Companies are moving to adopt business intelligence (BI) systems because the potential payoff can be needle-moving. However, making the decision to implement a BI solution is the easy part. What’s much harder is making sure you’re getting the most out of your investment by ensuring that certain preparatory measures are taken, and important processes, such as identifying key performance indicators important to your company, are solidified ahead of time.
In this slideshow, Chris Garabadian, CoE leader (business intelligence, sales analytics and services) at IMS Health, a company that provides information, services and technology to the pharmaceutical industry, outlines top questions to ask yourself before and while implementing a BI/analytics system.
Click through for five questions you should ask before and during a BI implementation, as identified by IMS Health.
Moving from data collected and managed in Excel spreadsheets to information collected and presented on a fluid, more visual business intelligence platform can be, without question, an abrupt change – but certainly a welcome one for businesses who benefit from deriving insights from data quickly, as many sales forces do.
Spreadsheets usually require that the business user do some level of analysis on them (i.e., “Which of these 200 prescribers on the spreadsheet have decreased more than 10 percent from last year?”), taking them away from more value-adding tasks. Studies have shown a poor adoption rate for spreadsheet deliverables as well, with the majority of users ignoring the spreadsheets after their initial release. BI solutions should be designed so that they answer the top questions a business user needs to ask on a daily basis, allowing them to redirect their efforts to driving the top line, not performing analyst-level functions.
The answer to this question probably depends on who you ask in the organization. Odds are, the sales team has their KPIs, brand teams have theirs and managed markets have their own as well. While it is important for each business unit in the company to have unique performance goals, companies should look to adopt some standards across units. This helps foster greater collaboration and ensures accountability to senior management. Revisiting these standards is beneficial for companies looking to implement a business intelligence system because they’re given the opportunity to fine tune these KPIs and take advantage of the measurement of new ones that they may not have been able to gauge before, without a BI system in place.
Your BI platform may change over the years, but your company will always need data. It is important for companies to invest in a solid data infrastructure that can support changing BI trends and multiple BI tools in the near term and the long term. Many companies base their data infrastructure decisions around a specific BI platform. Inevitably, when the company wants to plug a new BI tool into the mix, they are faced with major data infrastructure challenges, or more likely, installing a second data infrastructure to support the additional tool. This causes redundant IT processes and business challenges in maintaining a single source of truth.
They might well be, but they probably need to pick up the phone and call someone in sales operations. Or perhaps there is a power user in the field force who handles a lot of questions from his peers. Or, they spend a lot of time asking their manager for information, which takes the manager away from his or her responsibilities. If a BI solution is such that only a handful of users know how to get insights from it, then it is not serving its purpose. BI solutions need to present information, and insights – not data – to the average business user in a way that they can easily understand. In addition, BI solutions should have easy-to-use ad hoc capabilities for power users. If the solution requires that the client ask the vendor for help getting access to new information, it is not serving its purpose.
Not every company has the internal resources needed to build their own BI infrastructure (and don’t forget the underlying data infrastructure needed to support it). Keep in mind that a build-from-scratch approach requires months to years (typically a minimum of eight months for an initial release of a single subject area) and will incur high costs. If companies are not willing to take on that investment and risk, they can look to cloud-based offerings on the market, which can be delivered much faster, cheaper and offload the risk to the vendor. At a minimum, take the opportunity to talk to your vendor about what other companies of your size are doing to solve these common challenges.
