Treat data as an operating capability
A leadership team should not need three spreadsheets and several private messages to understand a program's commitments, resource needs, or operational risks. Yet growing life-science companies can accumulate exactly that environment: capable individual tools, inconsistent definitions, and information that is difficult to reconcile.
The first digital investment is not necessarily another application. It is agreement on the decisions the business needs to make and the information it must trust. Technology becomes useful when ownership, definitions, and working practices are clear enough to support those decisions consistently.
Design for the next decision
Start with a few recurring questions. What have we committed to a program? Which equipment or service constraints could affect the next milestone? Who can access sensitive research? Which external partner owes the next deliverable?
For each question, define the decision it supports, the necessary level of detail, and how current the information needs to be. Not every dashboard needs real-time data. A dependable weekly view may be more useful than a continuously refreshed report with uncertain definitions.
Create a simple information map:
- The business question and the person accountable for acting on it.
- The authoritative source for each important data element.
- A shared definition, including units, status categories, and time periods.
- The owner responsible for accuracy and resolving discrepancies.
- The update frequency and how users can recognize incomplete or stale information.
- Access, retention, and recovery expectations appropriate to the information.
This map makes gaps visible before the company spends money automating them.
Reconcile the meaning before connecting the systems
Consider an illustrative program-spending review. Finance reports invoices received, the program lead tracks approved purchase orders, and an external partner reports work performed but not yet billed. The three figures differ because they answer different questions, not necessarily because one is wrong.
A useful operating view distinguishes actual expense, open commitments, and forecast remaining work. Finance and program leadership agree on definitions and reconcile exceptions. Only then does connecting systems make the result more dependable.
The same reasoning applies to sample identifiers, equipment status, vendor names, and employee records. Choose consistent identifiers and establish who can change them. A dashboard cannot repair ambiguity in the information underneath it.
Build protection into normal work
Treat access and continuity as part of the operating design, not a later cleanup project. Know which systems hold critical information, assign business owners, and define how access is approved, reviewed, and removed when roles change. Include external collaborators rather than assuming their access will expire on its own.
Use a proportionate cybersecurity review to identify the safeguards and recovery arrangements your environment needs. The NIST Cybersecurity Framework 2.0 Small Business Quick-Start Guide offers a starting point for organizations developing their cybersecurity risk-management approach. It is a planning resource, not a product certification or a guarantee of security.
Ask service providers to explain their responsibilities and the company's remaining obligations. A hosted platform does not eliminate the need to understand data export, recovery, account administration, and what happens when the relationship ends.
Choose systems for adoption and change
Evaluate a proposed system against a real workflow, not just a feature demonstration. Have the people who will maintain the records test the work they actually perform. Examine implementation effort, integrations, administration, training, and exit options alongside subscription cost.
Avoid both extremes: a collection of disconnected tools with no ownership, and an enterprise platform whose complexity exceeds the team's capacity to operate it. The right system is one the organization can use reliably now and extend when a meaningful need emerges.
As regulated activities become part of the business, involve Quality in determining intended use and applicable record and system requirements. Do not assume that a vendor's compliance language establishes suitability for your specific workflow.
Put trusted information before AI automation
An AI assistant can help summarize approved information or prepare a draft analysis, but it can also make conflicting source material sound convincingly consistent. Start with bounded uses, approved data access, traceable sources, and a named human reviewer.
Keep confidential source material within approved environments and review generated content before it influences an important decision or becomes public. Improving the underlying records and ownership remains valuable whether the next interface is a spreadsheet, a dashboard, or an AI query tool.
Operational takeaway: build one trusted decision view
Select one question leadership revisits every week. Agree on its definitions, appoint a business owner, reconcile the sources, and establish a repeatable update and review process. Then automate the parts that are stable.
Measure success by less time spent reconciling competing versions, fewer unresolved discrepancies, and clearer decisions—not by the number of systems installed. A digital foundation earns its value when people can explain where an answer came from and act on it with appropriate confidence.
See this in practice
IT infrastructure planning and full remote work and data access formed part of this laboratory relocation from Steve Michel’s prior leadership experience.