The following information management maturity challenges are verba tim those articulated by participants in Gartner EIM Maturity workshops throughout 2016. Information leaders should anticipate these kinds of challenges and resistance, and take sufficient measures to avoid or overcome them.
Vision Challenges
Information is seen as a source of power
Information is managed in silos
Data fiefdoms
People spend time arguing about whose information is correct
People spend time arguing about who owns data
Little effort to seek uniform availability of information assets
A general acknowledgement that information management (or lack thereof) is a serious problem
Efforts by IT to formalize objectives for information availability are hampered by:
Culture
Contradictory incentives
Organizational barriers
Lack of leadership and executive support
Different types of information are still treated and managed separately
Poor awareness of exogenous data such as that from public data sources (open data), data brokers, or social media
Information is seen as disposable
Information is poorly linked across business areas or applications
Information is not perceived as a fuel for innovation and transformation
Information is not perceived as a competitive differentiator
Information is not a central component of business strategy or enterprise architecture
A focus only on Mode-2 (transformation) than on Mode-1 (operations)
Customers and partners are not involved deeply in defining information uses
The language of information is imprecise, and dialects differ throughout the organization
Strategy Challenges
IT taking the reins for information management
A static, annual planning process
Too much planning, not enough doing
Information hoarding or begrudged sharing by individuals and departments
Lack of executive support and executive-level leadership (e.g., no CDO or similar)
Obliviousness to what information exists
Vision is lacking upon which to base a strategy
EIM enablers have both process- and people-oriented gaps
Being too focused on technology
Executives are consumed by expense management
Controls and standards get in the way of information enablement
Corporate strategy is set without consulting information leadership
An ill-defined or incomplete information management organization
Lack of funding
Information only being defined in terms of the value it brings, not its intrinsic characteristics
No consideration of the larger info-ecosystem of partners, suppliers, and customers
Information strategy being a separate work task, poorly linked to business operations
Information Metrics Challenges
Measures and goals are purely subjective
The achievement toward goals is rarely tracked, at least in any quantified way
Information management is not an IT budget item, and certainly not an enterprise budget item
Simple, often predisposed, cost-benefit models are used to justify independent information management investments, but not collectively
Cost-benefit and ROI metrics and prioritization merely are part of IT projects
Priorities and goals are based on:
Influence peddling
Failure prevention
User surveys
Expense reduction, or
Scaling infrastructure performance or capacity
A proliferation of mostly incompatible nonfinancial metrics
Qualitative metrics don’t link to business KPIs
Data quality is not measured or performed only downstream for specific IT or business projects
Information value, cost, and risk go unmeasured
Information is not treated as an investment (e.g., an information portfolio)
Governance Challenges
The culture allows few official (if any) policies to exist for the handling or use of most information, other than those required by law and industry regulations
A lack of governance culture as evidenced by limited governance in other domains
Ad hoc data quality efforts are favored or simply budgeted that way
A lack of data definitions (metadata) result in low data trust and usage, and therefore no imperative for governance
Emerging policies are mostly for particular information silos.
Information is too easily copied, resulting in information sprawl
There is no mandate or precedence for monitoring or enforcing policies, which leads to policies being regularly circumvented
Information owners (or “trustees”) are assumed, not actually designated
Limited authority for anyone entrusted with information to do anything about its quality or policies
Lack of sponsorship or organizational structures and budget for information governance
A “project” mentality in which information is merely an input or output for that process
A fixation on policies, rather than a well-crafted, integrated hierarchy of precepts
A fixation on control, rather than governance as an enabler of information
A lack of defined information principles
Lack of information inventory—not knowing what needs to be governed
Data stewards without advocacy as part of their role
Data stewards (for business information) who are part of the IT organization
IT running the information governance initiative
People (Organization and Role) Related Challenges
Information-related responsibilities are resourced on an application-by-application or project-by-project basis
Business people are resigned to circumvent IT in an attempt to source and manage their own data, or must queue up in the IT backlog
Lack of change management as part of EIM initiatives
A lack of pooled or centralized database administrators, data administrators, information architects, data modelers, etc.
The above resources being part of the IT department
Information not being perceived as an enterprise resource or asset (hoarding)
Lack of budget and executive sponsorship for such roles or structures
A fixation on traditional information-related roles at the expense of emerging and increasingly important roles such as the CDO, data steward, information curator and information product manager, master data manager
CDOs without budgetary authority or resources beyond a small “office of the CDO” team
A lack of understanding of the larger information ecosystem beyond the immediate enterprise
Information management being perceived as a cost center rather than as a revenue generator or business innovation enabler
Process (Information Lifecycle) Challenges
A lack of understanding of information even having a lifecycle (Most managers and users of see information or part of it at a certain point in time, or they don’t see it at all as it’s embedded and obscured in systems and applications.)
Information silos where it languishes
Information is copied with wild abandon rather than being accessed in place
A tendency toward local (single application or system) efficiencies
Information is deleted early due to a lack of infrastructure or policy
Infrastructure asset budgets are planned independently of information assets—which usually are not even budgeted
Data integration may be effective in linking disparate sources, but efforts to semantically align them are lacking
Metadata management is mostly manual (e.g., spreadsheets) and is specific to information assets for specific projects or applications
A lack of interest or perceived business importance in defining information flows or architecture
A lack of data architects owning or driving the definition of information asset lifecycles
Little concern, planning, or innovation regarding older information
An impression that information lifecycles are IT workflows or tasks rather than business processes
No means to value information assets or balance this against their assessed risk