Stop! Before you invest even 10 minutes of your precious time reading this blog, please make sure it's really business intelligence (BI) governance, and not data governance best practices, that you are looking for. BI governance is a key component of data governance, but they're not the same. Data governance deals with the entire spectrum (creation, transformation, ownership, etc.) of people, processes, policies, and technologies that manage and govern an enterprise's use of its data assets (such as data governance stewardship applications, master data management, metadata management, and data quality). On the other hand, BI governance only deals with who uses the data, when, and how.
CIO pushback is part of a typical growing pain of all business intelligence (BI) startups. It means your land and expand strategy is working. Once you start expanding beyond a single department CIOs will notice. As a general rule, the earlier the CIO is brought on board, the better. CIOs who feel left out are likely to raise more objections than those who are involved in the early stages. A number of BI vendors that started out with a strategy of purposely avoiding the CIO found over time that they had to change their strategies - ultimately, there’s no way round the CIO. Forrester has also noticed that the more a vendor gets the reputation of “going round” the CIO, the greater the resistance is from CIOs once they do get involved.
There is of course also the situation where the business side doesn’t want the CIO involved, sometimes for very good reason. That notwithstanding, if there’s a dependency on the CIO when it comes to sign-off, Forrester would strongly recommend encouraging the business to bring him/her to the table.
The two key aspects to bear in mind in this context are:
CIOs look for transparency. Have architecture diagrams to hand out, be prepared to explain your solution in as much technical detail as required, and have answers ready regarding the enterprise IT capabilities listed below.
Delivering broad access to data and analytics to a diverse base of users is an intimidating task, yet it is an essential foundation to becoming an insights-driven organization. To win and keep customers in an increasingly competitive world, firms need to take advantage of the huge swaths of data available and put it into the hands of more users. To do this, business intelligence (BI) pros must evolve disjointed and convoluted data and analytics practices into well-orchestrated systems of insight that deliver actionable information. But implementing digital insights is just the first step with these systems — and few hit the bull's eye the first time. Continuously learning from previous insights and their results makes future efforts more efficient and effective. This is a key capability for the next-generation BI, what Forrester calls systems of insight.
"It's 10 o'clock! Do you know if your insights support actual verifiable facts?" This is a real challenge, as measuring report and dashboard effectiveness today involves mostly discipline and processes, not technology. For example, if a data mining analysis predicted a certain number of fraudulent transactions, do you have the discipline and processes to go back and verify whether the prediction came true? Or if a metrics dashboard was flashing red, telling you that inventory levels were too low for the current business environment, and the signal caused you to order more widgets, do you verify if this was a good or a bad decision? Did you make or lose money on the extra inventory you ordered? Organizations are still struggling with this ultimate measure of BI effectiveness. Only 8% of Forrester clients report robust capabilities for such continuous improvement, and 39% report just a few basic capabilities.
Major conferences are often the occasion for key vendor announcements, and SAP didn’t disappoint. At the 2016 SAP Insider event on BI/Hana in Las Vegas, SAP announced the acquisition of independent mobile BI specialist Roambi’s solution portfolio and key assets. With this acquisition, SAP underlines its commitment not only to mobile and cloud but also to getting the right data into the hands of the right people at the right time. With this acquisition, SAP underlines its commitment not only to mobile and cloud but also to getting the right data into the hands of the right people at the right time. The Roambi acquisition adds the following to SAP’s mobile BI portfolio:
An attractive set of prebuilt visualizations for fast creation of mobile dashboards.
A cloud-based back end that can connect to a variety of data and BI sources.
The capability to create data-rich, interactive, eBook-like publications.
There are both tactical and strategic aspects to SAP’s acquisition of Roambi, which:
Adds attractive capabilities to SAP’s mobile BI portfolio, even for customers who may already be using BusinessObjects Mobile.
Provides an instant cloud option for mobile BI to customers running on-premises BI environments, but who can’t, or don’t want to, support a mobile BI solution.
Can be leveraged as an important building block for the mobile capabilities of SAP Cloud for Analytics.
Brings more than software to the SAP stable. In one fell swoop, SAP gains a team of professionals who’ve been living and breathing mobile BI for a long time.
The hordes gathered in Las Vegas this week, for Amazon's latest re:Invent show. Over 18,000 individuals queued to get into sessions, jostled to reach the Oreo Cookie Popcorn (yes, really), and dodged casino-goers to hear from AWS, its partners and its customers. Las Vegas may figure nowhere on my list of favourite places, but the programme of Analyst sessions AWS laid on for earlier in the week definitely justified this trip.
The headline items (the Internet of Things, Business Intelligence, and a Snowball chucked straight at the 'hell' that is the enterprise data centre (think about it)) are much-discussed, but in many ways the more interesting stuff was AWS' continued - quiet, methodical, inexorable - improvement of its current offerings. One by one, enterprise 'reasons' to avoid AWS or its public cloud competitors are being systematically demolished.
