The Internet of Things: Our Bright Future or Inevitable Downfall

Post written by Blake W., Management Consultant at Ideaca. Read more on his blog: Blake Watson.

The Internet of Things (IoT), essentially a future-focused concept where everyday devices connect and communicate data in an intelligent fashion is a highly contested topic. Will it mark the beginning of a new era in our civilization or a catastrophic detriment to the world as we know it? Skipping over the possibility of our technology becoming self-aware and “terminating” us, these two polar opposites are often portrayed in the discussion of this topic. This post will broadly summarize the IoT and discuss the positives and negatives in relation to our daily lives.

So what is the IoT? It is a term that has been vaguely used since the 1990’s and has gained traction since its initial public proposal by Kevin Ashton in 1999. It is a term that suggests a heavy increase in device-to-device and device-to-Internet connectivity. By equipping these devices into a worldwide network of miniscule identification devices the IoT could transform our daily lives.

Is this interconnectivity even possible? Simply put, yes. Technology is growing at a rapid pace, confirming Moore’s Law, wherein Gordon E. Moore’s observed that the transistors, and thus the processing power of our devices, double approximately every two years. Although many have debated the staying power of this observation, the exponential potential of this theory is astounding. If the past few decades are any indication, the IoT is a highly probable (and sometimes frightening) reality.

As mentioned before, the IoT could transform life as we know it. A simple scenario: You get home from a busy day at work. Monitors in your home identify you and let you in. Immediately, the room taps into a wealth of your personal information and preferences…climate control, music, lighting, and digital décor. These sensors may even be able to determine what you want for dinner and start preparing it for you based off of what is in your refrigerator. Some of these devices are already available through “smart” technology. Within the next 20, the possibilities are endless.

THE GOOD:

For the individual, the IoT integration arguably increases our standards of living. No longer are we plagued by menial tasks that take up our days. The IoT essentially frees up time and energy that could be better spent productively or recreationally. It doesn’t necessarily mean that as a collective we will be healthier, happier individuals. However, we will have more opportunity to achieve this lifestyle.

From the business perspective, greater analytic capabilities are accessible to management and supervisors. Asset tracking, inventory controls, and financial drilldowns are far more accurate. Location services, automation, and device interconnectivity eliminate a great deal of the “guess-timation” involved in these operations. Sectors such as consulting, financial services, and even health could benefit greatly from these advancements.

Businesses also have access to a huge amount of data. Big Data will be a simple task compared to the vast amount of information that corporations will be able to collect from client usage and habits. We will have to start considering XXXL Data as opposed to Big Data. Billions and even trillions of source data will give business owners the tools to minutely tailor their products and marketing to individuals in the most literal sense of the word.

THE BAD:

The IoT has a dark side to it. Many people feel a sense of unease when they consider the privacy concerns the IoT imposes. If you are the slightest bit afraid of “Big Brother”, then the IoT is not for you. The amount of information that can be collected by governments and corporations through the billions of personal, business, and home devices is astounding. These devices sometimes know more about you than you do.

Another hot topic at the moment is job security; for low income earners, the IoT could make things especially tough. A number of unskilled tasks (and even some higher level analytics) might easily be replaced by a network of devices connected to the IoT.

Another concern is the effect that this new world order may have on our physical health. When all of our devices are communicating, making decisions, and essentially managing our lives for us, the opportunity to become complacent with that level of comfort is tempting. The World Health Organization estimates that over 65% of the world’s population currently lives in countries where obesity kills more people than being underweight. This upward trend isn’t expected to slow down anytime soon, especially with the continued introduction of technology that makes our lives even easier.

OVERALL:

Although there are many negatives that could affect reception of the IoT, it is my belief that reactions will be mostly positive. Although some aspects of these new technologies are to our detriment, there is a great deal of benefit that can come from an increased awareness of the IoT. As younger generations are brought up with modern day technologies, we may begin to see society move away from a privacy-centric culture. This shift would effectively reduce public outcry for greater privacy rights in this changing environment.

Although malicious Internet hackers and identity thieves may pry on the wealth of information available, we are facing no greater threat in the future than we are now. Security safeguards are in place and continue to develop. At the same time, data thieves are growing their methods for subverting such safeguards. This struggle for access and security will continue with no real definitive end in sight. Therefore, data security should not be considered within scope of this discussion.

The main problem moving towards our ideal vision of the IoT is that it will depend heavily upon data sharing and corporate cooperation. Think of all of the different products in your home… appliances, personal devices, clothing, and climate control. Seamless integration is necessary to ensure the IoT is able to function effectively in your daily life. If your devices cannot access the personal information it needs it will not function properly. It is hard to imagine companies (For example, Apple and Samsung) sharing customer data and integrating their products out of the box. Cooperation will be mandatory and it is something that companies will have to be overcome as we move forward with the IoT.

