Business Intelligence Strategy: Developing and Documenting Your BI Roadmap

By Alex Hossner , Product Lead at BI:PROCSI

Introduction

Successful BI is about solving real business problems by delivering insights that matter to your people. It's not just about fancy dashboards and technical wizardry.?

This guide cuts through the noise and focuses on developing a BI strategy that creates value for your business and actually moves the needle. We're talking understanding your users' and customers’ needs, aligning with product strategy, and measuring success in impact - not just metrics.?

We'll arm you with a roadmap to leverage data in a way that fuels intelligent decision-making, drives cultural change, and delivers bottom-line results. No fluff, no afterthoughts. Just a concrete plan to make your data work for you and your stakeholders.

So strap in and get ready to redefine how you approach BI. Your path to data-driven dominance starts here.

Life without a BI Strategy

Operating without a solid BI strategy is like writing an essay without punctuation – you can get your point across, but it will be a confusing mess.

You've got different departments working in silos, like sales crunching numbers in one spreadsheet while marketing tracks website metrics separately. It's fragmented chaos.

Your team wastes countless hours manually collecting and cleaning data from various sources every month. It’s not unheard of that analysts are spending 80% of their time just prepping data before any analysis can happen.

Without a data-driven approach, you're blind to emerging trends. Look at companies like Blockbuster, which missed the streaming revolution because they failed to leverage customer data properly.

Failing to embrace BI means operating based on gut feelings rather than facts. You're stuck reacting to fires instead of proactively driving growth.

In today's competitive landscape, lacking a BI strategy is tantamount to business suicide. Either get deliberate about leveraging your data or risk being left behind. The choice is yours.

The 3 Pillars of a Successful BI Strategy

For your BI strategy to succeed, it needs to be built on three solid pillars:

1) The Vision

This is your "why" - why are you building BI capabilities and what problems are you ultimately trying to solve? Don't get blinded by tech; start with the strategic objectives and user needs.

2) People and Processes

You can't just implement some dashboards and call it a day. Define the roles, governance processes, and support frameworks to properly operationalise BI throughout the organisation.?

3) Technology??

Once the vision and operational plan are set, then you can evaluate the right tools and platforms to enable your BI solution. The tech should serve the strategy, not the other way around.

Think of it like a three-legged stool. Remove any of those pillars and the whole structure collapses. Ground your BI strategy in this trifecta of vision, operations, and enabling tech, and you'll be set up to deliver sustained value.

Preliminary Stage: Assess Your Current State

Before you can chart the course for your BI strategy, you need to understand where you're starting from. Take a hard look at your current landscape:

Set a Baseline

It’s likely you already have pockets of BI efforts spread across teams - data analysts in marketing running website reports, the sales team crunching their Salesforce numbers, etc. Take stock of what data sources and tools each group is using.

Involve the Right People

Don't go at this assessment in a silo. Loop in representatives from the key stakeholder groups - current BI evangelists, data analysts, IT, department heads, and executives. You need their perspectives.

Ask the Tough Questions

Be brutally honest about the current state. What's working well? What's creating friction and inefficiency? Is data governance and lineage clear? Are licensing costs optimised? Leave no stone unturned. Document everything. You’ll be grateful for this in the future months and years.

This snapshot of your current, potentially disjointed state will reveal gaps, redundancies and prime opportunities. It sets the foundation to then architect a cohesive BI vision moving forward. An uncomfortable but necessary first step.

Stage 1: Create a BI Vision

You can't build a house without a blueprint. Similarly, you need a clear vision to guide your BI strategy.

Start by articulating why you're pursuing BI capabilities in the first place. What business challenges are you trying to solve? How will BI insights drive value and impact decision-making? Don't get bogged down in technical details yet.

Craft a vision statement that outlines the measurable goals, what cultural shifts will be required, and how it all maps back to the company's overarching strategy. This is your true north star.

Get buy-in early by painting a compelling picture of how BI will make people's lives easier and drive their career growth. You're selling the transformation, not just new tools.

This vision sets the strategic context and aspiration. It's the "why" that will guide all subsequent decisions around people, processes, and technology choices. Don't skip this crucial foundation.

Leverage a BI maturity model to map your progression from the current ad-hoc state to the desired future vision, where BI is an embedded core competency. A solid model, like this Gartner-inspired favourite, outlines the concrete steps to evolve BI from a disjointed tactic into an organisational capability driving intelligence.

Stage 2: Establish Governance Processes

Having a bold vision is great, but you need a robust operational plan to bring it to life and sustain BI long-term. This is where governance comes in.??

Set up a BI governance team with stakeholders from across the business—not just technology folks. They'll make the tough decisions about tools, data sources, processes, and more.

Don't confuse this with data governance. BI governance is about defining and maintaining the overall BI architecture and lifecycle management. It covers:

UAT (User Acceptance Testing)

Getting hands-on user feedback before rolling out new BI capabilities is critical. Don't assume you know what they need - validate through real-world testing.

Training

You're enabling a culture shift, so invest in training everyone from governance members to end-users on data literacy, tools, and processes. Identify and fill knowledge gaps.

