What if you are your project’s biggest risk?

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

“A little knowledge is a dangerous thing” – Alexander Pope

While I was studying to become a project manager, I believed what A Guide to the Project Management Body of Knowledge (known as the PMBOK) and my professors had to say as the gospel truth: a project is a project is a project. It didn’t matter that I had no experience building a bridge, planning a wedding, or configuring a database server…I was going to be a professional project manager, and that meant that I could manage anything (so long as I followed the 5 phases of the PMBOK and did everything that the 11 knowledge areas told me to do)!

For a while, that was the case. I made sure that all of my projects had strong technical people that were good communicators so as to provide good estimates, identify risks early and often, and manage the details of the deliverables. I was able to focus on managing at the executive level, facilitating problem resolution, and provide project administration support.

But then it happened – I was assigned a project where I had a little bit of technical knowledge, but not much, and was paired with some intermediate resources. They were technically strong, but were relatively inexperienced in working in a large project setting. At the time, though, I did not know this and just assumed that they were as skilled as every other project team I had worked with in the past. When we sat down to plan, I used the same process as with my other project teams; when we ran status meetings, I used the same process as with other project teams; and when we identified risks, I used the same process as with other project teams. However, development activities continued to miss dates, and my inquiry into what went wrong with the team yielded answers like “we don’t know.”

As a result, I used my fairly limited knowledge of the subject area to help plug the gaps that I saw. When asked questions by the sponsor and subject matter experts, I gave them answers that I believed to be true without consulting the team. When asked questions about the technology by the IT operations team, I gave answers that I had heard given in the past without consulting the team. And then things started to go really wrong. The client kept asking the team about things that I had said, and were told opposite things, the project team kept freezing me out of discussions, and my Program Manager came back to me with feedback that I was about to be fired from my project.

At that point, having a team that was not as strong as my previous teams was not the issue. My assumptions, silo’d decision making due to frustrations, and unfair expectations of the team introduced a myriad of risks, which of course I didn’t capture in the risk register, to the deliverables. These risks almost immediately became issues when I communicated out without consulting the team. I was the issue. I was the project’s biggest risk to scope, schedule, and budget.

So what should I have done?

1. Don’t assume you know everything

Even though I had some experience with the technical area, and was a well seasoned project manager, I should not have assumed that I knew better than the team. It’s ok to say “I don’t know”, so long as you promise to get the answers and follow up.

2. Consider your team’s requirements

Instead of forcing the team through processes that worked well for other teams, I should have considered their requirements in the locus of their experience level. During the “forming” and “storming” phases of team development, I should have been asking questions rather than imposing processes. When I saw a process that did not work, I should not have knee-jerked into command and control mode; rather I should have worked with the team to re-assess.

3. Recognize that you cannot push a rope up a hill

As a project manager, it is your job to facilitate successful project outcomes. Unless you are explicitly performing a specific role on a project team, your only true deliverables are status reports, communications, and facilitated sessions. It is up to your team to deliver the technical content. If there are performance issues, talk to the team members (and then their managers if required). If there are scope concerns, talk to your sponsor. If there are resourcing concerns, talk to your project management office. Do not try to own the issue; try to facilitate resolution.

In the end, I focused heavily on #2 and #3 and struggled with #1 through to project closure. After giving answers for so long, it was hard not to. As far as the project was concerned, after a re-baseline, it was delivered to scope, schedule, and budget constraints.

What type of learning opportunities have you had through projects? How else could a Project Manager be the project’s biggest risk?

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?

Ideaca To Become Hitachi Solutions Canada!

Same people, same values, different name

On December 2, 2013, Ideaca was officially acquired by Hitachi Solutions and will become “Hitachi Solutions Canada.” As Hitachi Solutions Canada, we look forward to providing our customers with a wider array of proven industry solutions and access to global resources.

"Ideaca is extremely pleased to join a global brand with the outstanding caliber of Hitachi Solutions,” said Muneer Hirji, newly appointed president of Hitachi Solutions Canada.

“We look forward to integrating our experience and strengthening our synergies to bring great industry-focused solutions to both regionally-focused and multinational companies throughout Canada. With its long history of technology excellence, industry leadership and employee-driven culture, Hitachi Solutions will make a great home for our employees.”

Our name may be changing, but our people and our values will stay the same!

Click here to read more.

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.

The importance of a shared vision

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

In a post from my series “Advice for Junior PMs," I touched on the concept of saying what you mean when working with your project team. The same concept should be applied when communicating outside of your project team.

There’s a fairly common graphic that gets passed around IT departments, and it’s somewhat self-deprecating. It shows that project teams tend to not understand what the customer needs – which is endemic of lacking a shared vision.