As briefly mentioned above, consulting firms such as Ideaca Knowledge Services will benefit greatly from the wealth of information available to them. The greater availability of information resources will allow their consultants to better assess client needs. Having clear needs from both the client and end consumer is essential. Better data means better solutions and ultimately better deliverables.

Whatever your take is on the IoT, there are a lot of variables to take into account. The changes that it will bring to our society are truly hard to imagine 20 years out. For good or for bad, the world is growing and developing towards the IoT. Will we try to hold on to our present state of technology or embrace these changes when they come?

Project Management isn’t just for IT or Engineering anymore

Post written by Jason Z., Project Manager at Ideaca. Read more about project management on his blog: Unnatural Leadership.

As part of this month’s Ideaca blogging network challenge, we were tasked with discussing our thoughts on Emerging Practices.

One of my favorite quotes to reference from the The Project Management Body of Knowledge (PMBOK, pronounced pemmmmbock) is “As project management is a critical strategic discipline, the project manager becomes the link between the strategy and the team. Projects are essential to the growth and survival of organizations.” So, while operational duties are of very high importance to maintaining the forward momentum and revenue generation for a company, projects are strategic and help organizations react to changes in the external environment that may slow forward momentum and/or impair revenue generation.

Taking this as rote, one Emerging Practice that I am pleased to see is that more industries and functions – outside of Engineering and IT – are recognizing the need for project management:

• In the legal sector, project management has been a fairly hot topic since approximately 2010. It’s also getting more attention in law schools.
• Digital Ad Agencies position project managers to help their customers realize a marketing vision.
• The Human Resources designation – Certified Human Resources Professional (CHRP) - now has a focus on Project Management.
• Investment Banks have started hiring project managers to help manage deals.

So what does this mean for Project Management as a career? It means that effective Project Management is not just for IT and Engineering anymore. In fact, the rest of the organization is going to have to contend with:

• Increased workloads for Subject Matter Experts. If you know the organizational area, you must know how to manage the project to do something in this organizational area.
• Gone are the days of black box projects – clients are demanding more visibility into what is being delivered, how it’s being delivered, and how delivery is progressing.
• Organizations are demanding value from their staff’s time - projects are going to have to deliver more than a “thing.”
• Successfully implementing changes in an organization can no longer be ad-hoc, and to a lesser extent grassroots. Rather, efforts must be controlled activities.

This is both amazing, and troubling at the same time. It’s amazing because having proper control, visibility, and communication for organizations can return recognizable and material value. It’s troubling though, as many organizations may start expecting their people to be expert project managers without any proper training or experience (this link is a great discussion on LinkedIn, by the way).

If your organization is transitioning to more of a project focus, and you don’t have the time or desire to become a fully trained PMP, there are a number of ways to get up to speed on how to be effective:

• Hire a dedicated (or shared) Project Manager – This person should be able to apply project management best practices while you are focused on the subject matter at hand. If your department doesn't have the budget or enough work for a full time Project Manager, share the PM (both cost and time) with a different department.
• Mentoring – Junior PMs will often work with Senior PMs for mentoring, so why not do the same? Your company should have a PM for you to reach out to, or you can contact someone in your local PMI chapter.
• Training – Most colleges offer introductory PM training. In exchange for some of your time over a couple of weeks, you can get trained up on how to run a small project effectively.
• Reading – There are many great books available. One that I recommend is Project Management Lite: Just Enough to get the Job Done…Nothing more. Another, more detailed, is the big bible - Rita Mulcahy’s guide to passing the PMP on your first try. You don’t have to attempt the PMP, you just need to read this book.

Has your organization made the transition to more project-based initiatives?  How has it impacted you?  What have you learned?

How Technology Changes Us: Canada In 10 Years

Post written by Niaz T., Senior Solution Architect / SAP BW Consultant at Ideaca. Read more about SAP HANA on her blog: Discover In-memory Technology.

The theme of the Ideaca Blogging Network for the month of August is a very interesting subject. Certainly, technology changes the way we do things on a daily basis. Not only in Canada, but also globally. There could be some specific cases in Canada, such as Green technology to combat climate change. However, most of the technology changes impact us globally, specially in more advanced countries.

The first thing that it comes to my mind is technology will enable us to convert Zettaflood (10 to the 21st bits, or a thousand exabytes) of data in to meaningful information which we are very dependent. Like it or not, business intelligence already has an increasingly important part of our life. The challenge will be how to deal with the explosion of data coming from all types of gadgets and smart technologies because value-based intelligent information helps us to get things faster, better and easier. The speed of rising adoption of cloud, mobile, real-time applications and social technologies and exponential data growth is a big challenge of staying current.

