The importance of BI specific skill sets

Wednesday, September 24, 2014 8:16
Posted in category Uncategorized

BI implementations are becoming more commonplace as organizations realize they cannot overlook the management of and access to their data in order to facilitate better decision-making. What this means for many is the re-evaluation of resources, skill sets, and project planning to ensure that the proper resources exist to support BI and analytics development. Unfortunately, many businesses overlook the fact that IT development expertise does not equal BI savvy. There are SMBs without the IT resources to facilitate a project but there are also companies with an IT department and developers on-hand, but without BI development experience or skills. The reason why this is an important consideration is because in order for solutions to be effective, they need to be designed right – and right includes understanding data, analytics, and design in a way that promotes BI best practices. In general, two types of organizations exist, and identifying and leveraging the right skill sets are equally important for both.

Organizations that don’t care

Businesses may feel that they don’t have the bandwidth to hire new people or to train existing staff. The problem is that risks increase as developers, already over allocated in many cases, struggle to get a solution up and running that they don’t understand. Although solutions will be developed and analytics access granted, there may be inconsistencies in performance, leading to the inability to access the data required when needed or to required functionality not being leveraged efficiently. Either way, organizations need to understand that investing in a BI initiative may require budget set aside for skill set development or outsourcing services.

Organizations willing to invest

Other organizations are willing to invest to make sure that their BI solutions are developed properly. In many of these cases, vendor professional services or outside consultants are used to develop the initial solutions to get BI up and running, or alternatively, to enhance what already exists. For these organizations it still becomes important to ensure that support exists on an ongoing basis or a transfer of skill sets occurs so that BI can be properly maintained moving forward.

The reality for organizations is that BI success requires specific skills and knowledge, and are not within the realm of a generalist to do effectively. Although many organizations attempt to go it alone, the reality is that businesses require an in-depth understanding of the technology and tools used in order to develop successful BI applications.

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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Why are organizations still struggling with their data?

Friday, September 19, 2014 6:32
Posted in category Uncategorized

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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Leveraging information assets and the need for collaborative decision making

Monday, August 25, 2014 10:12
Posted in category Uncategorized

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% 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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With all of the data available – why do companies still fall short?

Tuesday, August 12, 2014 9:47
Posted in category Uncategorized

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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Understanding User Expectations

Tuesday, July 29, 2014 10:57
Posted in category Uncategorized

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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