a smarter planet.

 

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http://www.b-eye-network.com/blogs/wise/archives/2014/07/understanding_user_expectations.php http://www.b-eye-network.com/blogs/wise/archives/2014/07/understanding_user_expectations.php Tue, 29 Jul 2014 17:57:37 -0700
Takeaways from MicroStrategy World MicroStrategy World 2014 in Barcelona marked a transformation in the company’s product positioning and corporate direction. From re-packaging their offerings to making their product roadmap public, MicroStrategy is looking to bring to market solutions that are easy to deploy and consume. 

MicroStrategy’s new packaging and pricing is based on taking the former 21 product offerings and packaging them as 4 products as follows:

  • Web: A browser based interface for analytics design and consumption (i.e. reports and dashboards).
  • Mobile: An interface for mobile devices to enable analytics and developed apps access on mobile devices.
  • Architect: Development and migration tools to manage application development and BI process automation.
  • Server: The infrastructure required to support multiple data source connection, scalability, administration, etc. capabilities to support governed data delivery.

Together, these solutions provide an analytics platform that supports a wide variety of uses – from traditional reporting to operational intelligence. In addition, added R integration exists to take into account robust statistical analytics to help support forecasting and predictive modelling. This means that organizations can take advantage of additional calculations and analytics available from outside of MicroStrategy’s product suite.  

The overall strategy change in MicroStrategy’s approach to the market complements their overall focus on analytics and how they are hoping to position themselves moving forward. This includes looking at solutions based on how they are delivered – through mobility and cloud availability – to broaden the way organizations store, analyze, and consume data. 

Analytics

In general, analytics capabilities and enhancing what already exists is nothing new. Where MicroStrategy is making inroads is its commitment to self-service access and easier development and deployment so that users can get to the data they need in an easier way. Additionally, MicroStrategy is committed to a governed self-service approach, by leveraging their platform for centralized data storage. The goal being to make sure that business users interacting with self-service independently can trust the reliability of the data they access. Obviously this type of analytics is limited to the data being maintained within MicroStrategy, but can help organizations manage information access to ensure accurate analytics.

Mobile

Over the past few years, BI vendors have been focusing on mobility as a way to get analytics out to a broader variety of users. MicroStrategy goes one step further with their app development capabilities and a focus on delivery of mobile applications. Consequently, their ease of consumption 0n mobile devices is obvious based on the fact that many customers are merging mobile apps related to customer experience with analytics insights.

Cloud

Platforms in the cloud are becoming more prevalent as organizations no longer want to have to provision and manage hardware within their organizations. In addition, cloud based solutions can support infrastructure, software, and business application requirements, and in many cases do so in a way that provides quicker time to value. Since MicroStrategy first announced their cloud offerings two years ago, much of their efforts have been spent building out and solidifying their cloud platform. Moving forward, it seems like their preferential deployment model for customers. 

Security

Security really falls outside the world of analytics and Usher is a separate product. However, it addresses the challenges that exist in a world that is rife with security breaches and identity theft. Securing the enterprise and making sure that people are who they say they are becomes more important as mobile devices store so much sensitive data. 

General Thoughts 

This time MicroStrategy World was very different than it has been in the past. As mentioned, there is an increased openness regarding communication and sharing product roadmap information. But it’s more than that. There was an admission that in order to compete strongly moving forward, their products need to become more consumable and easier to develop and to maintain. This goes beyond mobile and cloud based platforms, and towards capabilities that enable self-service, broader data blending, and managing. This was obvious with their new packaging and transparent pricing, but also in their Futures session discussing the goals of redesigning product capabilities to enable easier access for both developers and business users. 

It will be interesting to see how the new pricing and product strategy will work and whether MicroStrategy will begin to be more competitive with the likes of Qlik and Tableau.