How technology solves this challenge? Some of the biggest improvements have been around networking. We will be able to move more data faster from many sources and applications to where is needed. We won’t have any restriction in terms of capacity, scalability and processing speed. Organizations will be able to leverage the three “V’s”, volume, variety and velocity, of data to augment the value of data for their decision making. Powerful in-memory technology such as SAP HANA enable us to design complex predicative and preventative models for all type of data from structured and unstructured like audio and video files. Next generation of data visualization and intelligent reporting tools empower users to slice and dice information any way it is demanded. We will be able to tell stories with data by connecting millions of data points to get a bigger picture. Big data will change our world and it will blow our mind by providing us tons of opportunities. It will make our word smaller and we will be all connected.

I believe in the next 10 years, another significant change will be human and machines interaction. It seems that human interaction, communication and relationships will be more efficient, faster and stronger through smart technologies. Also, we will be able to have better understanding of machine behaviors and machines will have a better understanding of ours. Ideally humans and machines will work alongside each other and hopefully not replacing human with machines. Although there are ongoing developments and opportunities to replace human with machines, it’s required to consider all potentials dangers and associated risks.

Personally, I’m very excited to see how technology will enable us to access information easily, increase our potential and creativity, improve our lifestyle and promise of longevity, and improve communication and social networking. On the other hand, I believe we need to keep things in balance with respect to human identity and our social behavior. For example, neuroscientists are concerned about how modern technology is making us not use our brains to their full potentials. Based on the evidence, loneliness and depression is increasing and people are less happy in modern society. It’s been observed that the newer generation—equipped with all kinds of smart technology—is less effective in terms of communication skills and human interaction.

The bottom line is we use technology to change the world to suit us better. The important thing is to control it so it doesn’t destroy human intelligence and social interaction. For instance, it would be great to get a relaxing massage after a long day by a smart robot that has already taken care of the house chores. However, nothing will replace a nice face to face conversation with your favorite person or a warm friendly hug to someone you care about. I don’t think we could ever replace our human connection with human-robot connection.

Is Big Data Only About…Big Data?

Post written by Wade W., BI Consultant at Ideaca. Read more about BI on his blog: Pragmatic Business Intelligence.  

If nothing else, IT is all about buzzwords, and “Big Data” is one of the new arrivals to the party.
It is, however, a descriptive one. “Big Data” evokes images of enormous relational databases, providing analytical (or operational) reporting.

Big Data is not only about size however. Rather, it refers to attributes of the data that together challenge the constraints of a business need or system to respond to it. Those attributes can include any or all of attributes such as size/volume (of data), speed (of generation), and number and variety of systems or applications that simultaneously generate data. Another thing that is unique about Big Data is how it varies in structure. Elements of “structure” would include the diversity of its generation (eg. Social media, video, images, manual text, automatically generated data, such as a weather forecast, etc), information interconnectedness and interactivity.

I heard somewhere a thumbnail statistic that 80% of data in companies is unstructured or semi-structured. Just to clarify the meanings of those terms, an unstructured data artifact would be a document, an email, a video or audio clip. A semi-structured data artifact would include data that does not conform to the norms of structured data but contains markers or tags that enforce some kind of loose (or not so loose) structure. XML documents would be an example of semi-structured data.  Tagged documents in a Knowledge Management system would also fit into this definition.

Structured data is what we would find in any database – a Data Model has been defined and the data is physically arranged within this model into tables. The data in these tables is described with metadata (i.e. data types (such as “character”) and the maximum length of that data (number of bytes)).

The methods of data creation are multiplying and the velocity of its creation are increasing. And that, in itself is a complicating factor. Some analysts (IDC, for example), predict that the Digital Universe -  that is, the world’s data – will increase by 50x by 2020. There will be in the same period, a growing shortage of storage, which will drive investment in the cloud as both individuals and corporations look for scalable, ubiquitously accessible, lower-cost and environmental data storage options. In addition, the same study predicts that of all that data, unstructured data, especially video, will account for 90% of that data.

There is also an important historical dimension to Big Data. For decades, companies have been hoarding structured, semi-structured and unstructured data in hopes of one day being able to extract value from it at some point in the future.

A large percentage of all this data will come with a wrapper of automatically generated Metadata – that is, (as indicated above), data about (or that describes) that data. A practical example could be the generation of a data artifact coming wrapped with metadata from those GPS enabled, media rich, socially linked mobile devices we all carry with us that transparently capture location, GPS coordinates, time, weather conditions and a plethora of other data elements when you click that holiday photo with your mobile phone. IDC predicts that such metadata is growing twice as fast as data.

It is clear from the last three paragraphs that Big Data describes explosive growth in data and metadata and an equally explosive opportunity to capture, tame and corral that data to extract value from it.

So the case has been made that we have a lot of data today and we will have even way more tomorrow, but should your organization be investing in Big Data today?

