The company itself has come up with one example, the horizontally targeted Business Flow, which was announced at its recent Conf2018 event in Orlando. But Splunk Senior VP Senior VP for IT Markets Rick Fitz sees a classic business solutions model evolving for the company.
The formal arrival of the Biz/Ops capabilities has opened up market opportunities that the company has not the range of working expertise – nor the desire – to address directly. That is the balliwick of specialist partners that can take the Splunk tools, match them to their specific market sector expertise, and create new services for a wide range of customers.
The first steps along this path emerged at last year’s Splunk conference, and since then Fitz has been working closely with the small, but growing, group of customer beta testers, which led to the appearance of Business Flow. There will be more core tools to come, but most of the development now he expects to see from the channel partners exploiting their niche market expertise.
Most recently, Splunk has been working on defining various different types of business use case and problem areas where users have traditionally had what he calls 'a poor experience’. He is also looking at who the end user should be for Biz/Ops services and what their expectations and experience might be:
So we are trying to improve those experiences. The people trying to solve these business issues are much more process oriented rather than machine data oriented. They are definitely more on the business analyst or the process analyst side. They have titles like product owner or service owner, and their job, from the CIO’s perspective, is to perfect the customer experience.
With that focus, of course, it should not be necessary for them to be concerned with the technology in order to concentrate on their jobs, which he sees as now being about much more than traditional business intelligence tasks such as generating the weekly, monthly or quarterly reports. Instead, it is now about complex research and analysis about areas such as customer experience and Splunk helping customers to solve their customers’ problems.
Giving the partners a hand
The goal now is to help partners, and some of the Splunk direct customer base, develop tools that can work with modern, fast-changing customer experience issues, for example when it becomes necessary to change the process and to react to it based on the changing demographics they are dealing with.
As an example, Fitz referenced a retail business with a popular, but increasingly 'retro' brand image. Its existing demographic was still good, but inevitably ageing. And while the 18 to 35 year old group knew the product was good and good value, the company’s current approach to the market was not resonating with them. The company was starting to realise it had to change the way it interacted with that group to get them relating to brand, and realising that this meant moving into the world of digital sales and marketing channels:
Splunk having even remotely having this sort of conversation with someone would never have happened a couple years ago.
He sees the next step for the company is to pursue the line started with the appearance of Business Flow and put more business characteristics in the tools so that business analysts can go beyond simply fixing a process but also using it to observe business processes. The thinking here is that every observation actually creates metadata about the business system in its entirety. He feels this can become an important tool for business analysts because it help define and map out behaviour of business systems.
They can, for example, look across 10,000 different user experiences and set them against time, which he suggests will allow them to see aspects of the processes they have never seen before:
We live in a time series world where everything is an event, but in the business world, that's not necessarily true, because first of all when data comes into systems we’re used to structuring it and tucking it away, or dropping it. Then the time dimension isn't necessarily real, it's just a point at which we ran the general ledger or a batch report.
Right now he sees it as really important that businesses have people with the necessary skills to find such data and understand its place in a business process. But given the shortage of people with such skills one possible solution is to solve the problem by removing it as a problem. And one way of achieving that is the empowerment of the `citizen developer’, or more specifically the `tech savvy business executive’ developer.
This is where a tool such as Splunk’s Business Flow could find an unplanned role for itself, reckons Fitz:
I don't think we’ll ever get rid of the need for super smart people to do this data science, primarily, because I think the beauty of data science today is the amount of algorithms that are out there.
Using the algorithm method
This observation approaches the citizen developer issue from another direction, and one that Fitz does see having increasing traction over the coming few years. This is the potential for trickle down of those algorithms which demonstrate either widespread reusability or high specific user value as tools for the channel and reseller partners. If they can demonstrate efficacy at dealing with common business problem X or Y they will make excellent cornerstones for new business operations services pulled together by the partners, concludes Fitz:
Those are people who know how to deal with our relationship with a business. They generally have hundreds of customers, not the tens of thousands that we work with. So we know that this is a perfect play for a channel because they have the extensions, and they have those customer relationships. The analogy is your iPhone or Android device. A few apps are provided by the supplier, but that's not very useful, there's not enough utility in it. But you know the ecosystem will fill the rest, they will come up with the really cool stuff to make it really powerful and sticky.
Here is another example of the trend that technology trickle down is going to open up new markets for the niche market reseller partners of companies like Splunk. It is those partners that have the domain expertise, and as the technology trickles down – in this case re-usable data science algorithms – they will be well-placed to exploit them.