Oracle Autonomous Database is changing business practice
Drop Tank is a small company in footprint–it started with only 22 people–but with an outsized mission to provide loyalty and discount programs to thousands of gasoline retailers. It has been decades since gas stations offered incentives to purchase their products. Last time, in the 1960s, retailers would routinely offer silverware, glassware, and china for fill ups. Alternatively, some would offer Green Stamps–collectable coupons redeemable for merchandise. That was the state of the art for loyalty programs.
All of these arrangements were relatively easy to administer and there was no back-end data to massage. A customer made a purchase and got a reward on the spot. Those were the days! Today’s loyalty programs often capture metadata from the transaction that credits points to a customer’s account and the customer can determine how best to spend them.
Drop Tank started out providing single-use, cents per gallon discount cards to customersin 2012. Today it offers the same fuel discounting scheme but also gift cards and combined offers for gasoline plus consumer packaged goods sold in convenience stores that also sell gas.
Less than five years ago (2016), Drop Tank began designing a back-office system to ride herd on customer gas purchases and the points they accumulated. Any customer could join by adding a phone number which could then be used at the pump to identify the purchaser. The system has been through several iterations in its short life, each time becoming simpler and more efficient and thus better able to support an expanding mission.
Black box
When Drop Tank started out, it produced a small black box device that connected to the pumps capturing customer data and purchases for later upload and processing. The device was needed because 65 percent of retailers are independent and have the ability to choose their POS (point of sale) system. This resulted in integration challenges best met by hardware. But less than ten years later, the black box is gone and the latest iteration leverages the Oracle Autonomous Database which enables several important improvements for Drop Tank and its customers.
Drop Tank’s principal partner is Marathon Oil, a vertically integrated petroleum company that leads in oil refining in the US and runs a large distribution network located primarily in the Eastern half of the US, though recent acquisitions have spread the footprint into the West.
Although the original black box solution was good for its time, installing those boxes at more than 3,500 retail locations was time consuming and expensive, requiring a visit to each retailer.
Tim Miller vice president of technology for Drop Tank, was a co-founder of the company and he has run IT since founding so each iteration of the system was his responsibility to develop, deploy, and maintain–all the incentive he’d need to support continuous improvement.
Over time, Miller has been able to replace the black boxes with server-side software for all of the POS systems popular with his customers, the retailers. Importantly, the evolution of technology in the dealer network mimicked and supported the evolution of increasingly sophisticated services provided by Drop Tank to the retailer and, recently to CPG companies. Consider these milestones,
Stage 1, 2012
Initially, Drop Tank functioned as a promotional products company with cards and codes that dropped the price at the pump. Customers didn’t need to enroll in a program to enjoy savings, but Drop Tank had limited ability to leverage data to engage with them.
Stage 2, 2016
The original cents off system was built on Rackspace and was adequate for the need. But by 2016 Miller and a small team designed an improvement that would take the black boxes out of the equation letting the retailer simply connect a POS system to Drop Tank’s headquarters using Oracle Cloud Infrastructure. It made sense because it reduced the time and expense associated with deploying hardware from four hours per site to 30 minutes. Now all of the integration and conversion could be handled by software. It also appealed to retailers who wanted fewer devices behind the counter connecting to other systems and printers. So, simplification was good for all parties.
The dealer network reacted, and Drop Tank’s new retailer signups doubled..
Stage 3, 2018
With its system built and in place and connected directly to the POS systems Miller and his team discovered they could gather additional point of sales data that other systems either were not capturing or, because there were so many disparate systems in use, no one could easily aggregate. This was in stark contrast to the way other retailers could capture data and provide it to CPG companies. For example, supermarkets can routinely report to CPG vendors not only what sold but what other items made up the transaction.
Enabling business analysis with Oracle Autonomous Data Warehouse
Drop Tank discovered that it could collect data that CPG vendors needed and also provide more information to a growing set of CPG vendors. But the company needed a data warehouse that could handle the load while enabling the company to retain its small size, now a 22 people business. So, finding the right amount of automation was critical. That’s when they turned to Oracle.