In a sense, probably you already are. Enterprise Business Intelligence environments lay a solid foundation for the next phase of Big Data. EBI is an earlier iteration of Big Data and, married to tools such as Hadoop and NoSQL databases for example, enable a natural evolutionary growth curve to your mastery of your information ecosystem.

Big Data has a requirement for a new way of thinking, new tools, clustered commodity hardware and probably, substantial investment. It comes down to your business, and if there is a clear value-based case to present that data to your company’s brainpower. The actual needs for this will be radically different depending on your industry. Oil and Gas may be interested in leveraging real time alerts in wellhead data or analyzing petabyte seismic datasets.  Packaged Goods multinationals may be interested in monitoring and engaging advocates, detractors and influencers across multiple Social Media platforms, mining and understanding sentiment and identifying problem areas in real time in order to identify opportunity or identify and avert potential brand-damaging events. Financial institutions may be interested in monitoring international money traffic to identify fraud or illegal activity. Government entities may mine extremist forums, or other unstructured data traffic to identify national threats.

Big Data can serve these needs in real time, enabling rapid (or even automated) response to flagged events. Whether it is a fit for your organization today would be determined through viewing your industry and business through a critical lens on your current Information Intelligence maturity, a strategic assessment of the data and information assets currently owned or available to your organization, and a prioritization of potential initiatives. How much data you harness and convert into information should be a key outcome required from this exercise. The opportunities are legion, but initiatives should have clear objectives and success metrics understood prior to a project kickoff.
Whether it is today or tomorrow, Big Data is becoming mainstream through necessity. Whether that is a road your organization wants, or needs to drive today, is something all medium and large organizations should be considering now.

What are your thoughts on Big Data? Is your organization currently considering Big Data as a strategic imitative or Proof of Concept?

Project Management and Big Data – as a project

Post written by Jason Z., Project Manager at Ideaca. Read more about project management on his blog: Unnatural Leadership.

As part of this month’s Ideaca blogging network challenge, we were tasked with discussing our thoughts on Big Data.

This is going to be a 2 part post:

• The first part will cover how you, as a project manager, should approach a project that carries the mantle of “Big Data.”
• The second part will cover how you, as someone in a Project/Program Management Office, can use Big Data without getting snookered by the hype.

Part 1 – So you’ve been asked to “implement Big Data”… what now?

Defining Your Terms
I am going to assume that you – like me – tend to be baffled by the marketing speak until you can speak with someone intelligently about a topic. In the case of Big Data, I have heard a few definitions. The one that seems to stick the most for me is the one from Wikipedia:

• Data sets that are too big for traditional database management systems to handle
• Data sets that comprise information from multiple sources to try to infer correlation

Sounds easy enough, right?
Where it starts to get complicated (thanks Wade!) is when you try to integrate “unstructured and semi-structured data with our 'traditional' structured data.”

You will never “implement Big Data”
When it comes to Big Data, you do not implement it. You may be implementing a technology to support the analysis, but you will never actually implement this “thing.” A project of this sort relies on understanding the user requirements, selecting the right technology, and taking an exploratory approach when developing reporting capabilities.

Understanding the User Requirements
In the case of a new process and technology, such as this, your user requirements may be fairly light. "We want to correlate information from disparate sources to identify predictive trends” or “I don’t know – but I really want some cool looking reports” may be common lines that you hear. Like all projects, the user requirements are your definition of success. Because “Big Data” is still a technology in the exploratory stage, though, expecting detailed requirements may be the wrong sorts of requirements. The ones that you should be really focused on are the data sources and ensuring that the information being presented is right.

To wit, if I were to ask you to present the information on the average CEO compensation for the top 50 companies in North America, how would you start? How would you define the Top 50?  By Market Capitalization? By Environmental Performance? By Stock Price? By Revenue? What about getting access to private company information? All of the sudden, a fairly simple question about the average CEO compensation gets a little more complex.

The same will be true of your Big Data project. Start by understanding that to present the information your users want, you will either have to ask a whole lot of detailed questions, or provide a platform to enable them to answer their own questions.

Understanding the available technology
As Project Managers, we know that when we are asked to Implement something, it’s never that simple. Understanding what the technology can and cannot do is critical to ensuring that your project can meet the user’s definition of success.

One might want to satisfy the guiding principles of a company’s Enterprise Architecture. A quick scan of the landscape will reveal that tools like SAP HANA, Oracle’s Exadata, and Amazon’s AWS can all fulfill the technology requirements quite nicely and potentially support a company’s Enterprise Architecture. However, since this is a new application of technology, fulfillment of requirements needs to trump Enterprise Architecture.

Take an Exploratory and Iterative Approach to reporting
Some organizations will judge success of your project by its ability to deliver a load of reports. If this sounds like your organization, be realistic as to what can be delivered. Deliver a robust and reliable dataset, some transactional reports, and one report that really helps demonstrate the art of the possible.

