BI implementation
Iryna Kravchenko Iryna KravchenkoChief Editor

Business intelligence implementation: A step-by-step guide

Long gone are the times when business owners acted on a hunch while running their enterprise. Today, even small locally-dealing firms prefer to collect information on clients’ demographics along with their tastes and preferences as to the products or services the vendor offers.  

For bigger organizations, collecting business data is a vital necessity that is highly instrumental in analyzing historical activities and the current stand of their venture as well as in divining market trends symptomatic of their niche for months and even years to come.  

Purposing to outsell their rivals, blue-chip companies spend outrageous sums on similar activities turning business intelligence (BI for short) into their major competitive differentiator.  

Is BI really that valuable? 

The importance of being intelligent and business-wise

Business intelligence implementation

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Business intelligence implementation

The term “business intelligence” subsumes a whole range of procedures aimed at collecting, hoarding, and analyzing business operations information. It can be subsequently utilized to make knowledgeable data-driven decisions based on the comprehensive picture this overview creates. What activities does an average business intelligence implementation plan include? 

Once you implement business intelligence, you will be able to leverage all these summands to the maximum and drive much value for your business.

What benefits does successful BI implementation bring in its wake?

We hope that now you are convinced that business intelligence is a coal-and-ice practice for a modern enterprise of any size. How should you go about it? 

Business intelligence implementation steps: An algorithm to follow

Implementing business intelligence isn’t hard but it takes meticulous preparation and rigorous following the agreed-upon plan. 

1. Develop a business intelligence implementation strategy 

Having successfully accomplished dozens of business projects of different kinds, we at DICEUS know well that any complex and multi-phased endeavor will triumph only when it is thoroughly planned. Without a well-defined strategy, employees refer to discrepant data, follow conflicting instructions concocted on the fly, and take guesses at unclear names and definitions. What makes the matters worse, during such randomized and haphazard efforts data quality becomes only an afterthought.  

While developing the roadmap, you should answer three basic questions: What do we have? What is our goal? What do we need? 

First of all, make a roster of available data and departments that are responsible for storing it. Then, try to understand what other data you will need and what systems must be used to obtain it. 

Secondly, shape your objectives. You should clearly realize where you would use BI insights. Do you want to improve your workflow? Do you want to reduce customer churn? Do you want to optimize your expenditures? By setting priorities, you will be able to choose efficient ways of reaching your goals. 

Thirdly, form a vision of your future BI system. Should it integrate the existing disparate structures or should it totally replace them? What functionalities would you like it to have? Should it be an on-premise network or would hydrating the cloud suit you better? 

Only after you have come to grips with all minute details of the future undertaking, you can go at it hammer and tongs. 

2. Appoint the team responsible for BI implementation 

Once the plan is drawn, you must decide who will see it through. Since business intelligence is not just an IT or financial project but essentially an across-the-board issue, the implementation team should include representatives of all departments. Moreover, all stakeholders who work with business data should be involved in the venture. And the entire personnel of the company should be carefully explained how each of them will benefit from BI implementation to mitigate conventional resistance to change. 

3. Define KPIs to be subject to BI 

State-of-the-art software tools can yield dozens if not hundreds of various indices. Don’t try to boil the ocean and cull tons of them. Go through your company’s pain points and business goals to check which KPIs are critical, which are just useful perks, and which can be done without.  

To streamline your selection throes, split KPIs into categories: project management metrics (ROI and productivity), marketing data (conversion rate, customer acquisition cost, cost per lead), financial indicators (net income, liquidity ratio, sales growth), customer metrics (customer lifetime value, monthly number of new customers, social media traffic), HR indices (cost per hire, net income per employee), etc. 

It is also necessary to know which of the KPIs you would gauge across the organization and which of them will be monitored within the departments. 

4. Find a competent software vendor 

Contemporary business is heavily IT-reliant, and implementing business intelligence requires utilizing a set of corresponding software tools. Of course, you can try to do it on your own and pin your hopes on the in-house team. In this case, it should consist of a BI infrastructure architect, a data and a database administrator, a data mining specialist, an application lead and an ETL lead developer, a data quality analyst, and a project manager. Do you have all of them on your payroll?   

Evidently, large-scale projects of this kind that necessitate specific expertise seldom (if not never) benefit from employing a DIY approach. That is why outsourcing BI implementation is a wise solution.  

Searching for a vendor, you must make sure the company of your choice has sufficient experience in the domain, a qualified team of specialists, the knowledge of the required tech stack, and offers high-end services at a reasonable price. With DICEUS, you can tick all the boxes. We can handle a BI implementation project of any complexity and deliver an excellent outcome within a stipulated time and budget. 

Learn how to find a reliable software vendor! Download a free white paper

5. Select the right BI tools 

Today, there is a whole gamut of business intelligence tools on the market so to navigate well among the plethora of options you should consider both your functional needs and non-functional requirements (security, performance, availability, etc.). The way you will access the data, visualize it, interact with the metrics conditions your choice to a great extent. 

In case your data intelligence efforts are going to be of a medium scope, out-of-the-box solutions will suffice. But if you plan to dig deep into analytics, consider acquiring customized tools that can be tailored to perfectly match your vision of business intelligence. 

However, you can avoid the headache of choosing BI tools by entrusting all technical details to the recruited vendor, which is probably the best course to take.  

6. Take thought for infrastructure 

The two crucial infrastructure elements related to implementing business intelligence projects are data storage and the BI platform. 

Today, on-premise data banks are considered to be obsolete and unwieldy behemoths that can hardly keep abreast of ever-growing volumes of data and shifting demands imposed on data handling. That is why most organizations opt for enterprise data warehouses (EDW) that can hoard larger amounts of data from multiple systems and apps (ERP, CRM, HRM, etc.) and provide efficient processing of it.  

Equally outdated are local BI platforms that are being increasingly ousted by cloud facilities. As a balanced tradeoff between the level of control and storage cost offered by either option, you can try hybrid solutions that combine the best of the two worlds. 

7. Prepare the data 

By all accounts, this stage takes up to four-fifths of all the time BI development requires. First of all, data should be synchronized since various departments may use different tools, approaches, codes, storage patterns, etc. – the phenomenon known as data silos. When the integrity of data is achieved, there are other parameters related to data quality you should look into (completeness, validity, consistency, relevance, accuracy, uniqueness). 

8. Perform data migration (optional) 

In case you realize that the on-premise data storage and BI platform that you use hamper effective business intelligence, consider hydrating the cloud. DICEUS is ready to consult you on the matter and provide high-profile data migration services. If you already enjoy all amenities the cloud provides, pass on to #9. 

9. Initiate a feedback loop 

You should schedule regular meetings of BI stakeholders where the current progress of the project is reviewed and corrections are timely introduced.  

10. Start small 

It is recommended to launch a trial with a few vital KPIs. Collect feedback on its success and detected bottlenecks to remedy the overall strategy (if necessary). 

11. Implement BI on a larger scale 

Once you make sure you have introduced requisite adjustments and your strategy works smoothly, proceed to implement business intelligence with other KPIs. But remember to assess the procedure ever and again and optimize the problem areas to see the whole project through and get at the expected deliverables.  

Business intelligence is an imperative practice that supplies enterprises with critical information on their operation. It enables them to evaluate performance, expose deficiencies, and map out strategies to improve workflow efficiency and customer engagement. By employing the services of a seasoned outsourcer, you will be able to drive positive change to your company and significantly facilitate its business activities.

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