While Drop Tank captures a great deal of data in its data warehouse, there are always times when CPG companies might want specialized information that’s not easily available as the system was set up.
It’s a common problem. For years data warehouse users have tried to build a perfect warehouse containing every kind of data and every possible analysis, but that’s not real. So, Miller took the company in a different direction. Today he says, “Don’t try to build a data warehouse that’s perfect, instead, leverage the power of the Autonomous Database,” which he does.
When a CPG customer makes a special request, Miller says that, thanks to the Oracle Autonomous Data Warehouse, Drop Tank can simply spin up a new database automatically in about an hour without the traditional overhead of building, tuning, and maintaining it. “Spinning up a traditional database and tuning it can take days or weeks. Within an hour I can have the database running, within 4 hours we can load data and then within another hour we can have answers. That’s as difference-maker.”
Topping off
Oracle technology has enabled Drop Tank to grow in several ways. Oracle PaaS and IaaS have enabled the company to run its IT in the cloud using a service-oriented architecture (SOA) that helps the company reduce overhead and save headcount. Oracle Autonomous Database enabled the company to branch into providing information services to CPG companies from its starting point as a loyalty program provider. And, Oracle automation has enabled this small company to remain small in headcount but to continue to grow its services while significantly increasing productivity.
New CRM research shows awareness gap
CRM guru, Esteban Kolsky, and I did some primary research paid for by Zoho earlier this year. We wanted to better understand what buyers of CRM systems today were most interested in and to discover their highest priorities. Our survey population comprised more than 200 highly qualified executives and managers (47 percent C-level) in companies with at least 500 employees and ranging to several thousand. All respondents indicated a need to make a CRM purchase decision in the months (not years) ahead. So, we felt our data represented a good measure of current need.
Our findings were what you might expect from such a group though some data points puzzled us. For example, few executives seemed to understand the need for platform technology to support their ambitions. Those aims included taking on the digital disruption and leading their organizations to be more agile, things that platform-based CRM is ideally positioned for. So that seemed like a big disconnect.
CRM all in
After most of two decades where CRM was seen in some circles as a technology suite to keep an eye on but not necessarily purchase, our data clearly showed that most people surveyed see a CRM solution as a necessary additive to business strategy. Most, said they wanted greater technology flexibility (80 percent), increased ability to take on new opportunities (63 percent), and better information sharing among the groups in the front office (60 percent).
Since all of the members of our study had purchased CRM before, the great yearning for technology flexibility speaks to some of the limitations of earlier CRM systems. It also suggests to us pent up demand that could result in a new adoption wave.
These findings are also in line with other research that points to majority CRM purchasers today seeking opportunities for greater differentiation in their markets. You can’t blame them. With CRM well distributed in many markets, the dividend from installing first or even second-generation CRM systems has evaporated. Today, users with systems that only capture and store customer data (systems of record) are being out-competed by businesses that can perform some amount of data analysis and make relevant recommendations about what to do next, integrate other systems easily, and offer support for social media.
The latter systems are often referred to as systems of engagement. In other research I’ve documented an important chain of cause and effect this way. Engagement drives loyalty which drives profits. No wonder there’s so much interest in modernizing CRM. A note of caution though, your notion of engagement might not be the thing that motivates customers to engage.
Best of breed?
Over time I’ve seen the number of disparate best of breed applications in organizations steadily climb from a low of several dozen when I started tracking to many hundreds now. Part of this finding simply reflects the success of cloud computing. As the number of cloud vendors has steadily increased so has the number of apps available. And the cloud technology and business models make it easy to add a new app.
But at some point, which I am confident we’ve passed, the sheer number of different apps capturing and trying to share data produces its own limitations. With hundreds of apps needing to integrate to a CRM suite it becomes more than a full-time job to keep all of the apps synched and the integrations in good repair, even with modern cloud technology.
There are two keys to success in this scenario: 1) limit the number of apps the organization will take in or 2) invent better ways to integrate systems. Good luck with the first idea, departments are now fully capable of bringing cloud-based IT solutions into their workflows without seeking permission. Too often IT only discovers a new app when it is asked to fix something.