Supporting Users

Deploying dashboards is one thing. Ensuring continuous adoption is another. Establish clear support channels, including:

• Data education: A knowledge base guiding users on data assets, definitions, origins, etc.?

• Tools support: Processes for tool selection, issue resolution, and SLAs.

• Business as usual: Having dedicated power users in each department to drive change management and ensure BI drives ongoing value.

The best BI vision will fizzle out without deliberate processes to operationalise it. Robust governance provides the crucial framework for systematic execution and long-term sustainability.

Stage 3: Build the BI Roadmap

With the strategic vision set and the governance model defined, it's time to map out the actual implementation plan - your BI roadmap.

This should be a visual document outlining the key deliverables, milestones, and timelines required to make your BI vision a reality. Think of it as the master schedule that coordinates all the moving parts.

When building the roadmap, you'll want to:

• Determine the appropriate level of detail based on your audience (high-level for executives, more granular for working teams)

• Use swimlanes or other visuals to map deliverables to the responsible teams?

• Clearly define what "done" looks like for each deliverable, not just tasks

• Identify critical milestones that mark significant stages like "Proof of concept" or "Minimum viable product"

The roadmap serves as the central artefact to align all stakeholders on the plan of attack. It's the "what" and "when" that actuate the "why" from your vision.

But remember, even the best roadmap needs to stay flexible and adaptive as situations evolve. Make it a living document that can accommodate pivots.

With a clear roadmap in hand, you're ready to start executing and bringing your BI strategy to life.

Stage 4: Document the BI Strategy

With the vision set, governance model defined, and roadmap mapped out, it's time to combine them into a comprehensive BI strategy document.

This serves as the official record and universal reference point for anyone involved in or impacted by the BI initiatives - from leadership to end-users.

At a minimum, the BI strategy doc should include:

Executive Summary

A concise overview of the key initiatives, timeline, and expected business impacts - written for executive stakeholders to digest easily.

BI Vision & Alignment?

A more detailed explanation of the vision and how it ties back to corporate objectives and drives value.

Project Scope & Roadmap

The implementation plan, architecture decisions, resource requirements, budget, etc., are all part of this core "how" section.

Governance Model

Clearly defining the BI governance setup - the processes, roles, and responsibilities.

Vendor/Tech Evaluations

Justifying why certain solutions/vendors were selected or rejected.

Success Metrics

How progress and ROI will be measured and monitored over time.

Don't treat this as a static, one-and-done document. It should evolve as the BI capabilities mature. Review and update it annually at a minimum.

This single source of truth ensures transparency and sets clear expectations across all stakeholders. It's the cornerstone artefact for driving true BI transformation.

Stage 5: Review the BI Strategy Yearly

Even the best-laid BI strategy can go off the rails if you set it and forget it. The business landscape is constantly evolving, so your strategy needs to adapt.

Build in an annual review cadence to assess what's working well, what's not, and where course corrections are needed. Treat your BI strategy as a living, breathing document.

During these yearly reviews, evaluate:

Metrics & ROI

Are you actually realising the intended business benefits? Look at quantitative metrics like cost savings, revenue impacts, productivity gains, etc. But also assess qualitative factors like user satisfaction.

Alignment to Goals

Is the BI vision and roadmap still tracking to the business priorities? Adjust as needed to stay synced with shifts in strategy.

Tool and Process Effectiveness

With real-world mileage, you may uncover flaws or inefficiencies in the current data pipelines, governance model, training programs, etc. Optimise accordingly.

Evolving User Needs

Gather the voice of the customer and user feedback to identify emerging requirements. The goalposts are always moving, so be prepared to evolve with them.

You're never really "done" with a BI strategy. It's an ongoing cycle of execution, measurement, and adaptation. These yearly reviews are the reset point for re-aligning, re-calibrating, and re-committing to maximise BI's business impact.

Conclusion

You just consumed the ultimate blueprint for constructing a business intelligence juggernaut. But having the roadmap is only half the battle.?

Now it's time to execute and outpace those losers still messing around with fragmented spreadsheets and gut instincts.

Let's recap the critical steps to ascend to data-driven dominance:

1. Conduct a brutally honest audit of your current landscape to set the baseline. Don't sugarcoat those inefficiencies and redundancies - expose them like throbbing data wounds.

1. Craft a bold BI vision aligned with your strategic objectives. This is your north star to meaningful insights, not just pretty dashboards.??

1. Establish an elite governance squad to design ironclad processes for the development, adoption, and continuous optimisation of your BI capabilities.

1. Plot out a detailed roadmap for flawless cross-functional execution, leaving no gaps for delays or missteps to derail your momentum.

1. Document your master BI strategy, getting full buy-in as the single source of truth to rally the troops.

1. Then, iterate, assess, and adapt that strategy at least annually because data environments evolve faster than software updates.

That's the framework for data dominance. But here's the acceleration hack - why lag behind trying to DIY this entire transformation yourself?

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Hesitate, and you're wasting precious time as the disruptors outmanoeuvre you.?

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