Smarter organizations will judge the success of your project by its ability to deliver analytic capabilities to the user base. The robust and reliable dataset is still mandatory, but the ability for users to generate their own reports will satisfy all of the “what about …?” requirements that would blow your project budget and schedule out of the water.

In the end… it’s the people that matter
If we believe all of the marketing hype, Big Data will help us explore all the myriad of ways our world is constructed. But from the perspective of a Big Data as a project, an empowered user base will produce much more value than some canned reports.

Have you been asked to “implement big data”?
If so, what did your project look like? Let me know in the comments down below. Stay tuned for another post on making the most of Big Data in a PMO.


Special thanks to Wade Walker and Chris Sorensen for keeping me honest with this post.

Just Imagine...

Post written by Chris S., BI Consultant at Ideaca. Read more about BI on his blog: The Outspoken Data Guy.

For quite some time I have been imagining what the possibilities of Big Data might be. I am certainly no expert in the area but being the data guy that I am, I often wonder what might be able to be done with data that may be being collected at any point in time. Face it, we are so connected now that our every move generates some form of data and often multiple pieces of it.

For example, if a marketer wanted to know everything about Chris Sorensen in a given day, chances are that most of that data is logged somewhere. What time I leave my house is available via my cell phone, my driving directions and speed are also available there as well. When I sit on the train I surf the web, send emails and organize my task list, all of these actions generate recorded data. What time I log into work, how often I am active on my computer and what I am do all day long is logged. Where I shop, what I buy (if I have a rewards card) is all tracked. My Facebook views, tweets all contain things that could be used to build a personality model of myself and my habits.

It is not really that big of stretch to think that this data could be used in one gigantic model to predict my next move and perhaps even entice me to make a different one. Maybe instead of stopping at Home Depot to get my painting supplies, an app could suggest the best place for me to go based on what I am doing. Sound like a stretch? Not really…Think about the labor that gold miners went through just to get a few stones. Now gigantic machinery does the same thing. The same thing is happening with Big Data where machines are able to gather information from a variety of sources and store large volumes of it in order to form predictive models. We are only at the tip of the iceberg but just imagine what the possibilities might be

Standards = Starting Point

 Post written by Wade W., BI Consultant at Ideaca. Read more about BI on his blog: Pragmatic Business Intelligence.  

In a data migration project, standards are synonymous with quality.

Every developer has a different philosophy of what works. Many say that it is easier to develop with “what I know," which sounds a lot like “quick and dirty."

The definition of, or existence of Standards of Development and Naming Conventions provide guidelines within which developers should be expected to work. Without these, your environment quickly becomes rife with development packages, interfaces and jobs with different naming conventions, different approaches and widely varying levels of development quality.

I think it is common that, lacking a mentor or some kind of guidance, developers new to data migration start the same way – monster jobs, lack of flexibility, lack of clarity…and lack of documentation. Result: effectively, unmaintainable, throw-away jobs.

The good news is, as discussed, there is a remedy: Take the time to define standards, or work with a supplier who uses a proven methodology based on established standards and quality-centric processes…ideally processes that can be templated and reused.

Re-usability of processes (i.e. “templates") should be your objective. Ensure that in your environment, your team lead is responsible to establish a set of skeleton templates (say 5-10?) that 95% of all your data migration mappings can be based on. “Skeleton” templates means that they are pre-populated with the parameters (that’s “placeholders” for the project-specific values) – these skeleton templates contain no table structure information – just as much development that can be reused in all cases.

Once you have this in place, you can quantifiably calculate substantial cost savings just from having these templates in place… from every project.

Really.

Sliced or Shaved? Avoiding spreading your BI team too thin

 Post written by Chris S., BI Consultant at Ideaca. Read more about BI on his blog: The Outspoken Data Guy.

As a consultant with a background in Agile, I often get questions about how Agile can be used to solve certain problems that people are having with their Business Intelligence Programs.

I recently sat with a client to listen to some of the issues that they are currently having with their BI program. One of the biggest issues that this client is facing is what I would classify as a simple supply and demand problem. Basically their team of around 8 people cannot keep up with the demands of developing and sustaining their BI/DW environment in what is a large organization. The main question for me was could Agile help solve this problem. In my experience, Agile cannot solve the problem directly but it can be used to highlight the root cause.

This is a very common problem that BI programs face. It is the fact that teams are often small relative to the size of an organization and are also too small to manage the tasks that they need to perform to grow and maintain a BI portfolio. And in certain circumstances it is compounded by the fact that teams are often staffed with the wrong skills sets needed to grow and manage a BI offering.

So how can Agile help?