 

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http://www.b-eye-network.com/blogs/wise/archives/2014/07/takeaways_from_microstrategy_world.php http://www.b-eye-network.com/blogs/wise/archives/2014/07/takeaways_from_microstrategy_world.php Fri, 18 Jul 2014 20:02:09 -0700
Understanding Audiences For Self-Service Consumption Many solutions claim to be self-service and tout the value of their offerings by saying that ease of use and high levels of interactivity exist. The reality of these solutions, however, is that there is no industry standard for self-service delivery. There are only concepts of design that are used to enable independent analytics adoption. What this means on a practical level is that the term self-service can be misleading if used without an understanding of the target audience. For instance, some self-service offerings are built with the data scientist in mind, while others are designed to enable broader analytics deployment across the organization. Although this might not seem like a big difference, both expectations and expertise differ within these groups, making their use of business analytics different.

Data analyst/scientist

Technical users expect autonomy. The ability to add data sources, create joins, and add business rules in a flexible way support the role of data scientist. The delivery of standardized dashboards or pre-defined table views only give a limited view of what analysts need to gain relevant and valuable insights. Essentially, self-service for these users is truly that – the ability to leverage data in a way that doesn’t require IT input or management to develop new business insights. 

In many cases, these users support management and provide analytics that aid in decision making and daily operations. Because of this, self-service capabilities need to be flexible enough to address daily challenges that may not have been accounted for in design. Since each use case cannot be defined in advance, it might not be possible to identify how information will be needed or why. After all, static reports or views will provide limited insight that will most likely require broader analytics to understand in depth. Since data scientists understand the underlying information structure and business needs, this level of self-service is understandable.  

Business user

Business users, on the other hand, require a more guided experience. This means that self-service refers to user experience. Ease of use, guided design, governed data access to ensure accurate analytics, and pre-defined views are all aspects of this level of self-service. Too much flexibility can actually lead to invalid analytics based on incorrect inferences and joins that may be based on similar field names but that aren’t connected. Therefore, part of self-service involves providing pre-defined access while still maintaining flexibility to slice and dice and one-click analytics to give users quick results.

Organization specific

Although these two audiences are the most common, other consumers also exist. Organizations may have targeted self-service audiences that require specific capabilities or levels of interactivity. These unique requirements should be considered when audiences fall outside of the general types discussed above. Having successful self-service requires solutions that provide the level of self-service the user needs. If this isn’t provided accurately, then self-service interactivity may not be successful.

This post was brought to you by IBM for Midsize Business and opinions are my own. To read more on this topic, visit  IBM’s Midsize Insider. Dedicated to providing businesses with expertise, solutions and tools that are specific to small and midsized companies, the Midsize Business program provides businesses with the materials and knowledge they need to become engines of a smarter planet.

 

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http://www.b-eye-network.com/blogs/wise/archives/2014/07/understanding_audiences_for_self-service_consumpti.php http://www.b-eye-network.com/blogs/wise/archives/2014/07/understanding_audiences_for_self-service_consumpti.php Mon, 14 Jul 2014 15:41:49 -0700
#SMB4Cloud Spreecast Event: The future of cloud and SMBs Last week I took part in a Spreecast event, hosted by IBM – Cloud: Reshaping The World of Business where the increasing importance and adoption of cloud computing for SMBs was discussed. John Mason, from IBM, stated that cloud computing has become a game changer for SMBs as it takes away any barriers to entry, such as the need for an IT infrastructure or venture capital due to set up costs. Laurie McCabe, from the SMB-Group, expanded on this by discussing that in the last 3 years cloud has become more important to SMBs as it has allowed them to skip on premise implementations and supports their go to market strategy more easily. McCabe mentioned three aspects of cloud adoption that are beneficial to SMBs:

  1. Cost of solutions 
  2. Ease of use
  3. Masking of complexities while providing powerful solutions

All of these aspects also reflect the increasing importance of cloud adoption within the analytics market. Organizations continually struggle with the best way to get information into the hands of decision makers, empower customers, and increase relationships with partners and suppliers. Because many SMBs do not always have the resources to build solutions like this internally, many turn to the cloud. In most cases, SMBs are already familiar with cloud offerings because they have data hosted by outside providers and are comfortable with the concept of the cloud due to a lack of internal IT infrastructure.

As the cloud becomes a more central component to SMB adoption, analytics adoption will also become more prevalent in the cloud. This is already happening as many solution providers offer cloud BI. If they don’t already, it is in their roadmap. In addition to this, app stores are becoming more prevalent due to the fact that the way people are adopting solutions are transitioning to a more self-service methodology. The Spreecast announced IBM’s new app store and many other vendors offer analytics style app stores to make adoption easier. Instead of requiring approval through an acquisitions department, a credit card can be used. All of these market transitions will eventually make it easier for SMBs to apply broader analytics applications, without the roadblocks associated with traditional deployments.

