Making a data driven enterprise – 4 challenges and how to address them
Updated: Sep 30, 2020
Today (big) data and analytics promise organizations and executives to help them increase organizational performance and value. Both are helping organizations to create differentiation and competitiveness in the market. They are helping organizations to grow, to be profitable, to be effective in acquisition and retention of customers and talent alike. More and more organizations are exploiting data driven strategies.
Making of such data driven enterprises is a journey full of challenges and pitfalls –
here are the 4 top in our experience
1. Data volume, variety and velocity
Volume of data is increasing rapidly ( velocity).There is significant opportunity to enhance insight by adding more data sets ( variety).Bigger and larger data help organizations to get panoramic and granular view of organization ,market and industry . It creates better optics on areas of improvements in operations, strategy and execution.
This also brings the challenge of organization’s abilities to collect, cleanse, integrate, manage, access and secure the data. Organizations and executives get overwhelmed with scope of IT teams, skills required and time required to manage these tasks
Another challenge is that not all in organizations may realize the potential of data upfront. Operations executives, for instance, might not grasp the potential value of the daily or hourly factory and customer-service data they possess.
Solution to this challenge is a bit counter intuitive.
Collect everything and then ask, “What decisions could we make if we had all the information we need?”
With choice of right tools and technologies collecting and storing the data can be very inexpensive. Smart tools don’t require the large or additional teams and skills. This approach also prompts broader thinking in organization about potential of data.
2. Lost focus on workflows
Dash boards are good. They help executives to gain insights but those don’t help making a data driven enterprise.
To make organizations data driven enterprise enterprises data and its analysis should be available to all in the enterprise. We should have a dashboard at every level and that means data should be in fabric of work flows. In fact most of the organizations are calling these initiatives as making a data fabric to help all functions make all decisions driven by data
3. Technology and skills
No doubt data and analytics have technology flavor to it. Mostly any initiative in these areas calls for specific technology skill and training – to prepare data, to model it, to analyze it and to present it. High dependency on IT staff, cost and budgetary priorities bring delays and potential failure of these programs
Also skills part have added challenge as to bring domain or function knowledge to technically skilled person
To address these organizations have multiple options – (1) start small with cross functional teams, deliver success, learn and replicate. (2) Invest in smart tools and technologies and empower business users to ‘ prepare and play’ with data (3) start citizen data scientist program in the organization and scale up
4. Data governance
Velocity, variety and volume of data when handled across the organizations bring another “V” in the play – Veracity. Data driven enterprise have no choice but to empower its functions, locations, departments and all stakeholder with data and data sources to be effective. And this calls for robust data governance policy and framework and a mechanism for its deployment and compliance. Organizations are encouraged to leverage people, process and technologies to ensure the access, security, quality and management of data