With proper tracking and monitoring of what the team does on a daily basis, teams can begin to gather data on what types of work the team is doing on a daily basis. What we often find is that at a certain point new development will stop coming from small teams charged with both the development and sustainment of a program as they cannot keep up with both. The ironic thing is that most BI managers have no real data to back this up. So taking advantage of some of the rigor around agile in terms of tracking what is done on a daily basis and how slowly new work burns down, one can begin to understand and report better on how time is spent and in fact how little time is available to delivering new functionality.

You've Collected Data...But Now What?

Post written by Peter T., Management Consultant at Ideaca. Read more about visibility on his blog: Visibility.

The list of technologies that allow us to capture vast amounts of data is quite extensive. This list varies in magnitude of use and exposure within organizations. Companies today can, and most often do, use multiple means of collecting data, such as: Spreadsheets, Databases, Operational specific Software, Enterprise Systems; ERP, CRM, HRM, Various Portals; Personal Portals, News Portals, Enterprise Information Portals, Self-Service Portals, e-Commerce Portals, Collaboration Portals… And the list goes on and on.

It is very evident that companies are really good at collecting data. Whether the data management function within an organization is primitive or advanced, gathering data in spreadsheets or in elaborate enterprise systems and databases: the majority of organizations are great at data collection. Hard copy, Soft Copy, e-Copy, web displayed; data in all forms, shapes and sizes is being collected at an enormous pace. If you can write it, print it, draw it, type it, sketch it, draft it, and capture it, you can rest assured it is being gathered.

The question is not what data to capture next, but now that we have all this data, NOW WHAT?  

Once data is collected, do organizations use it in the most efficient way? The overarching question is: now that you have all this data, what value are you getting from it? The following are five steps that will assist organizations in gaining the most value out of their data.

STEP 1 – IDENTIFY YOUR VALUE DRIVERS

Before we can successfully answer the question of value derived from data, we need to understand what the value drivers are for an organization. Are the value drivers; profitability, reputation, market share, productivity, customer service? The list can certainly be expanded upon. Getting value out of your operational data is imperative, but if you don’t link the data that you are capturing with the value drivers of the organization, you could be spinning your wheels and not realizing the full potential of your systems and efforts.

STEP 2 – LINK DATA TO YOUR VALUE DRIVERS

The next step to ensuring you are making intelligent decisions based on relevant information is to verify that all data captured is linked to the value drivers of your organization. Every piece of information that is collected and processed is intended to provide new intelligence, thereby improving the positive outcomes of critical operational decisions. The way to optimally perform this is by linking significant data retrieval and performance functions to your value drivers. Furthermore, these links can be expanded upon where multiple associations exist.

Dissecting the specific data captured will allow organizations to assess data accuracy, timeliness, depth, and most importantly the interconnection with various other data sets and systems. The key is to ensure that crucial data is modeled to display how it is gathered, at what interval, and how data from one source is related to data in another.

STEP 3 – ANALYZE

Now that you have modeled all significant operational data, you will be able to focus on the highest impacting pieces. By designing new processes or re-engineering solutions, you will be able to increase the usefulness of the information. The analysis will be focused on interconnecting data, assets, management, and operational systems. This exercise will require a thorough look at the data to ensure that standards are in place and the collection of information is from across the entire organization in order to ensure corporate-wide accurate reporting. The outcome from the analysis is to design a roadmap that will focus on operational improvements tied directly to the value drivers of the organization. This can be initiatives such as: identifying ways to increase production, improve safety records, decrease maintenance costs, improve asset visibility, reduce compliance risk, and much more.

STEP 4 – SOLUTIONING

After defining opportunities to improve operations, organizations need to devote some time to developing a realistic plan of achieving these goals. A key step in the Solutioning process is developing the overall vision and detailing the various components of development in palatable sizes ready for execution. Increasing the capabilities of the organization through the design of new automated systems or enhanced analytics, processes and interfaces are just some of the improvements that can be realized. If structured properly, these enhancements can provide the organization significant wins by capitalizing on the information captured along the way.

Information Technology has assisted organizations in navigating from simple and non-existent data management environments, to an optimized level where data can be used for benchmarking and analysis to drive their strategic and operational initiatives. This cannot be successfully done however without ensuring that all data captured provides value and that value is something that drives the automation, analysis and design of advanced systems and integration opportunities. The following diagram depicts the stages of data management and provides a visual of where organizations currently are and how far they may have to go in order to achieve the most optimal level of data management:

Setting expectations with clients (part 2)

Post written by Steve J, Project Manager at Ideaca

Setting Expectations with Clients Part 2 is a two part blog series on managing client expectations. See here to read part 1.

In my previous blog post, I told a story about a project I was involved in that required expectations to be managed and the project to be pivoted. In this blog post, I will discuss four key factors in managing expectations that I have learned throughout my career.