The second approach calls for platform technology from a CRM vendor. With platforms a third party builds to the specifications of the platform and the user has a much easier time bringing apps onboard. So it was a great surprise to us that less than ten percent of the executives surveyed had an inkling of the centrality of platform technology to their search.
Another surprise
When I started in this business implementing a CRM system in an enterprise could easily take a year given the complexity of deploying CRM for the very first time. The rule of thumb for a full CRM deployment was that the cost of the effort would easily be two or three times the cost of software thanks to the need for an army of SI specialists. Software costs have been reduced considerably thanks to competition and cloud computing, but the time involved has barely budged though it has been refactored.
In our study 63 percent expected to complete the selection process in 4 to 6 months though a smaller cohort expected it to take upwards of a year. With selection complete 43 percent think purchase to rollout should take 2 to 4 months while an additional 33 percent expect the process to take 4 to 6 months. When everything is laid out and accounted for, the executives still think the process will last a year between purchase and first ROI proof.
Perhaps this can be partly explained by the additional need for setting up AI rules and algorithms and training machine learning systems. Also, some explanation may rest in the need to customize by adding vertical market expertise.
My two bits
We might be in the early stage of a new CRM deployment wave. The situation in the industry and between vendors has changed a lot since cloud computing came to dominate and AI and machine learning made appearances. To a degree platform orientation within a CRM product set could significantly alleviate the need for substantial rip and replace efforts. With a good platform it’s far more likely that a vendor could update customers with new technology in-line with the maintenance process. Yet another reason to pay attention to platforms.
What social can learn from CRM
In The New York Times the other day, Kara Swisher was doing a pretty good impression of a woman at her wits end over social media’s part in recent killings such as in Sri Lanka over the weekend and in New Zealand a few weeks ago.
She wrote in part, “[S]ocial media has blown the lids off controls that have kept society in check. These platforms give voice to everyone, but some of those voices are false or, worse, malevolent, and the companies continue to struggle with how to deal with them.”
Indeed, the social media community seems tied up in knots over what to do about all the abuse happening within their communities but if you look elsewhere you might see signs of solutions that could solve some fundamental problems.
There’s been a chorus of calls from all corners for social media regulation from pundits like me to the halls of congress and even Mark Zuckerberg himself. A few weeks ago, Zuckerberg penned an editorial in The Washington Post saying that the first things we should work on or regulate include, “harmful content, election integrity, privacy and data portability.”
But a quick look at the CRM industry and its use of social media coupled with analytics far outpaces anything Zuckerberg’s company is even dreaming about. The solution that works well in CRM occurs almost by accident and companies like Salesforce are bringing solutions to market based implicitly on a few ideas that the greater social media community could emulate.
Salesforce’s accidental model
Last week I covered some Salesforce announcements and two that stick out are the Einstein Prediction Builder which enables admins and developers to build AI models for apps running on the Salesforce Platform and the other, Einstein Predictions Service enables admins to embed Einstein AI analytics into third-party systems. Here’s what’s interesting about them.
The salesforce customer organization owns its data which is stored in Salesforce and it is discriminate about who gets to access it. Each organization manages a minimal set of rules about who can use its data, what it can be used for, and things like frequency of use. It also tracks who uses the data and for what purpose up to the point of providing reports on customer responses. These are some of the elements of a broader and more professionalized use of social media that could be implemented without a lot of fanfare.
The essence of regulation in our society is that it is bottom up not top down. We just finished tax season and very few of us ever had to consult with a government official or agent who told us what to do and how to file. Instead some of us might file by ourselves and a growing number of tax preparation professionals and software firms handle the rest of the load.
We don’t take our taxes to the barbershop, we take them to people who are certified to do taxes either through specialized training in a tax course or who are trained accountants and lawyers. Also, if you don’t calculate your own taxes the person who did is supposed to sign the form too. That’s everything we should expect in finding solutions to the current social media mess.