The battle over customer versus internal business processes requirements and priorities has been fought — and the internal processes lost. Game over. Customers are now empowered with mobile devices and ubiquitous cloud-based all-but-unlimited access to information about products, services, and prices. Customer stickiness is extremely difficult to achieve as customers demand instant gratification of their ever changing needs, tastes, and requirements, while switching vendors is just a matter of clicking a few keys on a mobile phone. Forrester calls this phenomenon the age of the customer. The age of the customer elevates business and technology priorities to achieve:
Business agility. Forrester consistently finds one common thread running through the profile of successful organizations — the ability to manage change. In the age of the customer, business agility often equals the ability to adopt, react, and succeed in the midst of an unending fountain of customer driven requirements. Forrester sees agile organizations making decisions differently by embracing a new, more grass-roots-based management approach. Employees down in the trenches, in individual business units, are the ones who are in close touch with customer problems, market shifts, and process inefficiencies. These workers are often in the best position to understand challenges and opportunities and to make decisions to improve the business. It is only when responses to change come from within, from these highly aware and empowered employees, that enterprises become agile, competitive, and successful.
“Business Intelligence in the cloud? You’ve got to be joking!” That’s the response I got when I recently asked a client whether they’d considered availing themselves of a software-as-a-service (SaaS) solution to meet a particular BI need. Well, I wasn’t joking. There are many scenarios when it makes sense to turn to the cloud for a BI solution, and increasing numbers of organizations are indeed doing so. Indications are also that companies are taking a pragmatic approach to cloud BI, headlines to the contrary notwithstanding. Forrester has found that:
· Less than one third of organizations have no plans for cloud BI. When we asked respondents in our Forrsights Software Survey Q4 2013 whether they were using SaaS BI in the cloud, or were intending to do so, not even one third declared that they had no plans. Of the rest, 34% were already using cloud BI, and 31% had cloud in their BI plans for the next two years. But it’s not a case of either/or: the majority of those who’ve either already adopted cloud BI or are intending to do so are using the SaaS system to complement their existing BI and analytics capabilities. Still, it’s worth noting that 12% of survey respondents had already replaced most or all or their existing BI systems with SaaS, and a further 16% were intending to do so.
Many of us have spent the past 10 years focusing on business intelligence solutions in order to help our businesses make better fact-based decisions. In fact, BI has been among CIOs’ top 10 priorities for more than a decade. These solutions have, for the most part, been successful — and we continue to improve our BI capabilities as the demand for fact-based decision-making goes deeper, wider, and further into the business.
This whole time, we’ve also been aware of the significant amount of unstructured data that resides within our business, and the fact that we struggle to use it to make better decisions. To begin to get value from this data, we have made our organizations more collaborative and implemented tools and platforms to support that collaboration — with varying degrees of success.
The fact remains that there’s a huge amount of unstructured information and data that we do not get value from. However, a growing number of solutions are beginning to mine elements of this data: product information, software code, legal case files, medical literature, messaging data, and other unstructured business data.
I’ve recently been working with TrustSphere, which is a messaging intelligence provider. TrustSphere has an interesting solution that mines your messaging data to get real insights and information from the mountains of emails and messages that bounce into, out of, and around your organization every day. This is an interesting concept, and TrustSphere has developed a number of use cases for its solution. I’ll be presenting at a webinar hosted by TrustSphere on February 25— feel free to register here.
Business decision-makers in Asia Pacific (AP) are increasingly aware of the importance of business intelligence (BI) and broader analytics to business strategy and execution. However, lack of internal expertise remains a significant barrier to BI project success.
To succeed in the region, BI service providers must provide guidance on how to translate data access into actual insight and information into business value. This requires a strong understanding of local cultures, business practices, regulatory frameworks, and market dynamics. When evaluating providers, understand how their capabilities are likely to evolve across five categories:
People. To minimize project risks, understand who will be the on-site business and technical leads on BI projects and how many successful implementations this staff has led in a similar industry and similar technical environment within the region.
Technical expertise. Service providers need to demonstrate region-specific knowledge of the technical characteristics of various BI tools, platforms, architectures, and applications. Most companies will not have all of the necessary skills on site, so closely evaluate ease of access to remote staff from the service provider as well.
How is it possible for a local company to defeat global giants like Pepsi, Coca-Cola, and Watsons in your market segment and establish market leadership for more than a decade? The answer is given by Nongfu Spring, a Chinese company in manufacturing and retail industries. In my recent report “Case Study: Technology Innovation Enables Nongfu Spring To Strengthen Market Leadership”, I analyzed the key factors behind their success, and provide related best practice from enterprise architecture perspective. These factors include
Business strategy is enterprise architecture's top priority. EA pros often need to be involved in project-level IT activities to resolve issues and help IT teams put out fires. But it's much more important that architects have a vision, clearly understand the business strategy, and thoroughly consider the appropriate road map that will support it in order to be able to address the root causes of challenges.
Agile infrastructure sets up the foundation for scalable business growth. Infrastructure scalability is the basis of business scalability. Infrastructure experts should consider not only the agility that virtualization and IaaS solutions will provide next-generation infrastructure, but also network-level load balancing among multiple telecom carriers. They should also refine the network topology for enterprise security.