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The ‘2020 Enterprise Data Strategy Blueprint’

This is 2016. If you have been working with a large enterprise in any business function, you now realize that ‘data’ and your perception of the what it is and its usefulness to your enterprise would have taken twists and turns towards a precipice, where you now need to invest in order to survive the digital age.

If you are a CIO, COO, CFO or expression even a CEO, you now realize that your outcomes solely lie in your hands and the ability of your team to succeed over the next few years in the digital age running up to 2020, firmly hinges on your ability to spot and take control of opportunities, in order to create your reality.

Your time has come. You need to act now.

In this article, you will find three simple steps, which you and your organization can connect with in order to chart your course in the turbulent waters of the digital age.

My claim that these 3 steps work for any enterprise is based on my experience with clients across sectors, spread globally and my keen research interests in technology developments in enterprise data technologies globally. Added to this, I have been a keen observer of the transition of mankind from one era namely, the industrial era to the digital era. Lastly, I am a practitioner working with project teams closely including past experience of consulting for the IBM Labs in Dublin, Ireland on various data related client programs.

If you are serious about your organization’s success towards 2020, my bet is that you would want to reconsider and even prepare your way with a sound strategy that will take you towards 2020.

For sure, your organization believes that for most part your data strategy of the past five, ten or even fifteen years has had mixed results. You would have experienced some success as well as some failures. And both outcomes would have given momentum to get to your current circumstances.

The question though is, was it good enough? And can you afford to relay now?

2020 Enterprise data strategy blueprint – steps

STEP – 1 – Data Serves the Purpose

Here’s where you take an honest benchmark of your current position. However good or bad things may be. My belief is that there would equal or more number of successes that your failures. The best thing for you to do is ‘mark’ your position for what it is – nothing less or nothing more!

How would you do this?

Ideally, you will perform a thorough and a detailed review of your current position in terms of people, processes and technologies along with the data footprint in your division or subdivision or business unit, eventually rolling up to your enterprise, corporate or central functions.

You have an option to do a top down or a bottom up approach.

Based on my experience, I would hinge the capturing of the benchmarking exercise on one or two well-known and critical business processes. These facts though, should be a good representation of the overall. Apply the 80-20 rule here. That is 80 percent of the issues are caused by 20 percent of the causes.

This will be your starting position for your strategy. The added good news is that you can define some key measureable metrics here for your journey. A few suggestions are below:

1. Revenue per byte managed

2. Expenditure per byte managed

3. Number of bytes per persons employed

STEP – 2 – Data as a capability

If you consider your organization to be a ‘matured’ business, for sure you will be able to map a ‘capability model’. For example, most businesses will have the following high level capabilities:

· Customer Acquisition

· Customer Service or Product Fulfillment

· Production or Product Management

· Operations

· Human Resources

· Technology

· Finance

· Sales

· Marketing

If like most senior executives and business leaders, you believe that data is going to a strategic capability, you must consider including ‘Data’ in your capability model to begin with.

What are the capabilities that are related to data, which you will need for your organization’s success? Here are a few to consider:

· Data Acquisition

· Data Cleansing

· Data Quality

· Data Transformation

· Data Presentation & Delivery

· Data Security

· Data Storage

· Data Archiving and Preservation

· Data Distribution

· Data supply – internal

· Data supply – external

· Data reporting – statutory

· Data reporting – non-statutory

· Data analytics

· Data visualization

Of course, this is just a list for demonstration and could be customized to suit your specific and relevant circumstances.

A few metrics which could help are:

· Total revenue per data capabilities employed

· Total expenditure per data capabilities employed

· EBITDA per data capabilities employed

· PAT per data capabilities employed

· Total number of persons employed per data capability

From my experience, a simple change in perception itself is worth millions in project budgets, channelized in the right direction. Added to this, by the time that you accept that ‘Data serves its purpose’ and that it does not add any further and specific enterprise value in dollar terms, you would have already acknowledged your need to be data centric. To be data centric, be people centric. (add hyperlink to the other article)

In addition to this, you would have rationalized your widely scattered and fragmented data collection, processing, transformation and consuming activities into a ‘consolidated’ logical bucket, which you can leverage for optimal value creation in dollar terms.

 

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