Specifics
And it isn’t only tax filing that operates this way. Consider plumbing and electrical work. You are welcome to do it yourself and many people do but for most people and more complicated jobs we’ll gladly hire professionals because they have the right tools and experience. They also have licenses administered by the state which enables them to get a building permit whenever the need to. A job without a permit is liable to be shut down by your municipality for good reasons. Safety and zoning laws are enforced by permits and they help the community to maintain standards and prevent wildcats from doing funky things with the plumbing infrastructure or electric grid.
But there’s a glaring exception when it comes to social media. What was once seen as an elaborate email system has grown to become a world-girding data gathering and analysis effort to help customers gain insights into people’s actions and motivations. By the way, a customer is, as always, the one who pays the bill and for most social media users that’s not you. You’re another category called product.
A humble proposal
Zuckerberg might have a few good points, but he proposes a top down approach when bottom up is much more effective. Top down approaches are often derided as bureaucratic and they are because they require laws to cover all contingencies. In a bottom up world, individuals with a good amount of training make the calls which might not be a perfect situation either but applying local facts to decision-making beats a blizzard of rules.
So, here’s the pitch. If we had a two or three tier approach to social media certification, we could solve a lot of problems. Uncertified do-it-yourselfers could still operate on a personal level but possibly with some restrictions on number of contacts. By analogy you can mess up your own plumbing but not your neighbor’s. A do-it-yourselfer named Mad Dog shouldn’t be able to blast to the world if you recall the purpose of social media is keeping up with personal relationships.
Professional users ought to be required to have as much knowledge as a hair stylist to get a certification and mad dogs need not apply. Real names please. Professionals should be required to put their names or license numbers on their work just like an electrician pulling a building permit.
My two bits
I am under no delusions that these suggestions would change everything about the social media landscape and perhaps that’s a good thing. Social is successful because it’s spontaneous and it fills a need for maintaining human contact. People beyond the age of reason don’t like being told what to do so any regulation needs to be handled with a light touch. Placing responsibility with the actor fosters a sense of agency, a powerful tool for spreading and sharing responsibility. It works in a lot of places. We should try it in social.
Disruption plus
There’s a chicken and egg issue with digital disruption. Making decisions based on numbers instead of gut instinct is recognized to be a superior approach in many situations, but before you can get to decision-making, people have to be able to use things like AI and machine learning. Humans are not naturals when it comes to numbers; thinking back to high school algebra is all it takes to convince most of us.
Humans are really good at things like relationships and reading faces. So there should be a natural association between providing crunched numbers to customer-facing employees and their use. But before you can expect employees to take on thinking with numbers more than they ever have, it’s got to be dead solid easy to crunch the numbers and deliver their meaning. For much of the AI universe so far that crunching and delivery has been focused on things involving a next best algorithm. Next best offer in sales perhaps, or next best service solution in customer service. But there’s a lot more we can do.
Salesforce delivers Einstein analytics for a broader audience
Today, Salesforce announced four new products based on Einstein, its analytics engine, that are designed to spread analytics to more parts of an organization and to enable more types of employees to work with the tools. All introductions support clicks or code thus enabling admins and developers to access functionality according to their skill levels. Briefly the introductions include,
- Einstein Translation which enables admins and developers to set up automatic language translation. If a user enters data in a different language the system instantly converts to that language. There was no statement, however, about how many languages are initially supported. The product is in pilot so look for more information later.
- Einstein Optical Character Recognition (OCR). OCR has been around a long time because it works and is an important part of scraping usable data off documents. Initially Salesforce sees this as a way to streamline data entry. Also in pilot.
- Einstein Prediction Builder enables admins and developers to build AI models for apps running on the Salesforce platform with a declarative setup tool. Generally available.
- Einstein Predictions Service enables admins to embed Einstein AI analytics into third party systems like ERP or HR. Also generally available.
Continuity
In a move that seems like a commentary on the troubles that social media companies are having, Salesforce also restated its commitment to its core values, especially trust in this case. The company went out of its way to state that its AI products are transparent, responsible and accountable. For instance, the system provides users with justifications for predictions based on which factors influence a prediction. Also, protected fields warn of potential bias in datasets with pop-up alerts. And Model Metrics evaluate the accuracy and performance of AI models. If only things like this were available in social media.
