Tag Archives: Business/IT Collaboration
Within every corporation there are lines of businesses, like Finance, Sales, Logistics and Marketing. And within those lines of businesses are business users who are either non-technical or choose to be non-technical.
These business users are increasingly using Next-Generation Business Intelligence Tools like Tableau, Qliktech, MicroStrategy Visual Insight, Spotfire or even Excel. A unique capability of these Next-Generation Business Intelligence Tools is that they allow a non-technical Business User to prepare data, themselves, prior to the ingestion of the prepared data into these tools for subsequent analysis.
Initially, the types of activities involved in preparing this data are quite simple. It involves, perhaps, putting together two excel files via a join on a common field. However, over time, the types of operations a non-technical user wishes to perform on the data become more complex. They wish to do things like join two files of differing grain, or validate/complete addresses, or even enrich company or customer profile data. And when a non-technical user reaches this point they require either coding or advanced tooling, neither of which they have access to. Therefore, at this point, they will pick up the phone, call their brethren in IT and ask nicely for help with combining, enhancing quality and enriching the data. Often times they require the resulting dataset back in a tight timeframe, perhaps a couple of hours. IT, will initially be very happy to oblige. They will get the dataset back to the business user in the timeframe requested and at the quality levels expected. No issues.
However, as the number of non-technical Business Users using Next-Generation Business Intelligence tools increase, the number of requests to IT for datasets also increase. And so, while initially IT was able to meet the “quick hit dataset” requests from the Business, over time, and to the best of their abilities, IT increasingly becomes unable to do so.
The reality is that over time, the business will see a gradual decrease in the quality of the datasets returned, as well as an increase the timeframe required for IT to provide the data. And at some point the business will reach a decision point. This is where they determine that for them to meet their business commitments, they will have to find other means by which to put together their “quick hit datasets.” It is precisely at this point that the business may do things like hire an IT contractor to sit next to them to do nothing but put together these “quick hit” datasets. It is also when IT begins to feel marginalized and will likely begin to see a drop in funding.
This dynamic is one that has been around for decades and has continued to worsen due to the increase in the pace of data driven business decision making. I feel that we at Informatica have a truly unique opportunity to innovate a technology solution that focuses on two related constituents, specifically, the Non-Technical Business User and the IT Data Provisioner.
The specific point of value that this technology will provide to the Non-Technical Business User will enable them to rapidly put together datasets for subsequent analysis in their Next-Generation BI tool of choice. Without this tool they might spend a week or two putting together a dataset or wait for someone else to put it together. I feel we can improve this division-of-labor and allow business users to spend 1-2 weeks performing meaningful analysis before spending 15 minutes putting the data set together themselves. Doing so, we allow non-technical business users to dramatically decrease their decision making time.
The specific point of value that this technology will provide the IT data provisioner is that they will now be able to effectively scale data provisioning as the number of requests for “quick hit datasets” rapidly increase. Most importantly, they will be able to scale, proactively.
Because of this, the Business and IT relationship has become a match made in heaven.
Analyzing current business trends helps illustrate how difficult and complex the Communication Service Provider business environment has become. CSPs face many challenges. Clients expect high quality, affordable content that can move between devices with minimum advertising or privacy concerns. To illustrate this phenomenon, here are a few recent examples:
- Apple is working with Comcast/NBC Universal on a new converged offering
- Vodafone purchased the Spanish cable operator, Ono, having to quickly separate the wireless customers from the cable ones and cross-sell existing products
- Net neutrality has been scuttled in the US and upheld in the EU so now a US CSP can give preferential bandwidth to content providers, generating higher margins
- Microsoft’s Xbox community collects terabytes of data every day making effective use, storage and disposal based on local data retention regulation a challenge
- Expensive 4G LTE infrastructure investment by operators such as Reliance is bringing streaming content to tens of millions of new consumers
To quickly capitalize on “new” (often old, but unknown) data sources, there has to be a common understanding of:
- Where the data is
- What state it is in
- What it means
- What volume and attributes are required to accommodate a one-off project vs. a recurring one
When a multitude of departments request data for analytical projects with their one-off, IT-unsanctioned on-premise or cloud applications, how will you go about it? The average European operator has between 400 and 1,500 (known) applications. Imagine what the unknown count is.
A European operator with 20-30 million subscribers incurs an average of $3 million per month due to unpaid invoices. This often results from incorrect or incomplete contact information. Imagine how much you would have to add for lost productivity efforts, including gathering, re-formatting, enriching, checking and sending invoices. And this does not even account for late invoice payments or extended incorrect credit terms.
Think about all the wrong long-term conclusions that are being drawn from this wrong data. This single data problem creates indirect cost in excess of three times the initial, direct impact of unpaid invoices.
Want to fix your data and overcome the accelerating cost of change? Involve your marketing, CEM, strategy, finance and sales leaders to help them understand data’s impact on the bottom line.
Disclaimer: Recommendations and illustrations contained in this post are estimates only and are based entirely upon information provided by the prospective customer and on our observations and benchmarks. While we believe our recommendations and estimates to be sound, the degree of success achieved by the prospective customer is dependent upon a variety of factors, many of which are not under Informatica’s control and nothing in this post shall be relied upon as representative of the degree of success that may, in fact, be realized and no warranty or representation of success, either express or implied, is made.