Is Digitalization a Tech Problem or a Management Problem?

Technology capabilities and limits

Technology can build a platform for data storage and retrieval, design automated workflows that move requests between steps, and generate reports and charts. It cannot decide business rules such as which customers are key, the sales‑follow‑up process, or which department maintains the data; those decisions require business‑savvy managers. When a customer‑management system is built without clear business definitions, the system may be well‑engineered but misaligned with actual needs.

Management responsibilities in digitalization

Management must define approval permissions for expense reimbursement, specify which expense levels require which approvals, and determine the statistical scope for sales data (contract‑based vs cash‑based). These definitions directly affect system design.

In data analysis, management must clarify the statistical basis, decide whether to separate product‑line data, and ensure consistent definitions; otherwise the resulting data are unusable.

Problems from poor tech‑management alignment

Mismatch between system functions and actual needs – The tech team may develop features based on an ideal template, but business users find the new system incompatible with their habits, leading to low adoption or workarounds.

Confused responsibilities – After go‑live, no one knows who should resolve data errors or unblock stuck processes, causing delays.

Data inconsistency – Different departments enter the same data with varying names, formats, and meanings, making downstream integration impossible. The author’s team previously solved this with FineDataLink, a data‑integration and task‑scheduling tool that cleanses and aligns heterogeneous data before loading it into a unified warehouse.

FineDataLink URL: https://s.fanruan.com/64fht

Cooperation model

Start with a concrete business problem – Identify a pain point (e.g., real‑time inventory visibility) and deliver a small tool that solves it, demonstrating digitalization value.

Close collaboration – Include true business experts in the project team, not only senior managers, so they can convey detailed requirements. The tech team must also explain implementation constraints and limitations.

Management participation in rule definition – At critical stages such as workflow design and data‑standard definition, leaders need to make clear decisions that guide subsequent development.

Build a solid data foundation – Create a unified data dictionary with unique definitions for key terms (e.g., “order”, “customer”, “project”) and assign clear ownership for maintenance.

Adjust policies to match new systems – If a new system adds data‑entry steps, performance assessments should reflect that; if responsibilities shift, job descriptions and reward structures must be updated.

Conclusion

Digitalization is neither a pure technology problem nor a pure management problem. Successful transformation requires both sides to understand each other's language, collaborate on rule definition, and align systems with business processes.