My two bits
A few years ago, when sales analytics were the only analytics game in town, I remember some emerging vendors telling me it was hard to get customers to use their tools to develop their own unique analyses. They were happy to use all of the reports that came with the tool out of the box though, which led to delivering a large number.
In my experience this rang true because sales veterans (and I am one) seem highly attached to their unique approaches. At the time I thought that asking them to develop their own analyses was akin to asking a fish to invent fire. In the years since, I discovered that sales people were not unique. So making analytics’ use as easy as possible is a pre-requisite for getting on with a company’s digital disruption.
Clicks and code, the two approaches Salesforce emphasized in this announcement are not out of the ordinary for most things the company enables. They want to reach the broadest audience possible for their solutions and that’s good. But it has extra importance at the intersection of digital disruption and analytics.
Philanthropy is good business
The other day Salesforce announced that it was integrating its philanthropic arm, the non-profit Salesforce.org, into the larger organization, Salesforce.com. This makes a round trip for “the org” as it’s sometimes referred to. At its founding Salesforce built its 1-1-1 model of philanthropy, in which it donated one percent of its equity, product, and employee time to communities around the world, into its core business.
As you can imagine, such an endeavor starts slowly but builds momentum over time and to date Salesforce has donated over 3.8 million hours of employee time and more than $260 in grants. But at some point a few years ago, Salesforce created the org as a public benefit corporation under California law.
That all went along swimmingly until the org developed its own vertical apps including the Salesforce Philanthropy Cloud, Nonprofit Cloud, and Education Cloud and voila, the org was in the software business. But it might not have had all of the resources a software company needs so merging seems sensible.
Salesforce has been playing both a long game and a short one for a long time. The short game is easily understandable–they sell seats of use to corporations. This can include the company’s flagship CRM, partner apps, or development tools for those who want to roll their own apps. This makes perfect sense in the software business.
The longer game, which takes some explaining, is more about culture transfer. As the company has evolved it has helped set standards for modern business and it has used what it built in an eat your own dog food way. That’s partly responsible for the Salesforce culture and it’s something the company is not shy about exporting.
Cloud computing is a good early example of culture transfer. The cloud commoditized computing and made it possible for businesses to both get better and more reliable computing while also saving money. Today there’s virtually nothing you can do in your data center that you can’t do in the cloud, except maybe get hacked.
Cloud wasn’t the only innovation, there’ve been major inflections in social media, and analytics just to pick a couple. At each point the company was selling more than software, it was teaching businesses new approaches and ways of doing business and with that come culture changes. Consider analytics and machine learning. Most of us will consider this just the latest new wrinkle in an industry that has had more than its share. But it leads to a culture change which is what digital disruption is–learning to trust numbers over gut instinct.
The thing is, they’ve been at this so long that Salesforce is actually addressing a new generation of customers and users now and that’s why philanthropy, non-profits and education are so important. It’s doubtful that any of the clouds from the org will generate serious income for businesses that use them. But the real test of their value is in how they help businesses manage culture change.
There have been numerous studies linking a business’ philanthropic efforts with employee job satisfaction and the younger the employee the more significant the effect. Philanthropy Cloud in particular has been instrumental in helping Salesforce to spread its 1-1-1 model around the business world. For instance, there are well over two thousand businesses that have adopted the model, and more being added weekly. But also, major players in the philanthropy world like The United Way, are big users and proponents because the Philanthropy Cloud helps non-profits extend their missions.
So, it’s not too surprising to me to see the two corporations coming back together. Increasingly it’s likely that the non-profit/philanthropic/education solutions will have positive drag-on effects wherever the core technology goes. This looks like one more culture change sponsored by Salesforce and it might be the one with the most lasting power. Social techniques and analytics will be absorbed and blend into a company’s background, but this is different.
Nearly four decades ago business thinkers decided that a company’s main and perhaps only responsibility was to the shareholders. Prior to that, there was a more nuanced view of stakeholders which included shareholders but also included employees, customers, and the community at large. Perhaps this begins to rebalance that trend.