This graphic makes me cringe every time I see it.

As we all know, a project is a temporary group activity designed to produce a unique product, service or result. However, more often than not, project teams take an “I know best” view of the world when designing solutions for their customer.

A strong project manager will not only sit with their customer to understand what is required, but will bring the whole project team along to understand as well. We all have our own perceptions and filters, and as a result may play broken telephone.

At this point, you may be asking if a shared vision is different from the project scope statement. It is, in that the shared vision is what the customer will see as the product, service, or result of the project, whereas the project scope is everything that will be delivered (including training, documentation, organizational change management).

To create a shared vision of what the project will produce (be it a unique product, service, or result):

1. Bring everyone to the table to ensure open communication

1. Define what is to be produced in simple language – do not say “we are going to produce a tree swing,” and leave it there, say “we are going to produce a tree swing, which is comprised of a tire hanging from a sturdy branch of a large oak tree by a piece of polyester rope.”

1. Involve the customer in design meetings. Subject Matter Experts (SMEs) should definitely lead, but should be eliciting feedback so that the customer’s requirements are re-confirmed by the team.

1. Revisit the shared vision often. Ask your customer at difference acceptance testing points if what is being developed meets the shared vision.

Most importantly, communicate the shared vision often. Use it as the first line in your status reports, use it as part of your elevator speech, and when people ask you what you are working on, relay your project’s shared vision.

What are your tips for creating a shared vision? What have you seen work well? Do you have any stories of spectacular failures? Share your tips and stories below!

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.

The data has the answers

Post written by Evan Hu, Co-founder of Ideaca. View his blog here: evanhu.wordpress.com

In a 2001 research report by META Group, Doug Laney laid the seeds of Big Data and defined data growth challenges and opportunities in a “3Vs” model. The elements of this 3Vs model include volume (the sheer, massive amount of data or the “Big” in Big Data), velocity (speed of data processed) and variety (breadth of data types and sources). Roger Magoulas of O’Reilly media popularized the term “Big Data” in 2005 by describing these challenges and opportunities. Presently Gartner defines Big Data as “high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.” Most recently IBM has added a fourth “V,” Veracity, as an “indication of data integrity and the ability for an organization to trust the data and be able to confidently use it to make crucial decisions.”

The volume of data being created in our world today is exploding exponentially. McKinsey’s 2012 paper “Big data: The next frontier for innovation, competition, and productivity” noted that:

• to buy a disk drive that can store all of the world’s music costs $600
• there were 5 billion mobile phones in use in 2010
• over 30 billion pieces of content shared on Facebook every month
• the projected growth in global data generated per year is 40% vs. a 5% growth in global IT spending
• 235 terabytes data was collected by the US Library of Congress by April 2011
• 15 out of 17 sectors in the United States have more data stored per company than the US Library of Congress

IBM has estimated that “Every day, we create 2.5 quintillion bytes (5 Exabyte) of data — so much that 90% of the data in the world today has been created in the last two years alone." In their book “Big Data, A Revolution That Will Transform How We Live, Work, And Think,” Viktor Mayer-Schonberger and Kenneth Cukier state that “In 2013 the amount of stored information in the world is estimated to be around 1,200 Exabytes, of which less than 2 percent is non-digital.” They describe an Exabyte of data if placed on CD-ROMs and stacked up, they would stretch to the moon in five separate piles.

This sheer volume of data presents huge challenges. For time-sensitive processes such as fraud detection, a quick response is critical. How does one find the signal in all that noise? The variety of both structured and unstructured data is ever expanding in forms: numeric file, text documents, audio, video, etc. And last, in a world where 1 in 3 business leaders lack trust in the information they use to make decisions, data veracity is a barrier to taking action.

The solution lays ever more inexpensive and accessible processing power and the nascent science of machine learning. While Abraham Kaplan (1964) principle of the drunkard’s search holds true: “There is the story of a drunkard, searching under a lamp for his house key, which he dropped some distance away. Asked why he didn’t look where he dropped it, he replied ‘It’s lighter here!’” A massive dataset that all has the same bias as a small dataset will only give you a more precise validate of a flawed answer, we are still in early days. Big Data is the opportunity to unlock answers to previously unanswerable questions and to uncover insights unseen. With it are new dangers as the NSA warrantless surveillance controversy clearly exposes.

I have had the privilege of listening to Clayton Christensen speak several times. In particular he has one common through line that stuck with me and forever embedded itself in my consciousness. “I don’t have an opinion. But I have a theory, and I think my theory has an opinion.” I believe the same for Big Data. The data has an opinion, the data has the answers.

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.