Technology adoption involves more than just procuring and deploying technology. Ultimately, organizations have to ensure the use of their systems in a manner that strategically benefits the business. “Hope” is a weak strategy, which is why more companies are taking proactive steps to ensure they get value from their technology investments.
When computers were first introduced in a business context, users pushed back. Business intelligence and data analytics are going through similar adoption woes. While some companies have complex systems in place, it turns out that of those many systems are underutilized and underleveraged because the business isn’t enforcing their use, or because employees fail to understand the value they provide. Meanwhile, competitors may be retooling their corporate cultures to require and inspire employees to use data in ways that lead to competitive advantage.
“The worst thing is investing millions or tens of millions of dollars in infrastructure to help people make decisions and then they don’t use it,” said Jason Beres, vice president of product management at Infragistics, a company that provides data visualization components. “People don’t know how to use it, they reject it, they say it’s too hard to use. There might be pockets of people who mastered reporting or analytics but the majority of employees aren’t using the solution. Then it becomes a joke in meetings. Oh, that.”
Historically, business intelligence and data analytics tools were used by a relatively small subset of employees in the form of executive dashboards or complicated applications that were too technical and difficult for the average person to use. Increasingly, key performance indicators (KPIs) are being integrated into more job functions, however. While some departments have always measured success “by the numbers,” such as finance, sales, and manufacturing, only more recently have other job functions (such as marketing) adopted data-driven practices.
For example, the new focus on analytics allows marketers to understand customer behavior more deeply within and across online and offline marketing channels. The constant flow of timely data allows them to adjust campaigns in near real-time. Major retailers including Staples are tying together marketing, inventory, and customer support so they can avoid errors such as selling a product via a website that is not actually available, which can lead to a customer service crisis.
As companies become more sophisticated about their use of data, the question becomes how to use the data in ways that optimize the contributions of individuals, the performance of departments, and the overall success of the business. The best way to create a data-driven enterprise is to adopt a data-driven culture.
Creating a Data-Driven Culture
Businesses that recognize the strategic value of data are doing more than just making technology investments. They are adjusting their cultures to more effectively compete on data using various “carrot and stick” methods.
Mandates. Some companies are integrating data-driven businesses practices into their corporate policies. One example is requiring employees to back up their insights and recommendations with live data rather than with assumptions or personal opinions.
The U.S. Defense Intelligence Agency and one of the joint chiefs of staff used to make presentations to The White House using static PowerPoint presentations. During the night prior, analysts would gather the information and generate the presentation which was printed and bound. In the meantime, CNN might be reporting the latest developments live.
“By the time the information was presented it was already out of date,” said John Crupi, CTO of JackBe, an agile BI platform provider. “Instead of calling people to get updates, why not present a live PowerPoint that’s connected to the live data?”
One the world’s largest construction firms went as far as redesigning departmental portal pages as a means of forcing employees to pay attention to dashboards.
“In order to get people to actually look at their dashboards, they created an entire infrastructure of websites and portal home pages,” said Crupi. “Users did not choose to see the information; it was forced on them by management. It was not enough to say, ‘Go do it.’ The mandate needed to come from the top.”
Training. Some companies are investing in training hoping that employees will learn how to apply data-driven techniques to their jobs. This may include in-house training by tech-savvy people within a business unit, training by a vendor or IT, or encouraging people to attend conferences and seminars.
“If the technology is mandated, people then realize that they need to do this to keep their job. But without the proper training, the initiative is doomed to fail,” said Chamal Reyes, program manager at University of Houston System at Sugarland. “Typically, there's one training session and everyone is expected to go full steam ahead. This rarely gets the desired result. Group training sessions help set the stage, but more individualized attention throughout the whole transition is what will make the adoption a success. There needs to be a couple experts that everyone else trusts to help understand the finer details.”
Hiring data-savvy people. Some organizations are hiring data-savvy employees from the C-suite on down. Data-savvy executives are being brought in to retool the culture while data-savvy workers are hired to accelerate the organization’s ability to leverage data.
Source: McKinsey Global Institute
Last year, McKinsey Global Institute estimated that by 2018, the U.S. will need 1.5 million data-savvy managers and as many as 490,000 workers with “deep analytical skills.” People with “deep analytical skills” are not the average worker. They are analysts, statisticians, and data scientists that highly competitive companies use to discover new ways of leveraging data.