1. Communication is a key factor when working with clients. No two clients are the same, some will hire a team to complete a specific task, while others will want to be fully engaged. Learning how and when to communicate with these different groups is crucial to project success. Fully engaged clients may require daily or even hourly updates on project status while more removed clients may only want occasional updates. Knowing your client and making decisions on when and how to communicate is an important way to manage expectations. Some of the effective communication mechanisms that we use on projects can include: daily stand-up meetings with the entire project team (including the client), weekly status reports with all items completed that week, any issues or decisions that arouse, and a budget burn down showing progress. Email is a very handy tool for communication, however if a portal (SharePoint or something similar) is available, this technology will allow for much tighter control over issues, questions, and decisions on the project, without the issues with email branching off into numerous threads and side conversations.

2. Building a relationship on honesty is necessary. Right from the first meeting, the client should understand what you can and cannot do for them. As much as we wish we could offer solutions to every problem, the reality is we can only do what is within scope and within our knowledge and skills. While digging into the details of what that desired end state will be, it is important to discuss what is possible and what is not. These discussions will affect the project and the decisions made will impact the deliverables, the timelines and especially the budget. The hope of this is to catch and identify any areas of the project that may lead to deliverables not being delivered, budgets and time frames expanding and missing expectations.

3. Deciding the roles and responsibilities for the project team (including the client team members as well) is a major task that should be completed at the start of the project. From the start of the project, setting up a project Governance is a great way to start. Project Governance will outline the relationships between all groups involved in the project, define the flow of information from the project to all key stakeholders, and ensure that there is appropriate reviews of all issues during the project. Another useful tool is to create a RACI Matrix. A RACI matrix describes the participation by various roles in completing tasks or deliverables for a project or business process. It is especially useful in clarifying roles and responsibilities in cross-functional/departmental projects and processes. Key contacts for the different areas of the project should be also defined. It’s important for everyone to know who to go to for questions and issues with certain aspects of the project and to keep these people consistent from kick off to go live. In projects I have been on, we start the project with an internal kick off meeting before we meet with the client. This ensures everyone is on the same page and has a shared understanding of the project and statement of work. On the first day of work with the client, we begin with a similar meeting. At this point we can assign the key contacts on my project team as well as the clients’ team. Everyone involved on both sides will have had chance to meet and put a name to the face and to their role.

 4. “When is the due date and when can we launch this project?” should be questions that are asked and answered early on. Making sure to develop a realistic project plan adds transparency to the project, shows when the milestones are due and provides everyone responsibilities and accountabilities. The project plan is a living document. It should exist to provide everyone an up to date snapshot of where things are in the project. If there are delays or changes made, the project plan should be updated and discussed with the client immediately. When it comes to managing expectations, establishing clear and consistent deadlines are a necessity. The sooner deadlines are set, the sooner the team can begin to work to ensure they meet them.

Every new project allows for lessons learned or growth, both for the team and the individual. Personally, I have learned so much about managing expectations from every project I have ever worked on. Every client is different and understanding how to work with them is part of having a successful project. Communications, honesty, assigning tasks and confirming deadlines are four key aspects of managing expectations that are part of my expectation management strategy for every project. Ultimately you want to start the project the same way that you finish it: with happy clients!

Setting expectations with clients

Post written by Steve J, Project Manager at Ideaca

The Oxford Dictionary defines “managing expectations” as: “Seek to prevent disappointment by establishing in advance what can realistically be achieved or delivered by a project, undertaking, course of action, etc.”

Almost every part of our lives is surrounded by expectations, either ones we set for ourselves or ones that were set for us by others. When it comes to consulting and being on a project, every part of the project experience will be influenced by expectations. There will be expectations around the project as a whole, the deliverables, the time and especially the budget. It is the responsibility of the project team and Project Manager to ensure that the client has a clear and accurate understanding at all times. The overall success of any project will be linked to the expectations of the client, the understanding and efforts of the project team and how well these factors align. At the end of a project, the client’s satisfaction with the delivered project will determine its success.

I have worked on a variety of projects, including those with high expectations from the client. In one project the client as a whole had very little technical and user knowledge of the system that we were implementing for them. They were very much involved in the project and took on many tasks. One of the tasks that was completed by the client was the design and layout of the new system. This task was completed before the project team started on the project and with limited knowledge of the system. The designer was able to design the pages to match that of a SharePoint look and feel without any operational knowledge of the system as a whole. The project team was not a part of this design and the client wanted the end result to look and operate the same as they had designed it. When our project team realized this, we had to pivot our work to align with a more customized solution rather than an out of the box implementation as originally expected. Communication and managing expectations became a critical component of this project, especially since the plans and timelines shifted substantially. Working closely with the client, being honest about timelines and budget and reviewing changes before work continued were very important. Our open communication kept the client informed and the project team on the right track to meeting their needs. In conclusion, the client was very happy with the end product and assured us that we had exceeded their expectations.