Even for organizations choosing to keep solutions in-house, the increasing prevalence of self-service applications and ease of use and deployment associated with the cloud will translate into expectations that extend to the way solutions are deployed in-house. Consequently, solutions will have to shift to meet the needs of SMBs more readily through increasing ease of use, lower costs, and ease of deployment.

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’ve 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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http://www.b-eye-network.com/blogs/wise/archives/2014/06/smb4cloud_spreecast_event_the_future_of_cloud_and.php http://www.b-eye-network.com/blogs/wise/archives/2014/06/smb4cloud_spreecast_event_the_future_of_cloud_and.php Mon, 30 Jun 2014 14:56:44 -0700
Achieving Time to Value 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’ve 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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http://www.b-eye-network.com/blogs/wise/archives/2014/06/achieving_time_to_value.php http://www.b-eye-network.com/blogs/wise/archives/2014/06/achieving_time_to_value.php Sun, 22 Jun 2014 21:56:49 -0700
Intelligence, Integration, and Integrity – my takeaways from Information Builders Summit 2014 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.

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http://www.b-eye-network.com/blogs/wise/archives/2014/06/intelligence_integration_and_integrity_my_takeaway.php http://www.b-eye-network.com/blogs/wise/archives/2014/06/intelligence_integration_and_integrity_my_takeaway.php Mon, 16 Jun 2014 14:26:30 -0700
Common BI Newbie Mistakes 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’ve 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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http://www.b-eye-network.com/blogs/wise/archives/2014/05/common_bi_newbie_mistakes.php http://www.b-eye-network.com/blogs/wise/archives/2014/05/common_bi_newbie_mistakes.php Tue, 27 May 2014 18:06:47 -0700
Using Embedded Analytics for Enhanced Customer Experience 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’ve 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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http://www.b-eye-network.com/blogs/wise/archives/2014/05/using_embedded_analytics_for_enhanced_customer_exp.php http://www.b-eye-network.com/blogs/wise/archives/2014/05/using_embedded_analytics_for_enhanced_customer_exp.php Thu, 22 May 2014 12:31:51 -0700
Understanding the BI Landscape 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 – organizations 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’ve 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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http://www.b-eye-network.com/blogs/wise/archives/2014/04/understanding_the_bi_landscape.php http://www.b-eye-network.com/blogs/wise/archives/2014/04/understanding_the_bi_landscape.php Wed, 30 Apr 2014 21:51:36 -0700
Looking at the Cloud – SMB adoption is not new Mid-market organizations have always been familiar with service-based (hosted) offerings. Whether Salesforce, or ERP, Accounting, etc. types of applications, these organizations are used to hosted applications that store data off-site. What this means is that the new push to the cloud, isn’t necessarily so new for all organizations. Many are starting to take advantage of what the cloud has to offer, while other businesses are simply continuing or expanding their cloud deployments. The two things that have changed are the number of solutions available and the understanding of those offerings.

More awareness about the cloud

Although there is more awareness about cloud offerings, not all organizations want to have their data hosted or outside their firewall. In addition, some organizations misinterpret the concept of cloud-based offerings by not understanding the difference between where the data resides and whether it is just hosted or if services are attached. For instance, I have been told by more than one organization that they do not use any cloud offerings, only to find out through more analysis that a number of applications are cloud-based but not hosted as a service – in essence creating a differentiation between the level of control the customer has over the data they use.

With SMBs specifically, this makes a big difference. Many organizations want solutions with lower overall TCO and quicker times to implement, but still want to control their access to data and the overall use of the systems they deploy. Consequently, for these businesses, the cloud represents two levels of use:

  1. the hosting of and access to data off-site within a cloud environment
  2. the ability to manage that data or the applications the way the company desires, or alternatively, to be provided access to the data as a service through a hosted offering

Basically, a lot of the hype around cloud adoption and expanded offerings, simply means that SMBs have more choice when identifying the best way to leverage technology and find value through their data assets.

