Data is both the unprecedented opportunity and risk facing in today’s CIO, the attitude to data decides CIO’s multi-faceted persona and influence, CIO role is transforming from infrastructural manager to handle transactional data into the visionary business strategist to gain data insight and foresight via big data, and make strategic prediction & priority.
1. Top Five Challenges of Data Growth
- Cost Challenge
Data related cost include storage cost, power & cooler cost, administration cost, database license cost etc, it takes about 7% to 10% of IT annual budget, though modern storage technology such as virtualization/de-duplication/thin provisioning/ tiering/cloud provide the advanced, cost-effective solution for the enterprise data demand, CIO need forward thinking the scalability and well-calculating ROI for the long term.
- Data Full Life Cycle Management
Data/Information Lifecycle Management is the discipline around the planning, collection, creation, distribution, archiving of information, up to retirement and deletion/destruction, based on business and regulatory requirements. Data quality, data cleanse, MDM, data integration, data warehouse, data synchronization., etc are the fundamentals to decide the success of your business intelligence/analytics projects.
CIO should craft the right strategy, methodology and technology to manage the data and create effective link between data and business strategy.
- Data Security/Disaster Recovery
From varies of industry surveys, CIO’s top concerns are disaster recovery (72%) and reducing the risk of data loss, theft and corruption (65%)—understandably so, since disaster recovery is a necessary part of preventing or mitigating data loss, especially the emerging cloud computing enables more agile business via fast delivery and OPEX model, however, data security is still the top concerns to adopt the cloud. CIO need invent the trend and avoid the pitfalls.
- Data Governance
As the data (weather structured or unstructured), is aggregated and consolidated, to successfully leverage the data across the organization, it must be treated as an enterprise asset. Data governance provides a common language that makes it possible to understand and act on information across functions and lines of business. CIO’s success pill –take with governance: converge data/IT governance with enterprise governance.
- Data Analytics/BI
Perhaps Data analytics/BI is one of the most powerful secret weapons in digital era to out-weight and outthink your competitors, the market-leading companies see their ability to exploit analytics as the distinctive capability—the agile business processes and the integrated capabilities that together serve customers in ways that are differentiated from competitors and that create an organization’s formula for business success.
It’s value-added CIO’s new battleground to use BI/Advanced analytics such as predictive analytics, context/location base analytics, to craft dynamic Links between data & business strategy, and cultivate the analytic learning culture surrounding in the organization.
2. Five Senses to Dig through Data, Make Strategic Analysis
Where is data coming from? Operation data such as financial data, logistic data and HR data come from organizational supply chain, customer data from CRM/marketing, and big data from social/mobile/cloud/RFID, they are the raw gemstones, and strategic asset for modern corporation.
· Listen to Data: hear customers’ feedback, and employee’s opinions, one voice maybe a noise, but collective data is chorus, and statistic analytics such as gap analysis (helps companies compare actual performance with potential performance) will directly drive such as pricing strategy, customer insight, supply chain optimization and strategic workforce planning
· Touch Data: Feel the pain point and customers’ touch point, modern enterprises are mostly over-complex, integral data cross the organization will touch the ground, help optimize the process via root cause & simplicity analysis, improve business capability via simple process, not simpler (Einstein’s philosophy).
· See Through Data: like tea leaf, data can envision the mega-trends, data insight and foresight provide the scientific scenario analytics via asking what are the trends, what is going to happen, and what are the best could be happened., etc.
· Taste Data: crunch the data or taste the sweet spot: to further explore Porter’s five forces strategic analysis, and also discover his recent theory about transforming from CSR (corporate social responsibility) to CSV (corporate social value) via impact analysis: how will your organization make social/economic/regulate impact, become the strategic shaper and rule maker for the long term.
3. Five Strategic Crowns Weaved via Data Gemstones
Companies are pushing hard to get the benefit from their huge investments in IT. The effective enterprise information system focus on building the missing bridge between strategy and operation, apply their data in a focused, repeatable and structured way to support decision-making/analytical capability, the business agility and the art of possible
- Customer Strategy :
- Talent Development Strategy :
Unleash the employee full potential via above talent gap analysis, strategic workforce planning, IT should take the leadership to establish the communication platform such as social/enterprise 2.0, to encourage employee sharing knowledge & idea, inspire learning culture, and manage the modern metric system to evaluate talent via multi-dimensional lens, to make sure the right people do the right job at the right time, and manage the talent pipeline via analytical perception.
- Innovation Strategy:
“Innovation is the execution of new ideas that create business value."
Gartner's definition
a) Innovation Volume, which is the number of product ideas that are launched in the market;
b) Innovation Efficiency, which is the proportion of those product launches that are successful, as defined by meeting their net present value (NPV) goals for value creation.
A data-driven, driver-based risk management approach uses scenario analysis to prioritize drivers in terms of risk. These drivers also focus risk monitoring, remediation and governance so the organization knows where its key risk areas are and how they are organized. The effective IT risk management will deliver four As: Availability, Access, Accuracy, Agility.
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