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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 lwise@wiseanalytics.com.

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

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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Posted August 12, 2014 4:47 PM
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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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Posted July 29, 2014 5:57 PM
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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.

 


Posted July 18, 2014 8:02 PM
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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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Posted July 14, 2014 3:41 PM
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Last week I took part in a Spreecast event, hosted by IBM РCloud: 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‚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 30, 2014 2:56 PM
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