 

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’ve 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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http://www.b-eye-network.com/blogs/wise/archives/2014/04/looking_at_the_cloud_smb_adoption_is_not_new.php http://www.b-eye-network.com/blogs/wise/archives/2014/04/looking_at_the_cloud_smb_adoption_is_not_new.php Thu, 24 Apr 2014 18:24:00 -0700
Finding the balance between business and IT Technology projects always face unique challenges due to the fact that their success requires taking into account two viewpoints. The first being from the business point of view, identifying the business challenge and understanding how a solution will address specific needs. The second being an IT outlook and understanding the technology best fit. In some cases these will match and in other cases there will be discrepancies. The reality is that few companies will be able to avoid this disparity of views. However, if organizations can take responsibility for their portion of solution evaluation and collaborate to make the right business and technology decisions to support long term business goals, then both entities can develop a balance. 

Both business and IT need to take responsibility for their respective areas. This means that business units:

  1. develop an understanding of their business challenges and the causes of their pains
  2. evaluate the requirements based on their needs 
  3. understand the gaps between current technology use and why it doesn’t meet business needs
  4. make sure to look at must haves versus nice to haves
  5. create agreement among stakeholders who will also be using the new solution

In most cases IT supports and develops business applications meaning they require:

  1. an understanding of the business challenges being faced
  2. how these translate into features and solution capabilities and general technical requirements
  3. what the integration and storage requirements are and whether changes in infrastructure are required to support the new solution
  4. development effort and support for offerings being evaluated and the implications
  5. building up applications that meet business needs longer term

These aspects represent the first look at the responsibilities of each of these entities. The reality is that because they overlap, collaboration is required. How much and specific aspects will differ depending on the politics within the organization and the amount of collaboration that already exists. The best balance within organizations generally exist when both entities look at software projects as something that is the responsibility of both the business unit sponsoring the project and the IT department. This way both understand the value of each set of contributions. On the business side this includes all of the subject matter expertise, while the IT department develops the solution and supports the technology required to actualize the project. 

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’ve 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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http://www.b-eye-network.com/blogs/wise/archives/2014/03/finding_the_balance_between_business_and_it.php http://www.b-eye-network.com/blogs/wise/archives/2014/03/finding_the_balance_between_business_and_it.php Mon, 31 Mar 2014 14:47:14 -0700
Big data for small companies The term “big data” is a bit of a misnomer. Many mid-market organizations feel that big data doesn’t apply to them based on the size and infrastructure assumptions associated with these projects. Consequently, many organizations overlook the benefits of looking at big data as a BI and data management strategy. Whether or not big data should be addressed depends on many factors. Some of these include:

  • types of data being analyzed – this means looking at whether data should/can be stored within a relational database or should be stored separately within another format
  • purpose of analytics – traditional BI environments enable certain types of analytics well, but generally don’t support operational analytics, or the ability to store and access the data variety or complexities associated with big data
  • reason for information storage – big data is broader than BI or analytics and the different applications should be explored
  • level of complexity – sometimes organizations do not have high data volumes, but do have complexities based on industry or company specific requirements that are best handled within a big data infrastructure

These represent a subset of reasons why mid-sized businesses should be looking at whether big data applies within their organizations and what needs to happen to implement a big data framework.

As with all technology projects, more considerations are required than just looking at whether the organization faces challenges that reflect the factors above or others conducive to big data environments. Organizations need to understand their current infrastructure, what they can support, what hardware or cloud based provisions need to be considered, costs of initiating a new data management project, and how all of this will directly affect business. Understanding the bigger picture and where a big data solution might fit within a broader information architecture and how it benefits the company as a whole is one of the first steps of deciding whether it’s the right step for the organization.

Overall, the important thing to remember is not to discredit the potential big data can bring to the organization because it may seem out of reach as open source technologies, internal resources, and general education can help mid-market companies move towards their big data goals. 

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’ve 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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http://www.b-eye-network.com/blogs/wise/archives/2014/03/big_data_for_small_companies.php http://www.b-eye-network.com/blogs/wise/archives/2014/03/big_data_for_small_companies.php Tue, 18 Mar 2014 18:31:42 -0700