Ever wondered what a well-planned and deployed business intelligence project can do for your business without all the challenges? By now if you’re not aggressively mining your data you’re not only leaving money on the table, you’re falling behind your competitors. Looking for basic aberrations and trends in data for sales, marketing, operations and customers is second nature to most companies. This will help you tread water for a time but did you know you unlock exponential value to your data once you reach cross functional, role based, and collaborative analysis which enables iterative business process improvement?
The challenges to operative data visibility are pretty easy to identify in a company. Do any of these ring a bell? You have a thousand spreadsheets stored on your network and different departments may have different values for the same measure? The executives have clear objectives and have a strategy but if you ask an individual contributor there is only a vague notion of what they are, or are pursuing their own department objectives? You have data, a vision for analyzing your marketing or industry metrics but your IT department takes so long to assist with setting up the reporting tools and infrastructure that it becomes irrelevant before you can act?
But let’s back up a little and first understand what business intelligence is in the first place. There are a lot of terms thrown around like analytics, ad hoc reporting, data warehouse, key performance indicators and forecasting to name a few. If you ask ten people you’re likely to get 20 answers to the same question. The fact is, business intelligence applied in a business environment is an ecosystem of both technical and business factors that drive performance in an organization aligned to strategic objectives. The business components like strategy mapping, business process improvement and collaboration are just as important to the technical reporting, warehouse and ETL tools.
The actual process for running or starting a business intelligence project is a prescriptive methodology that is very different from other types of projects and as such there are best practices based on the size of the organization, vertical, maturity, objectives and processes being measured. In some ways it’s both an art and a science.
In short form, you’ll thoroughly understand your company’s objectives and how your department fits into that story. Then analyze the different processes in your company that affect those performances. Determine the measures within those processes that can be affected by managing their performance. These should be as far back in the process as possible which we call leading indicators, those which can be changed before the results are locked into your balance sheet. Then on the business side you’ll start your internal marketing campaign, yes internal. And at the same time start to round up the data for your analysis. And this is when the real work begins!
Though the following tips are not exhaustive or definitive, they are certainly some traps that a lot of organizations fall into while stepping up the BI Maturity Ladder from basic operational and transnational reporting to immersive and responsibility based performance management.
1. Executive sponsorship is critical but so is employee buy-in
Ever heard the term, “you can’t push a rope”? Leadership can have the greatest plans for moving the business forward but unless each and every contributor to the processes that affect the outcome have bought into the mission and actively participate, the movement won’t get very far. Yes you can use the hammer and tie incentives to performance immediately instead of over time for which you will receive immediate backlash as a result. Or better yet positive reinforcement by making progress and goals at a high level visible and celebrated for all to see and introduce some cross department competition on conformed measures. A good leader inspires the best in people, not the worst.
Pro tip: Leadership should make every effort to communicate not just on the metrics but also adoption and accuracy.
2. Drive vertical then go horizontal
Lofty enterprise goals are very hard to implement across an organization, it requires massive amounts of cooperation amongst departments to define measures, setup architecture and extract from complicated source systems which can be expensive. Instead start with one process that, for example, drives one channel of your sales funnel and then drive that vertical to the individual contributor level in the form or actionable reporting, “Here are the clients that need to be called today for satisfaction feedback”. In this way you can start to see immediate results and use it as a template to implement in your organization for other processes and departments.
Pro tip: Setup a regular BI governance and education roundtable meeting to foster communication and iterative improvement among the BI stewards at all levels.
3. Stay focused on the business drivers, not the technical hurdles
There is an odd dichotomy to business intelligence depending on your business or technical background. If you are a business person maybe you’ve heard of the Kimball methodology for data warehouse design. If you haven’t that’s okay but that’s what your IT professionals are using to build out your backend data repository and this may not always provide the data in the form that you need from a business perspective. It is an object oriented approach to data that, depending on the complexity of the data sources, can take months or years to develop and deploy. If your organization needs to be nimble shouldn’t you be able to make decisions faster than that? To overcome this as a business user, start with a coherent set of sample data and then prototype what you want in your role-based reports and dashboards, including objectives and goals. You should define the calculations, granularity, security, availability and as much agreement from business leadership as you can before approaching IT. Your month long sprints should include visible deliverables back to the business even if they are very small iterative improvements.
Pro tip: Your business intelligence architect is the best translator between business and IT, they will make this communication much easier.
4. Organizational change and data visibility is unsettling
When you first begin your BI initiative you will probably begin with interviews to better understand your processes from the different subject matter experts and data stewards. Through these interviews it will be pretty easy to spot who is not on board with your project. Everyone is busy and it’s not easy to squeeze out more time for yet another “pet” project of the higher-ups. Not to mention it may require change to already overburdened workers who are trying to do the best they can with less budget and time. But there can be other reasons as well, data visibility can expose weaknesses or mitigate control over a certain functional area. On the positive side, data visibility can also expose strengths and opportunities which may be leveraged in other areas. Once again, focusing on the ultimate objectives, clear an honest communication and support from the executive team is essential to moving through road blocks. The challenge is to make the change process as positive as possible for all involved. Rapid and successful improvements in processes leading to better metrics will help show value and increase confidence in the initiative.
Pro tip: During requirements be sure to measure the current state process in terms of hours or cost or opportunity and then the improved state so later you can show your BI on BI in the form of ROI.
5. Don’t exclusively focus on financial metrics
At the end of the quarter or year it’s not uncommon to get a report on sales revenue, cost of goods sold, other expenses and profit. But by the time these are realized whatever variables led to these metrics are impossible to change for the current timeframe. You could only look in your rear view mirror for potential fixes to be applied to the next quarter or year. The goal should be to develop an early warning system amongst your operational, customer and employee metrics where if changes are made early enough you would still have time to moderate the effects. Think of your processes as a linear timeline that may intersect other processes. For example, if the goal is to reduce customer acquisition cost by increasing customer retention you might measure employee support training or development speed on customer requested functionality. Both of these processes affect financial performance but the leading indicators allow for much earlier identification and improvement prior to their impact on the bottom line.
Pro Tip: Use what-if scenarios to determine the highest impact leading indicators and set your goals. Indicators can be rated on impact, probability and complexity. Also be sure that you are using key performance indicators and not metrics, KPIs are mostly measured using percentages, indexes and ratios.
So the takeaway from starting and progressing a business intelligence initiative in your organization can have challenges but they can be overcome. Get strong executive sponsorship and involvement, start with a vertical challenge that can provide the best ROI, deliver a role-based solution that can be quickly deployed, understand that change and data visibility can be unsettling so make it a positive experience and finally, start with the financial metrics you want to improve but then identify as far back in the processes as possible those metrics and roles that affect them.
Dan Beebe has over twenty five years’ experience in information technology in various business and technical executive roles.
Dan’s industry experience includes working with fortune 500 companies in the software, financial services, healthcare, public sector, and manufacturing verticals delivering solutions that provide real value.
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