5-SECOND SUMMARY:
- There are 7 steps to implement a BI strategy in your company: Vision, Sponsor, Tools and architecture, Talent, Culture, Governance and Security and Evolution.
Nowadays, the market is highly competitive meaning that having a good BI strategy is the first step to achieving results and mitigating failures or wrong directions that can make you lose position or competitiveness.
Making a BI strategy is very important, especially when you’re going to implement it for the first time. There are some challenges and pains while doing it as some variables that you must take care of to prevent you from failing while implementing such a solution. It’s not easy to achieve a perfect implementation, but it’s not impossible, and we’re here to show you. Just follow the steps below, and we’re sure that you will perform great:
1. Vision
We would suggest that first of all, you must identify in which state your company is. How are you treating data? Where does it come from? Which processes and tools are being used? And which human resources can you take advantage of that have expertise in data?
After that, set up your priorities, objectives and goals that will bring value to your company and help achieve the better performance you’re seeking. Think of building a BI roadmap with future actions, milestones, deliverables and KPIs over a certain period, this may help you identify what is essential and the timelines for achievement.
2. Sponsor
Adopting a BI strategy will require resources and change management, and for this, you’ll have to find a sponsor for it inside your company, and that choice can be crucial. First, it will fund the change you want to implement in your company and second, you need someone inside your company to trust your work and support the project. Ensure that you involve your sponsor often, so he keeps trusting in your work and sees the results.
3. Choosing tools and architecture
There are pretty good BI tools out there in the market. But still, each of them has its advantages and disadvantages. Choosing a not so well fitted tool will make you lose money and time. Identify what will be the main patterns of your BI project. How and where will you fetch data, which type of treatment will data need and where will you store it after being cleaned, will you need more tabular analysis or charts analysis, and where do you want end users to access data and analysis.
These are some questions that you must answer first and after that search for tools and ask for demos so you can see the utility of those tools and if they fit what you want to do. Besides that, you must ensure that you have the right architecture for all the tools you need to use. If local machines or cloud, their performance and interconnection, which tool will do what and how will each of them connect to each other so the flow can be smooth and without major problems, and many other questions you can ask. A way to know the best tools in the market is by following the Magic Quadrant of Gartner published yearly.
4. Gathering talent
One of the most challenging points will be this one. Choosing roles and finding people to fill those spots, especially in a company that is not data-driven yet, will be hard to do. You can hire new people with data knowledge but who know nothing about your company, or you can take advantage of those you already have and simply train them. Maybe in the end it will be a mix of the two.
Implementing a BI solution requires different skills and specialisation so matching the internal resources with a partner is likely a good option.
5. Promoting Culture
If I said that the previous point would be one of the most challenging, this one would be equally hard. If a company is not data-driven or at least people don’t understand that things have to change and they must know how data works, then your project will fail. No one will be motivated to use BI tools because they won’t get anything from them; they won’t understand the purpose and value of such, something that in the end, will make them boycott the change you’re trying to implement. Make sure, from the start to yourself, your sponsors and all stakeholders that everyone must be trained, and ensure that you deliver data literacy and digital competencies to everyone in your company. Democratise data, let business users answer their questions and do analysis by themselves. Don’t just tell them the value of it; let them touch and see the future, and make them follow and want more.
6. Governance and Security
Data is something of great value but is something private too. You must ensure that your data is protected and only accessible to the ones that are allowed to access it. Assign people like data stewards or content administrators to check if all data is well stored and governed. Build policies and procedures for different scenarios, and guarantee that you are prepared for any leakage and data protection. You can extend this to your tools, and see how they are performing over their lifespan, if they are updated or if there are any improvements to them.
7. Evolve
Always believe that there’s no ending to what you’re doing. Data platforms are continuously evolving, and you must do the same; you can escalate your BI solution to use tools with Machine Learning or Artificial Intelligence capabilities in the future. Never forget that nothing is forever so always keep informed about data tendencies. Besides that, you won’t implement a BI solution to your whole company at the start, it will be for one department or one problem, so after being successful you may escalate BI to other departments or other problems where it may fit so that one day, you can call your company – a data-driven company.
Final Thoughts
As you see, implementing a BI solution will have its challenges, but you know as we know that it’ll be a game changer for your company. You’ll need a lot of perseverance, patience and know-how to manage conflict and expectations so that, in the end, the result may be on time and bring value to everyone and that’s why Xpand IT can help you with our service of the data journey. Besides that, we have teams highly specialized in these types of solutions which can advise you right from the start and bring all the necessary know-how.
Data Analytics Engineer