Empowering Users. Representatives from business units or departments often work with IT to define their use cases or reports hoping that IT builds a solution that delivers actual business value. The process can take months or even years, which is one reason why “self-service” is becoming more popular. Self-service strategies allow users to define and run their own reports, define KPIs, and even the way information is displayed.
“If IT is singularly creating BI solutions and the solutions don’t meet user requirements, people will just dump the data into Excel and do it themselves,” said JackBe’s Crupi. “If you give people the tools to do their own analysis then I guarantee they are more likely to use it because they’re building it.”
Because resistance to change is a major cause of IT project failures, some businesses are involving user representatives earlier in the technology adoption cycle to help define the problems and the solutions.
“One way to approach the human part of change is engaging people before something new is needed,” said change management consultant Rick Maurer of Maurer & Associates. “Then when a change is called for, people are likely to see that something new is [necessary].”
Offering incentives. Some companies offer employees financial or professional incentives when they master data-driven techniques or when they adopt new data techniques, such as speeding fraud detection, preventing crimes, or identifying new markets.
“In many instances, technology deployment is based on operational or underlying cost reductions,” said Brad Kassel, client principal, Professional Services at Avaya. “Goals such as greater productivity or enhanced collaboration are much harder to quantify, are rarely articulated, and subsequently not clear to the final user population. Hence, the need to resort to incentives or mandates.”
Balancing the Business and User Needs
Given the accelerating velocity of business, companies are necessarily becoming more agile. While large enterprises tend to have complex BI systems in place, some of them are also using lighter weight quick-to-deploy solutions that not only get relevant information into the hands of users faster but also are easier to use.
Some companies have massive BI deployments but aren’t using their reporting infrastructure because the buy-in wasn’t so great, the tool doesn’t fit departments’ needs, or people don’t want to learn how to use the tools, said Infragistics’ Beres.
Quite often, supplemental solutions are deployed or apps are built to solve specific problems. Departments may bring in their own tools, which may have a negative effect on the IT infrastructure (such as creating security vulnerabilities). One approach is to define security policies and put governance practices in place that govern how technology is adopted, deployed, and secured.
“If you have platforms that have governance in place why not let users build their own reports or dashboards as long as you know which data sources are feeding into it?” said JackBe’s Crupi. “Customers say they want to put things together without having to ask a developer to do it. They want connectivity to information rather than raw data so they can pull out what they need to build their own dashboards. Then, if they can’t do the statistical analysis on it, they go back to the people who can.”
Infragistic’s Beres agrees.
“If you are using data for competitive advantage you are wise to make sure that you have a security policy and governance in place for file access,” said Beres. “An employee might go out and find a solution that helps him get his job done because it’s faster than waiting for IT to deliver it. But you still need IT to do linking when there’s a security configuration; and if you want more people to use it you may need domain authentication.”
Maturity is Defined by Culture
Companies can ill afford to adopt business intelligence, data analytics, or any other type of technology for technology’s sake alone. While new technologies bring with them new opportunities for technology-based competitiveness, it is the application of the technology that actually matters.
Corporate maturity as it relates to data use comes in two basic forms:
- How the data is actually used and
- How culture has evolved to enable data-driven competitiveness.
The existence of data is unremarkable in itself. Because data is continuing to grow exponentially, it is becoming more important than ever to surface relevant data. Data visualizations speed the understanding of things like project status or manufacturing yields. Yet, the true value of data is taking action in a manner that benefits the business. If sales are down, why are they down, in which location(s) are they down, and what should be done about it? The companies turning information into appropriate action are the ones reaping greatest return on their data investments.
Getting there is the hard part. Implying that use of data is important, such as by providing training in the absence of follow up is only a first step. The next step is to make it a job requirement through mandates, monitoring, and the rewriting of job descriptions (which may influence who is hired and who is retained).
Offering incentives and encouraging data exploration are not something most companies have yet considered. While it’s one thing force employees to use data, it is another to reward them financially or professionally for mastering new skills or applying their skills in innovative ways.
Even the most sophisticated companies admit they’re not perfect. Yesterday, they were trying to understand information inside the company. Today, they’re attempting to correlate that with external information from social media networks and information feeds to develop new levels of understanding (such as customer sentiment outside the CRM system).
Bottom line, technology even in the form of business intelligence and analytics only enables business competitiveness, it does not guarantee it. Competing on data requires cultural adjustments, from the C-suite on down, that not only ensure the strategic use of data but encourage innovation as well.