Through my experience working with a variety of clients in different situations, I have developed an understanding of how to best manage client expectations. As in the example above, the situation could have turned out with one, or both parties upset about the changes in plans. But by effective expectation management, we were able to explain to the client why things needed to change and what exactly we were going to change. This turned a potentially problematic shift in work into a positive improvement of work.

In my next blog entry, I’ll cover the four key factors in managing client expectations that I have learned throughout my career. Check back next Tuesday, September 17 for more! 

Statement of Direction for Dynamics AX 2012 "R3"

Microsoft recently released their latest Statement of Direction for Dynamics AX 2012 R3. This new version of AX will be available by Q4 of 2013 and will come with a number of benefits and new capabilities. These include:

Warehouse Management
Advanced warehouse management capabilities will be introduced including embedded RFID, improved warehouse processing and rate, and route and load planning.

Introduction of Demand Planning
There will be new functionality to support SKU-level demand planning based on the Time Series algorithm of SSAS.

Retail
R3 has a strong focus on retail capabilities, with key areas including mobility, clientelling, ecommerce and social.

E-Procurement
Capabilities for purchasing within complex organizations will be enhanced, specifically in the management and control of the RFX (RFI, RFP & RFQ) processes.

Budget Planning
There will be improvements in budget planning capabilities with a focus on supporting the planning needs of complex organizations.


R3 will offer many new and improved capabilities that AX 2012 R2 does not offer. This new version will benefit large and complex organizations the most, especially those with Distribution and Omni-Channel Retail.

The next major version of AX will be released at the end of 2014 and will be called “Rainier.”


Read the full Statement of Direction here.

Questions? Ask one of our consultants.

Is your website mobile friendly? Here's why it should be.

Many people believe that it is sufficient to only offer desktop computer versions of a website because that’s where people primarily use the internet. However, recent studies by Pew Internet have discovered that this is not the case. Increasing numbers of people primarily use their mobile devices to research or surf the internet. In some cases, these people do not have access to a desktop computer, have to share it, or prefer the convenience of their mobile devices. These mobile-only customers are as valuable as desktop computer users and need access to the same information.

How many people fit into this mobile-only category? A lot, especially young adults between 12 and 29 and low income adults. If your customers fit into either of these categories then it is especially important to make sure your website information comfortably fits onto a mobile screen. Even if your customers do not fit into these categories, more than half of all Americans used their mobile devices to browse the internet in 2012. This means that even if it isn’t your customer’s primary internet method, they may still be accessing your website and information on their mobile devices.

It is important not to force mobile only users to find a desktop computer to access your information. As well, forcing customers to zoom and scroll to navigate a site designed for a much larger screen will only frustrate them and detract from your valuable information and services. The good news is that mobile-only users may access the internet differently but they do not need unique information. The same messaging, content, services and offerings that you share on your website can be duplicated on your mobile site. Even the colors and branding used can and should remain consistent. This means that including a mobile site requires only technical changes and not major messaging or branding shifts.

Embracing customers regardless of the way they browse the internet is the best way to make sure your content is available and accessible. This ensures no potential customers are excluded, no matter the way they choose to browse the internet.

Sources: Pew Internet, Harvard Business Review Blog

Have you adopted mobile and tablet retail technologies?

If you haven’t, you might be falling behind and missing out on valuable opportunities.

Advancements in technology bring changes in retail and the way that people shop. Customers are no longer satisfied with customer service only at the till, promotional offers they don’t relate to and primarily using cash to pay. At the same time, retailers want to save money and gain valuable insight into their customers and how they shop. Retailers and customers can satisfy both of their wants with modern payment technologies.

Retailers face many challenges when considering new payment methods including cost, customer security and the speed of transactions. Growing technologies such as mobile payments improve customer convenience, reduce fraud and help retailers learn more about their customers. As for security, mobile payments offer security levels comparable to EMV, but without the expensive hardware. With the right technology, payments can be made on devices such as tablets. This allows employees to take payments from anywhere in the store without having to move heavy or awkward equipment. Tablet payment technology also offers access to information formerly limited to the till such as available inventory. 

When customers know that providing information leads to an improved shopping experience, they are more likely to provide retailers with their personal data. Retailers can then use this information to learn about their customer’s shopping habits and even customize offers to fit their exact interests. Various technologies are now available to assist in collecting and using this data efficiently. By implementing the right software, you can gain valuable access to your customers shopping preferences and habits, while benefiting customers with customized offers. 

While the future of retail technology is unclear, it is likely that mobile payments and tablet technologies will become more common and the benefits of collecting customer data will become more important. Retailers who adopt modern technologies today will better prepare themselves for the future and coming changes in retail. If you’re interested in learning more, Ideaca has knowledgeable consultants that are happy to discuss what technologies are right for you and your business.