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.
More than 100,000 people descended on Barcelona, Spain last week to be part of Mobile World Congress (MWC), one of the world’s largest annual technology events. My new report,IoT And Insights Are Two Sides Of The Same Coin, recaps some of the MWC 2016, including expectations for new 5G networks, the Internet of Things (IoT), and applications that will deliver value from the multitude of connected things — and people. A few of those highlights include:
5G Networks Promise Speed But Require Patience.
Telecom operators and network equipment providers eagerly discussed the faster speeds and lower latency of new 5G networks. And, fast it will be. While reports vary, network tests show download speeds peaking at more than 20 Gbps; average 5G speed is expected to be 100 times faster than current 4G networks. With that kind of speed, true video streaming becomes a reality for consumer and business uses. And, that reality can be with virtual or augmented: AR and VR were all over the exhibit hall. I successfully fought with a dragon but had to bail out of the helicopter I was flying as the experience got a little too real.
But alas, these good things only come to those who wait. The 5G standards will not be finalized before 2018; and commercial availability not before 2020 at the earliest. Large-scale network rollouts will likely take much longer. For now, we’ll all have to live with 4G reality as it is.
Interest In The Internet Of Things Is Exploding – Well Beyond Things.
We’re now only a week away from the Mobile World Congress 2016 to be held again in Barcelona. As the excitement builds and we plan our schedules, it serves us to reflect back on last year’s event and to explore what we expect this year.
Mobile World Congress remains the pre-eminent event of the mobile industry and now one of the largest global events across all industries – a fact which illustrates an ambiguity in the meaning itself of “mobile industry.” Last year, over 94,000 people attended the event – a 10% increase from the 2014 event but a 30% increase over the 2013 event. Interest in “mobile” continues to grow – for now. But the most interesting stat about past attendees is diversification. Yes, the event continues to draw representatives from mobile operators, device manufacturers, network equipment providers, software vendors, and other usual suspects. But representation from other industries is growing. Last year almost ¼ of attendees came from industries other than telecom and technology, including 4% from finance, 3% from government and others from automotive, pharmaceutical, retail, education, and entertainment. I expect even more diversity this year.
Do you ever feel like you’re facing a moving target? Whether it’s the latest customer requirements, or how to improve operations, or to retain your best employees, or to price your products, the context in which you are doing business is increasingly dynamic. And, so are the tools you need to better understand that context? Everyone is talking about the promise of big data and advanced analytics, but we all know that companies struggle to reach the Holy Grail.
Data and analytics tools and the skills required to use them are changing faster than ever. Technologies that were university research projects just last year are now part of a wide range of products and services. How can firms keep up with the accelerated pace of innovation? Alas, many cannot. According to Forrester's Q3 2015 Global State Of Strategic Planning, Enterprise Architecture, And PMO Online Survey, 73% of companies understand the business value of data and aspire to be data-driven but just 29% confirm that they are actually turning data into action. Many firms report having mature data management, governance, and analytics practices, but yesterday's skills are not necessarily what they will need tomorrow — or even today.
The same goes for data sources. We all know that using external data sources enhances the insights from our business intelligence. But which data and where to get it?
Today I heard an agency describe the content strategy that it was working for a client. At the end of the description (which revolved around how the client saw itself, and what it wanted to talk about), I said: “That sounds like an ad pitch.” Awkward silence.
Right now, in meeting rooms around the world, bad ideas for content strategies are being hatched. And it’s no fault of the idea-hatchers.
Sitting in a meeting room.
Thinking about the company’s (or client’s) management or board.
Needing to sell an idea in to sceptical constituents.
Knowing, no matter what they hatch, it’ll get enough paid air cover to make it look a winner.
So they lay an almighty egg of a content strategy. An egg that, within the hothouse confines of the group that hatched it, meets only reaffirmation. But the content strategy doesn’t serve customers. Not at all. And it doesn’t serve the real strategic goals of the company behind it.
How do you get around this natural tendency of organizations to lay eggs?
You need a very strong counterweight to the natural tendency towards basic self-interestedness from the parties involved (client approval for the agency, peer approval for the marketer, and self-serving messages for the internal stakeholders).
