IT Attributes and Metrics
No matter what your business size or model is there remains often a strong case for expanding your company into the areas of new business intelligence systems, big data, internet of things and big data. Existing trends indicate an increase of 50% for big data and the internet of things investment. Similar trends are supported with concern amongst many companies on their abilities to implement and address the challenges they face with such technology.
Here I provide some direct help for leaders to identify the best attributes needed by candidates and some key metric areas for performance management progress to address these new expanding and growth areas of what I call IT 2.0
The leader of such an endeavour needs some specific characteristics:
Simplicity / purity of vision and goal: With such a rapid and fast changing sector with new opportunities it can quickly become a distraction and thus stifle progress. The management leader will need to ensure the simplicity of steps is communicated and linked to the business vision and goal that was agreed at the start of the task.
Set up periodic reviews to ensure the scope, vision and goals are retained and may be pivot adjusted if new significant opportunities arise.
A business has its own culture and so the big data, analytics project leader needs to ensure that these morals, ethics and standards are retained in the actions, scope and methods of communication throughout the project. An ambitious new Big data or Internet of Things or analytics project will be considered already maverick enough action by many so retaining and exemplify the corporate values will allow greater success and acceptance.
Develop and continue to build trust and a high value reputation for upholding the business values and vision.
Large projects risk delay, unforeseen obstacles and stagnation if not been kept relevant and timely. Milestones to ensure hourly, daily, weekly or monthly progress is needed to communicate and share other leaders and stakeholders of the needs of support and resources.
Ensure you make your leader approachable and a killer communicator to highlight the relevance of deadlines.
Mistakes will occur and happen during any large and new project, showing a recovery plan as early as possible for issues develops the trust and willingness to support a solution. Ownership of issues and mistakes is important for the success of a plan. In large corporations finger pointing and a blame game damages trust, credibility and desire to support ambitious projects.
Acceptance that some poor decisions will be made is part of the “learning curve” for any new endeavour such as a big data, analytics or internet of things project. Do not forget it is all new for most of the business and often also the project leader.
Performance Metrics to be considered for your project:
· Data cleansing:
Although not as sexy or perceived as valuable to an organization there is a significant benefit in working through acquired and stored data sets to enhance it’s quality or recognize and understand the quality accuracy of such origins. For instance, is your marketing data accurate within a +- 5% band width?
Many analytics, big data and expanded business intelligence projects increase hours spent in certain reporting areas. However an important metric is to highlight the actual estimated net hours saved from problem resolution.
· Customer Satisfaction
If your project does not effect in some way customer satisfaction then ensure it provides a significant cost saving function for your business!
The quality of decision making through information gained from a big data, business intelligence, analytics or IOT project is important. This highlights the value of the actions and purpose of data gathering. Instead of relying on gut instinct or luck in management decision making, consistent improved decisions can be made.
· Employee satisfaction
Introducing new methods of data gathering and increasing the need for analytics may affect the morale of staff within the business. Some fear will need to be addressed as task function touch points are changed, replaced or removed and increased data backed management decisions are required.
· In an industry that is growing rapidly and the shortage of skilled, experienced staff there remains a need for companies to be realistic and supportive to their chosen project/management leader. Knowledge and skills in R or Hadoop are obviously a significant advantage but will not be possible to find for every business.
· Making use of the supportive consultancy services can provide optimal value to a company that is willing to support the openness required and needed for such a success project.
· To ignore the influence and continued advantage of analytics, big data, internet of things and expanded business intelligence systems is a disadvantage to your business.
I suggest companies review the below key steps for your large data projects as:-
1. Identify the largest high value opportunities. (use 80/20 rule)
2. Establish the correct funding and resource design for your project (budget, time, people, resource, authority)
3. Develop success story through effective value pilot projects (Tell the story)
4. Scale implementation through more business areas (reapply 80/20)
5. Enjoy a transformed business with delighted customers.
Phases of sector investment
Currently a lot of investment is been made in the Fintech and health sectors to benefit user experiences. There remains significant explosive growth potential in Education, Manufacturing, Retail and Entertainment industry’s. I am sure we shall be hearing and engaging more with these areas in our daily actions and interactions at work, home and state levels.
Let me know what challenges you are facing for your projects? What concerns or help do you seek in your business intelligence, big data, analytics or Internet of Things project? I would love to hear from you and am willing to discuss your ideas at anytime.
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Further Reading and Reference:
Infographics with sector overviews, tips and trends on Pinterest
Project management and change management tips on Pinterest
How to define your big data KPI
How to implement great business intelligence analytics