Please describe your organization.
HighPoint Solutions is a technology and management consulting firm based outside of Philadelphia, Pennsylvania, in East Norriton. We're focused on exclusively serving the life sciences and healthcare markets. In these markets we provide both functional and technical oriented solutions through package system implementations as well as management consulting. For example, we have a commercial excellence practice focusing on helping life sciences organizations optimize their commercialization path, as well as to initially commercialize. We actively serve over 80 life sciences companies, including 8 of the top 10 bio pharma companies and over 40 emerging pharmaceutical organizations. With the merger and acquisition propensities of these markets, we have been involved in a number of acquisition optimizations for companies that are either acquisitive by nature or are undergoing an acquisition to help optimize their structure.
HighPoint also has horizontal practices focused on technology implementations, including our informatics practice, which is comprised of subcomponents around data warehousing, business intelligence, master data management, data quality, etc. We also have a managed services organization, where we provide services for information-centric capabilities like data warehousing or business intelligence.
What is your position?
I am the Vice President Of Data Practice. My responsibility is for strategy and innovation, data warehousing, big data, and business intelligence.
What business challenge were you trying to address with Qlik?
We work with a lot of emerging pharmaceutical organizations. These are companies that are bringing their first or second product to market. We help them establish their whole commercialization roadmap, ranging from business commercialization (getting their sales force out on the street and what technology they should use in terms of customer relationship management applications) and also providing rapid understanding of the market which they will be entering. The second aspect is how they're positioned in that market through their pricing and managed care strategy. The third part is pulling this process through direct sales activities. Looking across this dimension, we can determine what a successful launch is going to be made up of. We create opportunities and maximize pulling them through.
We work predominantly with organizations which have therapies targeted to people with complex diseases which are treated by specialists, like oncologists. We also work with chronic diseases that need to be treated with complicated medications, like rheumatoid arthritis. The data landscape for understanding product flow, how products are positioned, and how uptake happens, requires integration of up to 200 data sources for a single product. These tend to be of low quality, but they have to be integrated and presented with some fairly low-latency understanding of what roadblocks may be presented in the marketplace, either for getting the message out or for getting therapy to patients. After this, it's important to understand what tactics the medical communications team or the sales team needs to employ to make sure that the product will get introduced to the patients that need it. We deliver a lot of solutions in this space with an underlying data fabric which we call DataBurst, which handles the integration side of the equation. In many cases, we present the analytics and day-to-day operational insight through QlikView.
What makes QlikView the better choice, compared to other available options?
We do implementations using both QlikView and Tableau. One of the positive aspects of QlikView is that time-to implementation can be very short once the data has been integrated in the background. For organizations with specific analytic journeys which they want people to take, we can create a nicely-governed Qlik application that is either hosted or distributed in order to make sure that people are focused on the analytics that are somewhat predetermined and understood. That is the data which will help them be successful without having to venture off into the analytics wilderness, spending time looking at data in a way which may not be correlated to reality, or is simply not a good use of their time. We find that the deployments that meet tightly-governed, high-value, easy-to-navigate analytics, work best in Qlik.
How would you say that Qlik fares as far as integrating with disparate data sources?
As an in-memory database, it requires a certain level or architectural sophistication in order to develop a truly self-service environment. Partners like HighPoint can create an analytic data pipeline that can provide the necessary data sources to Qlik in a way that can offer flexibility to people without running into performance issues. We normally have our analytics pre-processed or datamarted upstream. Depending on the use case, we publish Qlik files or use the publication server environment. The other aspect is trying to get to low-latency reporting. It can be very difficult for someone to do any self-service without direct IT intervention.
Are there any particular features by which you've been impressed, which you would highlight as Qlik's key strengths?
Qlik's visualization layer is very compatible with the user expectations of our customer base. Qlik's early penetration of the market, and providing visualizations for both enterprise and media applications, set an aesthetic with which people are comfortable. The applications which we publish are very intuitive and help people conduct directed analytics in a very efficient way.
Are there any services which haven't performed up to your expectations, or is there any tool which you'd like to see implemented within Qlik?
From a feature-functionality perspective, there are aspects of the overall architecture which create barriers to find either high frequency or low-latency analytics. I don't know if this is necessarily a negative issue; it's simply the nature of the product. I am referring to applications of large data landscapes which include hundreds of sources. I don't know if there is a business intelligence tool which can solve this problem. Upstream data integration and data mining are necessary in these cases. A lot of people think that solutions like Qlik are able to achieve this, but they can get themselves into a lot of trouble this way.
One of the challenges that Qlik has had over the last couple of years has to do with the fact that they function in an economic world in which pricing has to become more realistic. This has put a lot of pressure on them, given the competing emerging technologies within their business model. We've seen increased pressure from our customers to look at other tools that are a little more modern, more self-service oriented, and cheaper.
Have you had interactions with any of their support team or support resources? If so, how would you categorize the experience?
I would say their support experience is industry average.
We have five additional questions. For each of these, we ask that you rate Qlik on a scale of one to five, with five being the best score.
How would you rate Qlik for its functionality and available features?
Three and a half to four.
How would you rate Qlik for ease of use and ease of implementation?
Four for ease of implementation.
Four and a half for ease of use.
How would you rate Qlik for support, as in the response of their team, and the helpfulness of available resources online?
How likely are you to recommend Qlik to a friend or colleague, out of five?
We currently recommend the solution to our business clients.
How would you rate Qlik for overall satisfaction with the platform?
Three and a half.