Audience-centric design is the response. Taking its cues from the user-centric design discipline, audience-centric design relies on rich and direct audience observation – both their attitudes and behaviors – in order to inspire value in the eyes of the audience.
The battle of trying to apply traditional waterfall software development life-cycle (SDLC) methodology and project management to BI has already been fought — and largely lost. These approaches and best practices, which apply to most other enterprise applications, work well in some cases, as with very well-defined and stable BI capabilities like tax or regulatory reporting. Mission-critical, enterprise-grade BI apps can also have a reasonably long shelf life of a year or more. But these best practices do not work for the majority (anecdotally, about three-quarters) of BI initiatives, where requirements change much faster than these traditional approaches can support; by the time a traditional BI application development team rolls out what it thought was a well-designed BI application, it's too late. As a result, BI pros need to move beyond earlier-generation BI support organizations to:
Focus on business outcomes, not just technologies. Earlier-generation BI programs lacked an "outcomes first" mentality. Those programs employed bottom-up approaches that focused on the project management and technology first, leaving clients without the proper outcomes that they needed to manage the business; in other words, they created an insights-to-action gap. BI pros should use a top-down approach that defines key performance indicators, metrics, and measures that support the business' goals and objectives. They must resist the temptation to address technology and data needs before the business requirements.
Blogged in collaboration with Rebecca McAdams, Research Associate, serving Customer Insights professionals.
Consumers are connected, constantly influenced by marketing messages, their friend’s social posts, blog posts, reviews, mobile messages, and Twitter posts. In fact, US Adults have an average of three connected devices. Consumers are leaving breadcrumbs of information behind, across multiple channels and devices. Marketers are jumping at the chance to connect with their customers through proactive marketing campaigns and even through non-marketing interactions. But which interactions actually drive impact? What interactions are responsible for sales conversions, and which interactions merely "assist" conversions? CI Pros and marketers are stumped; they must measure these complex interactions to help drive future marketing and media investments and to actually measure their marketing efforts.
By now, we know that attribution is essentially the answer to many marketers’ prayers: more accurate performance metrics, better cross channel insights, and a more informed marketing spend. While the benefits to attribution are clear, many CI pros and marketers still need to make the case for attribution. They need funding, and support from their executives. In light of this aversion to investing in attribution, the recent business case report, Measure the Impact of Cross-Channel Attribution, will help CI pros build the business case you need to convince executives that implementing cross-channel attribution is definitely worth the time, effort, and money. As you follow our guide to building the business case, you will cover all necessary bases by laying out the costs and benefits of attribution, while also planning for any possible risks you may run into along the way.
On May 14, Acxiom announced its intention to acquire LiveRamp, a "data onboarding service," to the tune of $310 million in cash. Several Forrester analysts (Fatemeh Khatibloo, Susan Bidel, Sri Sridharan, and I) cover these two firms, and what follows is our collective thinking on the impending acquisition after having been briefed by Acxiom's leadership on the matter.
Last year, my colleague Srividya Sridharan published The State Of Customer Analytics 2012 (subscription required). Using the results of her annual customer analytics adoption survey, she uncovered key trends of how customer analytics practitioners use and adopt various advanced analytics across the customer life cycle and highlighted challenges and drivers associated with customer analytics.
This year, I have the pleasure of teaming up with Sri on her yearly survey, to further explore the adoption of advanced analytics, measurement, and attribution. Please read her blog post to learn more about the survey. This survey will explore the adoption and usage of measurement techniques, including attribution, and the adoption of advanced analytics methodologies. With this expanded survey we want to understand how you use and apply measurement and analytics in your organization to optimize both cross-channel marketing campaigns and customer programs.
In particular, we’re fielding questions to understand the goals and challenges associated with measurement and analytics, the adoption and application of measurement and advanced analytics methods, the use of several marketing and customer metrics, the customer insights process and workflow, and the organizational aspects that support measurement and analytics. We encourage you to participate in this survey, as this information will help you benchmark your measurement and analytics adoption efforts.